GENDER DIMENSION OF SOCIAL CAPITAL AND 
ITS EFFECTS ON RURAL HOUSEHOLD WELFARE IN 
OSUN AND ONDO STATES, NIGERIA  
     
 
 
 
Timothy Olusola  AGBOOLA 
MAT: NO 85329 
B. Agric. Ilorin 
M.Sc. (Agric Econs), Ibadan. 
 
 
A THESIS IN THE DEPARTMENT OF AGRICULTURAL ECONOMICS 
SUBMITTED TO THE FACULTY OF AGRICULTURE AND FORESTRY IN 
PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF 
THE DEGREE OF  
 
 
DOCTOR OF PHILOSOPHY 
 
 
OF THE 
 
UNIVERSITY OF IBADAN 
 
 
 
 
 
JULY, 2012 
 
 
 
ABSTRACT 
Social capital is trust and willingness to live by the norms of one’s associates. 
This household welfare asset has the potential to break the poverty cycle. However, 
there is little evidence on gender sensitivity of the effect of social capital on welfare 
status in Nigeria. Hence, gender dimension of social capital and its effects on rural 
household welfare in Osun and Ondo states, Nigeria were investigated. 
A multistage random sampling technique was employed for the study. Osun 
and Ondo states were selected from the six states in Southwestern Nigeria. Eight 
Local Government Areas (LGAs) were selected from each state. Thereafter, five 
communities were selected from each LGA. Three hundred and seventy respondents 
were selected from all the communities based on probability proportionate to size. 
Data were collected using structured questionnaire on socio-economic characteristics 
and social capital dimensions; group and network; trust and solidarity; Social 
Cohesion and Inclusion (SCI); collective action and cooperation; Information and 
Communication (IC); and Empowerment and Political Action (EPA).  Attendance at 
associations’ meetings is the number of times present on monthly basis. The mean per 
capita household expenditure was used as a proxy for welfare. Data were analysed 
using descriptive statistics, multiple and Tobit regressions at p= 0.05. 
Male Headed Households (MHH) constituted 51.3%. Mean age of MHH and 
Female Headed Households (FHH) was 44.1 ± 2.2 and 42.3 ± 1.2 years respectively. 
The mean household size was 6.2 ± 2.3 and 5.1 ± 1.4 for MHH and FHH respectively. 
Average meeting attendance by both sexes was two out of five.  Density of 
membership index in association was 0.30 and 0.34 for MHH and FHH respectively. 
MHH had 0.73 index of participation while FHH had 0.58. FHH were more involved 
in IC (0.69) compared with MHH (0.46). The SCI index was 0.47 for MHH and 0.65 
for FHH. Male household heads had higher EPA (0.67) compared with FHH (0.21). 
On the average MHH participated in three of five decision- making and two for FHH. 
Monthly cash contributions of male and female heads were N895.90 ± N55.37 and 
N985.67 ± N72.11 in 2007 respectively. Monthly average labour contributions for 
MHH and FHH were 2.4 ± 0.3 and 3.2 ± 0.1 mandays respectively. There was no 
significant difference between MHH monthly per capita expenditure (N2, 936.67 ± 
N143.43) and FHH (N3, 221.82 ± N104.10). Aggregate social capital enhanced 
ii 
 
 
welfare of MHH and FHH by 0.503 and 0.681 respectively. Meeting attendance 
reduced welfare for both sexes by 0.258. Participation in decision- making increased 
welfare of MHH and FHH by 0.714 and 0.812 respectively. Increase in household 
size reduced welfare for both sexes by 0.782. Increase in age reduced welfare of 
MHH and FHH by 0.225 and 0.319 respectively. Increase in level of education 
increased welfare of MHH (0.123) and FHH (0. 913) indicating that female benefit 
more. 
Social capital influenced welfare of female headed households more. 
Participation in decision- making, and level of education enhanced households` per 
capita expenditure. Household size, meeting attendance and age negatively affected 
households’ welfare.  
Keywords: Social capital, Gender disaggregation, Household welfare.   
Word count: 499 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ii 
 
 
ACKNOWLEDGEMENTS 
 
 The path towards completing a PhD programme is no doubt full of ups and 
downs which requires the support, encouragement and at times criticisms of various 
individuals. This perhaps aptly describes my journey so far and since it would be 
impossible to list all of them, it would therefore amount to being an ingrate, if I failed 
to faithfully acknowledge a selected few.  
My sincere appreciation goes to my supervisor, Professor MAY Rahji for his 
thorough supervision and kindness. I am very grateful to him for his painstaking and 
commitment to effectively go through my first and second seminar papers as well as 
the draft thesis. I am indeed very privileged to have been supervised by him. Without 
mincing words, his positive criticisms have really contributed to the quality of this 
work. 
In addition, the contributions of my supervisory committee, Professor A.E Ikpi 
and Dr. A Adeoti are highly appreciated. I thank them immensely for their 
encouragement and suggestions. Their contributions assisted in no small measure to 
the success of this work. 
I equally salute the love and unity being radiated in the Department of 
Agricultural Economics throughout my period of study here. I would like to thank the 
H.O.D. Prof.V.O Okoruwa for being a father and mentor. I am indeed grateful to the 
head of the postgraduate committee, Dr S.A Yusuf for his suggestions and 
contributions towards making the work a huge success. I cannot  but acknowledge the 
support (moral, spiritual and academics) of Dr.B.T Omonona. Infact he relates with 
me not only as a student but as a brother and friend. May the Almighty God continue 
to be with him. I am also grateful to Dr T.T Awoyemi and Dr Kemisola Adelegan for 
their assistance and encouragement at all times. 
To other members of staff of the Department, Prof. Okunmadewa,  Dr Oni, Dr 
Oyekale, Dr Sanusi,  Dr. and Dr (Mrs) Obayelu, Dr. Salimonu,  Dr Oluwatayo and Dr  
Adepoju, I say thank you all and God bless. I sincerely appreciate the contributions of 
Dr Temidayo Apata and Dr Femi Agbola. My colleagues in and outside the 
Department including Dr O.L Balogun, Dr J.O Saka, Pastor Akinsola,  Ayandiji, 
Akinleye, Olugbenro, Oluokun, Funmi Adepegba, Funmi Osoba and Francisca  are 
also highly appreciated. 
iii 
 
 
I wish to place on record the moral contributions of my age-long friend Pastor 
Ojo Olasupo, Mrs Lawson, Mrs Atanda, Mrs Oladejo,  Mr Animasaun and Nike of the 
departmental office. My appreciation equally goes to my immediate family, my 
daddy, Pa Samson Agboola, and my mum, Mrs Agnes Agboola. Thank you for 
bringing me forth into this world and setting my foot on the right path. Your prayers 
have in no doubt been seeing me through all my endeavours. I also thank my siblings-  
Segun, Sunday, Biodun,  Chioma, Rev. Biodun,  Bayo, Gbemi, Tobi and Bukola to 
mention a few. 
I wish to thank most sincerely and specially, my wife Oluyemisi Adetoun 
without whom the whole story will be incomplete. As my inestimable jewel, she has 
continued to be there for me day and night without been discouraged. I will forever be 
grateful to you. Thank you dear for helping to see my dream come true. To my kids, 
Toluwani, Temiloluwa, Oluwatoyin, Joshua and Iyanuoluwa, my prayer is that God 
will in his mercy take you to places. Thank you all for being there all through the 
thick and thin periods. I love you all. 
Finally, to Him who belongs the heavens and the earth all that they contain, I 
am grateful to him that made me what I am and still will be, the Almighty God.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
iv 
 
 
CERTIFICATION 
I certify that this PhD thesis was carried out by Timothy Olusola AGBOOLA under 
my supervision in the Department of Agricultural Economics, University of Ibadan, 
Ibadan, Nigeria. 
 
 
                 
 
 
 
 
--------------------------------------- 
Professor M.A.Y Rahji 
B.Sc Agric., M.Sc, PhD Agricultural Economics (Ibadan) 
 
 
 
 
 
 
 
 
 
 
 
 
v 
 
 
TABLE OF CONTENTS 
Title             i 
Abstract          ii 
Dedication          iii 
Acknowledgements         iv 
Certification          v 
Table of Contents                                                                                                  vi 
List of Tables                                                                                                        x 
List of Figures                                                                                                        xi 
CHAPTER ONE: INTRODUCTION 
1.1 Background to the Study                                                                                    1 
1.2  Problem Statement                                                                                             3 
1.3  Objectives of the Study                                                                                      6   
1.4 Justification of the Study                                                                                     7 
CHAPTER TWO: THEORETICAL FRAME WORK AND  
REVIEW OF LITERATURE  
2.1 Theoretical Framework                                         9 
2.2 Social Cohesion and Solidarity       16 
2.3 Social capital and trust        17 
2.4 Dimensions of social capital       18 
2.5 Social capital and welfare       19 
2.6 Literature review        20 
2.7 Forms of Social Capital       27 
2.8  Importance of Social Capital       28 
2.9  Channels of Social Capital       31 
2.10 Attributes of Social Capital        32 
2.11 Production of social capital       32 
2.12 Determinants of Social Capital       36 
2.13 Measurement of Social Capital        36 
2.14 Social capital and asset accumulation      38 
2.15 Social Capital and Community Participation.     40 
2.16 Gender Dimensions and Social Capital     41 
2.17 Gender and involvement in politics      42 
vi 
 
 
2.18 Social capital and social inclusion      47 
2.19 Social capital and Social cohesion      48 
CHAPTER THREE: RESEARCH METHODOLOGY                                                                                                                               
3.1 Study Area         50 
3.2 Method of Data Collection       51 
3.3. Analytical Techniques        55 
3.3.1 Descriptive Statistic        55 
3.3.2  Principal Component Analysis      55 
3.3.3 Social Capital Index        57  
3.3.4 The Aggregate Model        59  
3.3.5 The Disaggregate Model       61 
3.3.6 Tobit Regression Model Asset Accumulation    63 
3.3.7 Tobit Regression Model Access to Credit     64 
3.38 Tobit Regression Participation in Collective Action    66 
3.4 Definition of Variables and Concepts      67 
CHAPTER FOUR:  RESULTS AND DISCUSSIONS  
4.1 Demographic and Socio-Economic Characteristics of Household Heads.  70 
4.2 Different Types of Local Level Institutions and Household Membership 75 
4.3 Sampled Households Density of Membership     75 
4.4 Sampled Households Group and Network index     78 
4.5 Household Information and Communication index    80 
4.6 Sampled Households Empowerment and Political Action index   82 
4.7 Household Meeting Attendance        82 
4.8 Household Decision making index      82 
4.9 Household Heterogeneity Index       85 
4.10 Sampled Households Cash contribution index     85 
4.11 Sampled Household labour contribution index     88 
4.12 Sampled Households per capita expenditure     88 
4.13 Summary Statistics of Social capital dimensions     91 
4.14 Social capital dimensions and Household heads Educational status  93 
4.15 Social capital dimensions and Age Distribution of the Household Heads 95 
4.16 Social capital dimensions and Household Size     95 
4.17 Gender Dimensions in Building up Social capital    98 
vii 
 
 
4.18 Household heads welfare indicator by level of Social capital   99 
4.19  Household Income Model        101 
4.20 Household heads Welfare and Social capital; Aggregate model  104 
4.21 Social capital and Household heads welfare; Two way Causality  109 
4.22 Social capital effects on Asset Accumulation     111 
4.23 Social capital and Access to credit      114 
4.24 Social capital and Collective Action      117 
CHAPTER FIVE: 
 SUMMARY, CONCLUSION AND POLICY RECOMMENDATIONS   
5.1 Summary of Major Findings       120 
5.2 Conclusion         123 
5.3 Policy Recommendations        124 
5.4 Contribution to Knowledge       125 
5.5 Philosophy of the Study        126 
5.6 Suggestion for Further Research       126 
REFERENCES         127 
APPENDIX 1          142 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
viii 
 
 
 
LIST OF TABLES 
TABLE 
Table 1 Comparison of women representation in 2003 and 2007 general elections- 46 
Table 2 Sample Frame for the study------------------------------------------------------ 54 
Table 3 Demographic and Socio-Economic Characteristics of Household Heads- 72 
Table 4 Household heads characteristics-------------------------------------------------- 74  
Table 5 Different types of Local Level Institutions and household membership---- 76  
Table 6 Sampled Households’ Density of Membership Index--------------------- 77 
Table 7 Sampled Households Group and Network index--------------------------- 79 
Table 8 Sampled Household Information and Communication index------------- 81 
Table 9 Sampled Households Empowerment and Political Action index------- 83 
Table 10 Households’ Meeting Attendance----------------------------------------------- 83  
Table 11 Households’ Decision Making Index------------------------------------------- 84 
Table 12 Household Heterogeneity Index------------------------------------------------- 86 
Table 13 Sampled Households Cash contribution index-------------------------- 87 
Table 14 Sampled Household labour contribution index----------------------------- 89 
Table 15 Sampled Households per capita expenditure------------------------------ 90 
Table 16 Social Capital Dimensions and Gender----------------------------------------- 92 
Table 17 Social capital dimensions and Household heads Educational status--- 94 
Table 18 Social capital dimensions and Age Distribution of the  
   Household Heads--------------------------------------------------------------- 96 
Table 19 Social capital dimensions and Household Size---------------------------- 97 
Table 20 Household heads welfare indicator by level of Social capital------------ 100 
Table 21: Household Income Model------------------------------------------------ 102     
Table 22 Aggregate Social Capital Index and Gender---------------------------- 107 
Table 23 Social capital and Household heads welfare; Instrumental Variable -- 109 
Table 24 Social capital effects on Asset Accumulation-------------------------------- 112 
Table 25 Social capital and Access to credit-------------------------------------------- 115 
Table 26 Social capital and Collective Action------------------------------------------- 118
       
 
ix 
 
 
             
LIST OF FIGURES 
FIGURE     
1 Complexity between the determinants and consequences  
of social capital        9  
2 Relationships between determinants, structure and  
consequences of capital.       11 
3  Depreciation of social capital over time without reinforcement  
While norms of membership and belonging are likely to  
increase over time.        12  
4 Location of social capital within the framework of micro level  
social capital interactions       16 
5 Map of Osun and Ondo States showing the Senatorial Districts  53
    
x 
 
 
CHAPTER ONE 
  
1.1 Background to the Study.  
Social capital is an important factor in building and maintaining collective 
action (Krishma and Uphoff, 1998; Pretty and Ward, 2001; Putnam, 1993; Scoones, 
1998; Woolcock, 2001). However, analysis of causal relationships between improved 
welfare and collective action has hitherto centred on the existence and /or creation of 
appropriate institutional and mutual arrangements (Bromley,1992; Leach et al; 1999). 
There is an emerging recognition that relations of trust and common values are 
important to collective action (Pretty and Ward, 2001; Uphoff, 2000 Lyon, 2000). The 
concept of social capital resources ― from which people draw when pursuing different 
livelihood strategies requiring coordination and collective action‘‘ has received much 
attention (Scoones, 1998).   
Coleman (1998) defines social capital as ―a variety of different entities, with 
two elements in common: they all consist of some aspect of social structure, and they 
facilitate certain actions of actors – whether personal or corporate actors – within the 
structure‖. According to Putnam (1995) ‗‗social capital refers to connections among 
individuals—social networks and the norms of reciprocity and trustworthiness that 
arise from them‖. Fukuyama (1995) defines social capital in terms of cultural values 
such as degrees of compassion, altruism, and tolerance. Although an exact meaning 
remains elusive, these definitions have common elements that point to a solid base for 
a formal definition.  
Towards this end, Woolcock (2001) defines social capital as norms and 
networks that facilitate collective action. Formation of groups and other forms of civic 
activity or collective action are at the heart of this definition.  In addition, gender 
relations played a significant role in mediating the translation of economic benefits 
into the wellbeing of an individual, family and community. In this study, it is argued 
that the role of gender differences may be of particular importance in understanding 
the creation of social capital in order to sustain households‘ welfare.  
The gender dimensions and the effects of social capital on rural households 
have been identified as key factors shaping people`s access to and use of resources 
that could improve their welfare (Agrawal, 2000; Cleaver, 1998a). However, most 
discussions of social capital appear to have been almost gender blind (Molyneux, 
1 
 
 
2002) or even critical towards women‘s role in the formation and maintenance of 
social capital (Riddel et al; 2001). As a result, the analysis of gender biases of social 
capital is a collective action that (re)produces gender discrimination and reinforces 
male dominated power structures.  
This excludes women from participation in decision making. Thus, the 
hypothesis that gender influences welfare improvement through gender related social 
capital dimensions, stocks, and usages of social capital requires examination and 
empirical testing. The classification  of social capital as ―institutional‖ based on 
transactions governed by roles, rules, procedures, and organizations or as ―relational‖ 
governed by norms, values, attitudes, and beliefs suggests that different strategies are 
needed for building social capital to support collective action and to improve 
household welfare. Krishna (2000) indicates that in situations where rules, procedures 
and organizations are in place to support collective action but mutual trust is low and 
little value is placed on collaboration, interventions will be needed to build trust and 
the willingness to work together, and create relational social capital.  
This study intends to establish the linkages of social capital dimensions to 
welfare. This is because the distinction between relational and institutional social 
capital is highly pertinent to understanding the implications of gender differences. 
Therefore, the neglect of the gender dimensions of social capital in such linkages 
might engender to misleading conclusions. Even then, the recognition that social 
capital as an input in a household‘s or a nation‘s production function has major 
implications for development policy and project design.  
This tends to suggest that the acquisition of human capital and the 
establishment of physical infrastructure need to be complemented with institutional 
development in order to reap the full benefits of such investments. The promotion of 
social interaction among poor farmers may need to complement the provision of seeds 
and fertilizer. While there are many definitions and interpretations of the concept of 
social capital, there is a growing consensus that it stands for the ability of actors to 
secure benefits by virtue of membership in social networks or other social structures 
(Portes, 1998). If one takes a broad view of what is comprised by these other social 
structures, then social capital is a relevant concept at the micro, meso, and macro 
levels (Grootaert,1999; Portes, 1998; Woolcock, 1998;  Narayan, 1999). At the macro 
 2 
 
level, social capital includes institutions such as government, the rule of law, civil and 
political liberties, etc.  
There is overwhelming evidence that such macro level social capital has a 
measurable impact on national economic performance (Knack, 2000). At the micro 
and meso levels, social capital refers to the networks and norms that govern 
interactions among individuals, households and communities. Such networks are 
often, but not necessarily, given structure through the creation of local associations or 
local institutions. Putnam (1993) focuses primarily on horizontal associations in 
which members relate to each other on an equal basis, Coleman (1988, 1990) 
however, argued that social capital can include ―vertical‖ associations as well, 
characterized by hierarchical relationships and unequal power distribution among 
members. The analysis in this study is limited to social capital at the micro 
(individuals, households) and at the meso (community) level. The broader definition 
which includes both horizontal and vertical associations is utilized in this analysis. 
The objective of the study is thus to investigate empirically the links between social 
capital and household welfare in the case of Osun and Ondo states, Nigeria. 
 Specifically, a multivariate analysis of the role of local institutions as 
affecting household welfare and poverty is undertaken. The term local institution, 
local association and local organization are used interchangeably as done in most 
social science literature (Uphoff, 2000).  
 
1.2 Statement of Problem 
 The gender dimensions of social capital within the rural households have been 
identified as key factors shaping people`s access to and use of resources that could 
improve their welfare (Agrawal, 2000; Cleaver, 1998a). However, most discussions of 
social capital appear to have been almost gender blind (Molyneux, 2002) or even 
critical toward women‘s role in the formation and maintenance of social capital 
(Riddel et al; 2001). As a result, the analysis of gender biases of social capital within a 
collective action regime that (re)produces gender discrimination and reinforces male 
dominated power structures is of research relevance in the Nigerian context.    
One area in which social capital literature is lacking is gender (Kilby 2002). 
Ethnic and gender dimensions of social capital remain under-recognized (Fox 
Genshman, 2000). In the literature, social capital is generally conceptualized as 
 3 
 
gender blind, paying little attention to gendered intra household issues of power and 
hierarchy (Norton, 2001; Silvey and Elmhirst, 2003). Silvey and Elmhirst (2003) 
argued that a more complete picture of social capital, is specifically one that includes 
attention to the gendered and intergenerational conflict and hierarchies within which 
social networks are forged. Discussions on the gender aspects of development and 
environment have their origin in the theories of Women, Environment, and 
Development (WED). These theories highlight women as having a special 
relationship with the environment due to their responsibilities to their families and 
concern for the wellbeing of future generations (Jackson, 1993; Manion, 2002; 
Martine and Villarreal, 1997).  
In this respect, women are seen as a ―a transcultural and transhistorical 
category of humanity with an inherent closeness to nature‖ (Jackson, 1998). They are 
thus likely to be the principal managers of the environment at the community level. 
Despite the case for viewing gender differences and gender relations as influential in 
local association decisions, gender has been largely absent from efforts made to 
define social capital (Molyneux, 2002; Riddell et al, 2001). However, several studies 
have found that men and women may have different kinds and qualities of social 
capital. This is based on differences in their social networks, values of collaboration, 
levels of conflict and capacity for conflict management, social cohesion and welfare 
improvement of their households. 
Gender differences in several aspects of social capital have also been 
identified or hypothesized, but these two strands of analysis in the literature have not 
been well integrated. Several important and unanswered questions have practical 
implications for policy and program design. Hence, to what extent do women and 
men demonstrate differences in household welfare outcomes based on collective 
action? Do women tend to build and use social capital more readily than men? and if 
so, is this associated with greater differences in household welfare improvement? The 
family is the main source of economic and social welfare for its members. It is the 
first building block in the generation of social capital for the larger society.(Bubolz, 
1998; Hogan, 1998).  
As a result of differing social networks and correspondingly different levels of 
access to information, men and women face different economic consequences within 
the household and/or family.  Women are generally poorer than men because they 
 4 
 
lack the range of social capital endowments, which male members of their households 
tend to enjoy (Kabeer, 1990). Men‘s networks tend to be more formal, since they are 
more often involved in formal employment. Male networks include more co-workers 
and few kin than women‘s network (Moore, 1998). Traditionally, women are 
responsible for household‘s welfare and child rearing. As a result, reliance on 
informal exchange networks is necessary among women and their households so as to 
share resources, stabilize incomes and reduce risks. This study contributes to the 
literature by providing evidence of gender disparities in the access and exchange of 
information in south west Nigeria.    
Social networks of impoverished women are found to be important to them to 
obtain income and other necessities (Narris, 1985). Gender discrimination squanders 
trust, hinders family relations, restricts social networking and depletes social capital 
and the capacity of societies to work towards common goals (Picciotto, 1998 
There is considerable debate and controversy over the possibility, desirability 
and practicability of measuring social capital, yet without a measure of the store of 
social capital, its characteristics and potential remain unknown (Durlauf 2002b; Falk 
and Harrison 1998). Measurement attempts are flawed by problems with separating 
forms, sources and consequences (Adam and Roncevic 2003; Onyx and Bullen 2001; 
Sobels et al. 2001). An example is trust, which is commonly seen as a component of 
social capital. Some authors equate trust with social capital (Fukuyama 1995; 
Fukuyama 1997). Some see trust as a source of social capital (Putnam et al. 1993). 
Some see it as a form of social capital (Coleman 1988), and some see it as a collective 
asset resulting from social capital construed as a relational asset (Lin 1999).  
Collier (2002) asserts that social capital is difficult, if not impossible to 
measure directly and that for empirical purposes, the use of proxy indicators is 
necessary. Social capital has constructs that are inherently abstract. They require 
subjective interpretation in their translation into operational measures. These are 
invariably indirect surrogates of their associated constructs (Grootaert et al. 2002; 
Narayan and Cassidy 2001). Callahan (1996) opines that while it is hard to measure 
social capital directly, it can be inferred from its powerful effects. The choice of 
indicators to measure social capital is also guided by the scope of the concept and the 
breadth of the unit of observation used (Collier 2002). Social capital is such a 
complex concept that it is not likely to be represented by any single measure or figure.  
 5 
 
Aldridge and Halpern et al (2002) cautions that some of the empirical 
evidence on the importance of social capital for economic and social outcomes needs 
to be treated with caution. This is because of the mis-specification or ambiguity of 
equations or models used to estimate its impact. Without a rigorous method for 
measurement it is unclear how the benefits are ascertained and tested. Despite the 
problems with its definition, operationalization, measurement as well as its 
metaphorical character, social capital has facilitated a series of very important 
empirical investigations and theoretical debates. These have stimulated 
reconsideration of the significance of human relations, networks or organizational 
forms for the quality of life and of developmental performance.  
The following research questions guide the execution of the study. What are 
the main components of social capital? How do some relevant socio economic 
variables influence social capital index? To what extent do the components of social 
capital affect household welfare based on gender?  What are the roles of social capital 
in facilitating access to credit, asset accumulation, collective action and institutional 
support? How and to what extent have men and women benefited from the social 
capital build up?   
  
1.3   Objective of the Study 
The general objective of this study is to analyze empirically, the gender dimensions of 
social capital on household welfare in the study area. The specific objectives are to: 
(1) identify the social capital components from which to  construct the  social 
capital index; 
(2) ascertain the effects of social capital components on male and female 
household heads welfare; 
(3) determine  the effects of social capital components on asset accumulation; 
(4) examine the influence of social capital components on  access to  credit, 
and  
(5) analyse the effects of social capital components on collective action. 
 
 
 
  
 6 
 
  1.4 Justification for the Study  
Women as primary care givers are seen as playing a critical role in the process 
of social capital formation. The social capital thus generated is an important means 
by which women gain access to resources and economic opportunities thereby 
helping them to find an exit path out of poverty. A gender analysis of the impact of 
the improved groundnut production technology introduced in Mahanrastra, India 
during the 1980s led to the conclusion that gender is a key variable in relation to 
labour activity pattern, time use and crop product utilization and perceptions of needs 
of new technology development (Kolli and Bantilan, 1997).  
Information of this kind provides evidence that gender makes a difference in 
economic circumstances. The idea that society matters for economic growth is not a 
novelty in the economic debate. As pointed out by Coleman (1990), the interaction 
between the organization of a society and its economic performance was once 
considered the fundamental question of political economy.‖ Despite its 
acknowledged importance, this issue has been neglected by the contemporary 
economic literature. During the last decade and due to spurs coming from the other 
social disciplines, the recent emergence of indigenous growth theories in economics, 
we have witnessed a real explosion of the number of studies addressing the social 
roots of growth. These are often grouped together under the common label of social 
capital. This has been seen to have gone up. 
Scholarly interest in the concept of social capital is motivated essentially by 
the relationship between the stock of social capital and its relation to effective 
political institutions, economic development, low crime rates, and reduced incidences 
of other social problems. Coleman (1998, 1990) and Putnam (1993) argues that social 
capital is significantly positive on household welfare, economic growth and 
development. It promotes trust and cooperation among agents which in turn increases 
socially efficient collective action (L a porta et al; 1997).  
Few studies that investigated the causes of social capital did not examine the 
influence of socio-economic variables on social capital index (Brehm and Ralm, 
1997: Alesina and Laferrara, 2000, Glaeser et al; 2000, Charles and Kline, 2002). 
They did not substantiate their claims empirically or investigate the factors associated 
with variation in social capital levels. These studies use an array of individual and 
community-level factors as determinants of social capital. Previous empirical 
 7 
 
investigations of the determinants of social capital are based on surveys using 
qualitative method for data analysis, discussion and results (Putnam, 1995, Brehm 
and Rahn, 1997, Alesina and La Ferrora, 2000; Glaeser et al; 2002). Moreover, 
general social surveys which measured trust, civic engagement and association of 
individual were ambiguous and their results were not clear enough to vividly reveal 
the policy implications.  
 
 
 8 
 
CHAPTER TWO 
2.0 THEORETICAL FRAMEWORK AND LITERATURE REVIEW 
2.1      Theoretical Framework  
Any conceptualization of social capital aims at simplifying the complexity of 
the social world to assist in the development of an understanding of the structures and 
processes that affect a variety of outcomes. In the past, many efforts to conceptualize 
social capital have resulted in over-simplification and therefore questionable 
operationalization. There are considerable unknowns surrounding the current 
understanding of social capital theory. Various relationships exist between 
determinants, structural elements and consequences or manifestations but interactions 
are largely unknown (Figure1). Anything that has an impact on social interactions can 
be seen as a determinant and any situation arising because of social interactions can 
be seen as a manifestation. We know some of the elements in between but have little 
understanding of the processes. This highlights the importance of establishing a 
rigorous conceptualization, as the appropriate operationalization of social capital must 
be based on a rigorous conceptualization. 
 
 
 
 
 
 
 
       
 
 
Figure (1) Complexity between the determinants and consequences of social 
capital. Adapted: (Claridge, 2004)      
The conceptualization designed for the purposes of this study details processes and 
relationships operating between the determinants of social capital, the structure, or 
elements of social capital, and the consequences or manifestations of social capital. It 
 9 
 
attempts to take into account factors such as causal relationships, specific contexts, 
externalities, levels, feedback loops and chance (Figure 2).  
The literature review has identified a wide range of determinants that have 
been linked to social capital including history and culture, social structures, family, 
education, environment, mobility, economics, social class, civil society, consumption, 
values, networks, associations, political society, institutions, policy, and social norms 
at various levels.  Clearly the factors listed here play an important role in determining 
the characteristics of the social capital structure however the causal factors and 
functional relationships are largely unknown. Some studies have focused on some of 
the factors in-so-much as detailing the social capital of the circumstance, for example, 
family, trust, or networks, but have not studied factors as determinants of multi level, 
multi dimensional social capital. 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 10 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure (2). Relationships between determinants, structure and consequences of capital. 
Adapted: (Claridge, 2004),  
 11 
 
Various aspects of social capital structure are identified in Figure (2). These 
could be referred to as elements, components, forms or factors. Although difficult to 
identify on paper, this conceptualization should be thought of as three dimensional 
with the various levels acting as the third dimension (for an example of the 
application to natural resource management  (Figure 3). Ties are a fundamental 
component of social capital that describes the nature of social relationships. This   
simply put, can be strong or weak. Hierarchical refers to the distribution of vertical 
and horizontal ties. Temporal features are identified as a component as time has a 
considerable impact on other components of social capital.  
There is significant change in the nature of social capital over time, 
particularly with depreciation, reinforcing of ties and other network features. Figure 
(3) hypothesizes the possible temporal change of different norms over time. Both the 
norms relate to trust and reciprocity. Norms of networks, associated with ties, are 
expected to decrease over time with decreased expected future returns. These norms 
should be separate from norms associated with membership or belonging which may 
or may not include a social tie. These norms are likely to increase over time as one 
develops reminiscence and therefore increased strength of norms of trust and 
reciprocity towards other members whether a network tie existed or not. This diagram 
is a generalization based on applied theory and does not attempt to illustrate the 
complexity of social processes as there are likely to be numerous factors affecting the 
strength of norms over time. 
 
 
 
 
 
 
 
 
Figure( 3); Depreciation of social capital over time without reinforcement while norms of 
membership and belongings are likely to increase over time.  Adapted: (Claridge, 2004),   
 
 12 
 
Membership accessibility (Figure 3) relates to whether there is group 
exclusion or inclusion.This strongly determines the nature of the externalities. The 
type refers to important distinctions made in the literature between structural and 
cognitive, and between bonding and bridging social capital. There are many aspects of 
network structure (the study of network theories) that are relevant to social capital 
structure. The concepts of network closure and structural holes play a significant role 
in the interaction of ties at the meso and macro levels. As such, spatial features 
interact to determine the nature and impact of social capital structure.  
It has been found in previous studies that geographic proximity has a role in 
the formation of norms of reciprocity and the strength of ties, particularly in relation 
to the sense of belonging and membership through the opportunity for face to face 
contact and reinforcement of norms, particularly information flows. Technology has 
rapidly changed the effect of space and time on social capital networks. Email is 
increasingly being utilized for communication, which offers cheap and fast 
connectivity that compresses the space-time continuum. More recently SMS (short 
message service) is increasing networks of mobility. Both of these technologies have 
different impact on social capital because of the lack of personal contact of face-to-
face interaction. The type of social capital that is produced from this interaction is 
significantly different from that found in traditional relations (Kavanaugh and 
Patterson 2001; Meredyth and Ewing 2003; Pruijt 2002; Sullivan et al. 2002; 
Wellman et al. 2001).  
Although there are benefits, this contributes to social isolation, particularly in 
urban centres of developed countries. Whereas in the past, social networks were 
commonly based on proximity, they are now based more on work and interest groups. 
The strength of networks based on proximity has decreased because people know few 
of their neighbours, particularly in medium to high density areas and where there is 
high residential mobility. The result is limited opportunity for repeated interaction, 
which is fundamental to the equilibrium concept for social capital generation. 
Alignment has received little attention in the literature but is significant for similar 
reasons to spatial features. Alignment refers to the interests, beliefs and views of 
individuals or groups. People may be aligned to groups or communities for various 
reasons, and this 'membership' results in a range of social capital manifestations.  
 13 
 
There is a dynamic relationship between all of the components described 
above with the other factors identified in Figure 2 under the social capital structure 
bubble. These factors include, specific context, level, externalities, chance and 
feedback loops. Just as the determinants are context specific, the consequences that 
result from the social capital structure strongly relate to circumstances that change 
rapidly over time. For example, only under certain circumstances can social capital be 
realized; one cannot cash in a favour anytime. Also, the social capital structure 
operating behind vastly different manifestations, such as collective action and 
organized crime in most of the developed world, are not necessarily different only the 
circumstances. The level at which social capital is located has pervaded much of the 
discussions on social capital conceptualization.  
This is because different components of social capital operate at different 
levels. Ties operate at the individual level by their very nature (Figure 2), but 
aggregates of ties, described by network theory, operate at the meso and macro levels. 
Meso level studies look at groups, but these groups are still made up of individuals, 
with ties to other individuals outside the group and to other groups through ties with 
individuals who are members of other groups and through multiple membership. The 
complexity of these meso level interactions cannot be effectively graphically 
represented. Another example is belonging (types) that exists within levels or scales 
as one feels belonging to family, community, profession, country simultaneously.  
Due to the transitory, impermanent nature of social capital, chance plays an 
important role. Chance meetings and chance events both play an important role in the 
structure of social capital but also in realizing the manifestations of social capital. For 
example, an individual might meet, by chance, a work colleague away from the 
workplace. This is likely to transform the weak tie from being associated with the 
same employer to a strong tie associated with belonging, mutual interest, and so on, 
and strong norms of reciprocity, thereby transforming the organizational social capital 
representing changes at both the micro and meso levels. Another chance event may 
prevent this potential from being realized, for example, if the colleague is away in a 
time of need. 
There is evidence to suggest that there is a series of feedback loops that 
operate within the dynamic relationships between the components of social capital. 
For example, a community network created to build social capital has initial benefits 
 14 
 
in terms of information flows, norms of reciprocity and trust, however, network 
closure results in norms that restrict behaviour with a high likelihood of negative 
externalities thereby self-regulating total benefit and potentially returning community 
networks to pre-project states through loss of membership. The role of determinants 
should be highlighted as there may be an underlying reason for propensity for 
network closure and negative ends such as history, geographic scale, religion, family 
and other social norms. This highlights the fact that an event can be a determinant of 
social capital; a breach of trust for example.  
In this way, the dynamic relationships of social capital structural elements 
become somewhat self regulatory, fundamentally based on the context specific 
determinants. This is what could have led Putnam (2001) to state that social capital's 
roots were buried in centuries of cultural evolution and therefore cannot be built in the 
short term. The existence of feedback loops is further supported by other authors (for 
example, Biox and Prosner 1998) who have posited social capital theories as an 
equilibrium concept, although as equilibrium in terms of expected returns. It would be 
more appropriate to think of social capital as equilibrium caused by limits and 
determinants, particularly in terms of beneficial manifestations. 
Figure 4 identifies the location of social capital at the micro level. It is 
important to identify that different outcomes of social capital are evident at different 
levels. At the micro level the main outcomes relate to norms of reciprocity and 
information flows. In the diagram (figure 4) it can be seen that neither individual 
'owns' the social capital that exists between them. At the meso level, it can be 
understood that an individual has a level of ownership or control of his or her social 
capital by choosing ties and membership and therefore sharing his or her social 
capital. Some authors refer to structure and quality of relationships as these factors are 
thought to be important in achieving various outcomes. Norms operate at various 
levels. Norms of reciprocity exist between the individuals, as do social norms that 
govern behaviour. These same norms operate at other levels simultaneously, both 
meso and macro. 
 
 15 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 4 Location of social capital at the individual level within the framework of 
micro level social capital interactions. Adapted: (Claridge,. 2004),   
From this discussion it can be seen that social capital involves complex 
interactions between its determinants, structure and manifestations. The structure of 
social capital is marked by dynamic relationships between its components with the 
roles of chance, feedback loops and externalities that determine the outcomes or 
manifestations largely unknown. These relationships are further complicated by the 
level of investigation. Components operate at different levels and there is considerable 
interaction between components operating at different levels simultaneously. This 
complexity highlights the inadequacy of the current conceptualization of social 
capital, particularly for application to measurement and building attempts.  
 
2.2 Social Cohesion and Solidarity 
Social Cohesion is one of the terms which are abundantly used without being 
questioned. Social Cohesion is defined as  a society‘s ability to secure the long term 
well being of all its members, including equitable access to available resources, 
respect for human dignity with due regard for diversity, personal and collective 
autonomy and responsible participation (Council of Europe, 2005) Social Cohesion is 
largely seen as the responsibility and ability of the state to secure an environment in 
 16 
 
which citizens can express themselves, can freely participate in society, enjoy 
assistance to keep them out of poverty and marginalisation and so on ( Council of 
Europe, 2006). 
 To measure social cohesion and inclusion, we use statistics like life 
expectancy figures, and infant mortality rates as indicators, for human well- being and 
poverty rates and social expenditure figures as indicators for access to available 
resources and social solidarity. Crime rates and subjective fear of crime are used as 
indicators to assess the violation of personal dignity and official statistics on voluntary 
organizations as indicators for participation.  
 
2.3 Social Capital and Trust   
The concept of Trust is highly important in conceptualising social capital.  
Simmel (1950) states that trust is ―one of the most important synthetic forces within 
the society‖. Luhmann (1988) connects the notion of trust to the taking of risks 
because of the complexity of contemporary societies, Levi (1988) defines trust as 
holding word for a variety of phenomena that enable individuals to take risks in 
dealing with others, solve collective action problems tract in ways that seem contrary 
to standard definition of self interest.  Hardin 2006 describes trust as the cognitive 
premise with which individual or collective or corporate actors enter into interaction 
with other actors, in this framework, trust is fostered by past experiences and the 
trust‘s reputation. It helps to create a vibrant and virtuous community, where people 
know their neighbours, join together in voluntary associations, give of themselves, 
and commit themselves to moral codes: 
―Virtuous citizens are helpful, respectful, and trustful toward one another, 
even when they differ on matters of substance‖ (Putnam, 1993). Trust matters because 
it is part, perhaps the most essential part, of social capital Putnam (1995a) Trust 
makes for a vibrant community in several ways. It promotes cooperation (Putnam, 
1993). It leads people to take active roles in their community, to behave morally, and 
to compromise. People who trust others aren‘t quite so ready to dismiss ideas they 
disagree with. When they can‘t get what they want, they are willing to listen to the 
other side. Communities with civic activism and moral behaviour, where people give 
others their due, are more prosperous. Trust can dramatically reduce what economists 
call transaction costs—costs of negotiation, enforcement, and the like—and makes 
 17 
 
possible certain efficient forms of economic organization that otherwise would be 
encumbered by extensive rules, contracts, litigation, and bureaucracy.  
Trust is particularised when we trust those who are most like ourselves or 
generalised when we take greater risks for a more general form of trust. Only the 
latter is a form of social capital because you can invest and hope to reap additional 
income from that initial down-payment. Particularised trust entails little risk, but 
won‘t make you--and the wider community--either prosperous or vibrant. Generalized 
trust flourishes in democracies, while particularized trust is more typical of 
authoritarian and totalitarian societies. Generalized trust makes people more willing to 
take part in their communities and to endorse moral commitments. Particularized trust 
makes people withdraw from civic life.  
In totalitarian societies it makes little sense to trust anyone but your family and 
your closest friends. In authoritarian societies, you might trust a somewhat larger 
circle. But only in democracies--and not even in all of them--will you give your trust 
to strangers. Trust works because, like Forster‘s democracy, it promotes variety and 
admits criticism. It makes adherents more comfortable with strangers and more 
willing to put their trust where they might otherwise not tread. Democracies are 
breeding grounds for generalized trust and social networks. Why? Levi (1996) and 
Muller and Seligson (1994) argue that living in a democracy makes you more trusting. 
And that seems right. But Inglehart (1988) maintains that a trusting political culture is 
more conducive to democracy. And that seems right too. We know that trusting 
people are more tolerant and acceptant of minority cultures (Uslaner, 1994). The 
relationship between democracy and social capital appears to be symbiotic. This 
seems like a chicken-and-egg problem that defies causal ordering. (Van Staveren 
2002).  
  
2.4 Dimensions of Social Capital 
Social capital theory suffers from much criticism for being poorly defined and 
conceptualised. This problem largely stems from the fact that social capital is multi 
dimensional with each dimension contributing to its meaning. However, each 
dimension alone is not able to capture fully the concept in its entirety (Hean et al;  
2003). The main dimensions as found in the literature are : Trust (Coleman, 1988; 
Collier, 1998; Cox, 1997; Kwachi et al; 1999, Kilpatrick, 2000; Leana and Van 
 18 
 
Buren, 1999; Lemmal, 2001; Putnam, 1993: Putnam et al; 1993, Snijders, 1999;Welsh 
and Pringe, 2001),  Rules and Norms governing social action (Coleman, 1998; 
Collier, 1998; Fukuryama, 2001; Pates and Sensenbrenner, 1993), Types of social 
interaction (Collier, 1998; Snider, 1999) and Network resources ABS 2002; 
(Kilpatrick 2000, Snider 1999).  In addition to this are other network characteristics or 
groups dimensions as highlighted by Burt, 1997; Hawa and Shielle, 2000; Kilpatrick, 
2000; Putman 1993, 2003. Liu and Besser (2003) identified four dimensions of social 
capital as informal social ties, formal social ties, trust and norms of collective action. 
 
2.5 Social Capital and Welfare. 
 Welfare generally refers to socio-economic well-being.  This is ―correlated 
with the basic level of economic development, of course, but focuses more 
specifically on a variety of goods and services believed to be essential for individual 
and social happiness and security (such as health care, housing, social insurance, other 
employment-related benefits, and additional forms of social assistance)‖ (Warnecke 
2008).  Together, the institutions and policies supporting these types of goods and 
services form a welfare-state regime.   
The welfare state defends and supports the development of social rights, 
aiming ―to make civil rights actually work…removing the barriers that blocked the 
full and equal exercise of civil and political rights‖ (Bussemaker and van Kersbergen 
1999).  Supporting the idea of a welfare state can indicate a willingness to think about 
prosperity and economic security as community goals (or even community 
responsibilities), not merely individual ones.  At the very least, it signifies an 
acceptance that individuals, even hard-working ones, cannot always make things work 
out well on their own—that they, too, might need help from the state in order to make 
ends meet, in order to cope with unforeseen circumstances. 
It is widely assumed among development practitioners that social capital plays an 
important role in reducing material deprivation (traditionally measured by income 
and consumption levels), vulnerability, powerlessness, and voicelessness. This 
assumption is often investigated by analyzing the effects of social capital on poverty 
reduction at the macro (national), meso (regional and community), and micro 
(household/individual) levels.  
 
 19 
 
2.6      Literature Review  
The notion of social capital is said to have first appeared in Lyda Judson 
Hanifan's discussions of rural school community centres ( Hanifan 1916, 1920). He 
used the term to describe 'those tangible substances that count for most in the daily 
lives of people'. Hanifan was particularly concerned with the cultivation of good will, 
fellowship, sympathy and social intercourse among those that 'make up a social unit'. 
It took some time for the term to come into widespread usage. Contributions from 
Jane Jacobs (1961) in relation to urban life and neighbourliness, Pierre Bourdieu 
(1983) with regard to social theory, and then James S. Coleman (1988) in his 
discussions of the social context of education moved the idea into academic debates. 
However, it was the work of Putnam (1993; 2000) that launched social capital as a 
popular focus for research and policy discussion.  'Social capital' has also been picked 
up by the World Bank as a useful organizing idea. They argue that 'increasing 
evidence shows that social cohesion is critical for societies to prosper economically 
and for development to be sustainable' (The World Bank 1999).  
One of the most striking developments in social service over the last decades 
is the rise of interest in socials as a mechanism for understanding socio-economic 
phenomena. Social capital has been treated as a key feature of phenomena ranging 
from the mortality crisis in Russia (Kennedy et al1998), to political participation 
Dispasquale et al(1999) to children‘s welfare Putnam(2000) to the development trap 
(Woolcock(2000) to judicial efficiency Laporta et al(1997) to the spread of secondary 
education. Social capital is an elusive concept, for the fact that its definition differs 
across studies. Potes(1998) developed a strong critique of the social capital literature 
because of this definitional ambiguity. Sociologists refer to friendship as ―Social 
Capital.‖   
To the academics, the term ―capital‖ is one that speaks to resources that can 
advance or promote a profit.  They talk about physical capital which refers to things 
like land or machinery.  Economic capital might refer to goods, or services that drive 
an economy.  ―Human capital‖ is often thought to be the people needed to do the 
work to create the goods or services. Social capital, however, pushes the concept 
beyond its economic roots and suggests the connectedness among and between 
people.  Research is now convincing that the more social capital people have in their 
lives, the better their lives become.  Putnam (1993) reports that the more social capital 
 20 
 
people have in their lives the healthier they are, the happier they are and the longer 
they live.  That is right – social capital, or friendship is linked to the 3 highest quality 
of life indicators known to humankind!  That being said, Bourdieu defines 'Social 
capital as the 'the aggregate of the actual or potential resources which are linked to 
possession of a durable network of more or less institutionalized relationships of 
mutual acquaintance and recognition' (Bourdieu 1983). 
According to Coleman, Social capital is defined by its function. It is not a 
single entity, but a variety of different entities, having two characteristics in common: 
they all consist of some aspect of a Social structure, and they facilitate certain actions 
of individuals who are within the structure' (Coleman 1994). Whereas physical capital 
refers to physical objects and human capital refers to the properties of individuals, 
Social capital refers to connections among individuals – capital networks and the 
norms of reciprocity and trustworthiness that arise from them. In that sense Social 
capital is closely related to what some have called ―civic virtue.‖ The difference is 
that ―Social capital‖ calls attention to the fact that civic virtue is most powerful when 
embedded in a sense network of reciprocal capital relations. A society of many 
virtuous but isolated individuals is not necessarily rich in Social capital (Putnam 
2000). 
 
The World Bank: ' Social capital refers to the institutions, relationships, and norms 
that shape the quality and quantity of a society's Social interactions... Social capital is 
not just the sum of the institutions which underpin a society – it is the glue that holds 
them together' (The World Bank 1999).  Fukuyama (1999) captures many of the 
intuitions that have driven this literature. According to him social capital is defined 
bas an instantiated set of informal values or norms shared among members of a group 
that permits them to cooperate with one another. And if members of the group come 
to expect that others will behave reliably and honestly, then they will come to trust 
one another, and trust acts like a lubricant that makes any group or organization run 
more efficiently.  
Bowles et al (2002) define social capital as trust, concern for one‘s associates, 
a willingness to live by the norms of one‘s community and to punish those who do 
not. Putnam (2000) refers social capital to connections among individual, social 
works and the norms of reciprocity and trust worthiness that arises from them.  
 21 
 
Bourdieu (1979, 1983), Coleman (1988; 1990; 1994) and Putnam (1993; 1995; 2000), 
in an attempt to define social capital described it as intrinsically relational, with 
attendant emotional and perceptual consequences, and as being open to useful 
exploration through the metaphor of capital.  
What is central to Bourdieu, Coleman and Putnam‘s attempts at definition is 
the clear location of social capital as belonging to and existing within the relational 
bonds of human society. This is its socialness, the ‗durable network of, relationships  
the ‗social structure‘  or ‗social networks‘ . Socialness is the medium in which social 
capital operates, strengthens or diminishes.. The metaphors may vary, but social 
capital can only exist within a pattern of relationships. Such relational structures may 
vary in duration, density, distance and interconnectedness, but social capital is 
intrinsic to the relational network. 
A second feature of social capital common to Bourdieu, Coleman and Putnam 
is that the relational behaviours have emotional and perceptual consequences. This is 
the oxygen of social capital, providing either a potentially rich environment for 
growth and change, or a limiting context. Through investment in certain forms of 
behaviour and their products, social capital is sustained and nourished. The 
‗unceasing effort of sociability‘ (Bourdieu, 1983), the ‗general level of 
trustworthiness‘ (Coleman, 1994), the operation of ‗norms, trust and reciprocity‘ 
(Putnam, 2000:), all speak to the domain of interpersonal conduct.  
A third defining feature of social capital shared by Bourdieu, Coleman and 
Putnam is expressed in the symbolism of capital as an economic metaphor. Social 
capital is a form of power, a currency, a resource: it can be can be utilised, traded, 
exchanged, drawn upon, invested, cashed in. Social capital is a form of energy, a 
force; it is a capacity, a facility that can be deployed and activated towards some 
desired goal. 
Social capital ‗may serve as currency‘ (Bourdieu, 1977), it can ‗facilitate 
certain actions‘ (Coleman, 1988), and it can be used to ‗pursue shared objectives‘ 
(Putnam, 1996): social capital is a purposeful means toward other ends.  
 22 
 
Baron, et al (2000) emphasise five elements which could have direct relevance 
as a method for creating institutions such as secondary schools that are socially and 
network rich. First, the notion of social capital shifts the focus of analysis from the  
individual to the patterns of relations which exist within an institution, and is capable 
of dealing with the complex ambiguities of cooperation and conflict that characterise 
such a community. Second, it offers a way of examining the links between micro-, 
meso- and macrolevels of analysis in an area that has struggled with the 
interrelationship between the individual, small groups and the large organisation in 
education. This becomes an issue where schools with declining roles are amalgamated 
to ensure a wide and balanced curriculum. Third, social capital could promote multi-
disciplinarity and inter-disciplinarity in organisations noted for insularity, within 
secondary subject disciplines for example. A Curriculum for Excellence (Scottish 
Executive, 2004b) is posited on cross-curricular themes and cross-institutional 
movement of staff and such a marked shift in working practice demands a new way of 
thinking about the social processes of both teaching and learning. Fourth, developing 
social capital as a concept within schools could reinsert issues of value into the heart 
of the discourse, with terms such as trust, networks, norms and reciprocity gaining 
both theoretical and practical emphasis. Lastly, there is social capital‘s heuristic 
ability to open up avenues for exploration of complex, multidimensional issues. By 
applying notions of social capital to institutions such as mainstream secondary 
schools, the features which both facilitate and inhibit the collaborative working 
promoted by much educational literature and policy could be re-examined with a view 
to improving the secondary experience for many children, particularly those who are 
marginalised.  
  Social capital does not have a clear, undisputed meaning, for substantive and 
ideological reasons (Dolfsma and Dannreuther 2003; Foley and Edwards 1997). For 
this reason there is no set and commonly agreed upon definition of social capital and 
the particular definition adopted by a study will depend on the discipline and level of 
investigation (Robison et al. 2002). Not surprisingly considering the different 
frameworks for looking at social capital there is considerable disagreement and even 
contradiction in the definitions of social capital (Adler and Kwon 2002).  
 23 
 
Because of the difficulties in defining social capital, authors tend to discuss 
the concept, its intellectual origin, its diversity of applications and some of its 
unresolved issues before adopting a school of thought and adding their own definition 
(Adam and Roncevic 2003). It has been suggested that a cross disciplinary definition 
would be less important if scholars were to redefine and appreciate other discipline's 
definitions (SCIG 2000). SCIG (2000) further identified that all studies must discuss 
social capital in relation to the particular discipline, study level and context and that a 
set definition for such is not required, only an identification of operationalization or 
conceptualization (SCIG 2000).   
Other authors have identified that definitions vary depending on whether they 
focus on the substance, the sources, or the effects of social capital (Adler and Kwon 
2002; Field et al. 2000; Robison et al. 2002). Grootaert and Van Bastelaer (2002b) 
supported this view identifying that the main cause of variance in definitions is 
caused by focusing on the form, source or consequence of social capital. Social 
capital is multidimensional and must be conceptualized as such to have any 
explanatory value (Eastis 1998). Some authors see social capital as an economic term 
and do not adequately take account of its multi - dimensional and multi - disciplinary 
nature, for example Day (2002).  
Social capital is about the value of social networks, bonding similar people 
and bridging between diverse people, with norms of reciprocity (Dekker and Uslaner 
2001; Uslaner 2001). Sander (2002) states that 'the folk wisdom that more people get 
their jobs from whom they know, rather than what they know, turns out to be true'. 
Adler and Kwon (2002) identifies that the core intuition guiding social capital 
research is that the goodwill that others have toward us is a valuable resource. As 
such they define social capital as 'the goodwill available to individuals or groups. Its 
source lies in the structure and content of the actor's social relations.  
Its effects flow from the information, influence, and solidarity it makes 
available to the actor' (Adler and Kwon 2002). Dekker and Uslaner (2001) posit that 
social capital is fundamentally about how people interact with each other. There is 
now a range of evidence that communities with a good 'stock' of such ' Social capital' 
are more likely to benefit from lower crime figures, better health, higher educational 
achievement, and better economic growth (Halpern 2009b). However, there can also 
be a significant downside. Groups and organizations with high Social capital have the 
 24 
 
means (and sometimes the motive) to work to exclude and subordinate 
others. Furthermore, the experience of living in close knit communities can be 
stultifying - especially to those who feel they are 'different' in some important way.  
 With respect to social networks, a number of researchers have found that 
women often depend more on informal relations and so form stronger kinship and 
friendship relations than men, who tend to rely more on formal relationship (Agrawal, 
2000; Molyneux, 2002; More, 1990; Ridell et al, 2001). Molinas (1998) finds that 
successful collective action is dependent on the degree of women‘s participation. This 
is consistent with the argument that women exhibit more cooperative behaviour than 
men due to greater interdependence and altruism (Folbre, 1994; Sharma, 1980; White, 
1992). However, Jackson (1993) emphasizes that the assumption of women‘s greater 
altruism is evidence of a common failure to scrutinize the private interest of women 
adequately. Women cannot be seen as a uniform category but a diverse group of 
people who vary according to class and culture. They also vary according to resource 
endowments and decision-making power both between and within households. 
Gender relations have been identified as important determinants of the capacity for 
collective action for household welfare (Grooteart, 2007).  
In a system where women are confined to their homes, not much community level 
social capital is expected to be built. The better a society treats its women, the greater 
the social harmony and the higher their economic productivity (Picciotto, 1998).  
Development programs are often criticized for failing to account for gender 
inequalities in decision-making, task allocation, resource ownership and management, 
which has implications for policy recommendations (Quisumbing 2003). Gender 
inequalities almost always favour men, with women often being disadvantaged both 
in the control over household assets (Fafchamps and Quisumbing 2003) and in the 
division of responsibilities in the household/ community. Even when a woman heads 
the household and is in charge of household resources, gender differences emerge 
across female-headed households and their male-headed counterparts. Significant 
heterogeneity among female-headed households has also been highlighted in the 
literature implying differential provision of resources and their use in rural settings 
(Peters 1983). Women and men also have different resource endowments when 
pursuing livelihood strategies, which could have far-reaching consequences on social 
capital formation and information exchange. To build and maintain a social network 
 25 
 
is costly in terms of both time and other resources (Dasgupta 2005), imposing a 
barrier to social capital accumulation (Ioannides and Loury 2004).  
Women typically have a high opportunity cost of time that reduces their 
incentives to participate in certain social networks (Meinzen-Dick and Zwarteveen 
2003). Women have been found to join groups that mobilize fewer resources than 
men because they are resource-constrained (Maluccio et al 2003). Gender norms in 
the community may also exclude women from social capital enhancing activities, 
such as drinking clubs. Meinzen-Dick and Zwarteveen (2003) demonstrate how 
barriers faced by women in their participation in water management user groups in 
South Asia may stimulate use of alternative forms of social capital such as a network 
of friends and relatives.   
 Different social networks may provide different or unequal services to their 
members that could exacerbate women‘s disadvantages in development. If women 
and men have different types and qualities of social capital, they may participate 
differently in information exchange. Men may be inclined to acquire and provide 
more information to their social network (i.e. pooling of information) than women. 
Women are often more dependent on informal networks based on everyday forms of 
collaboration, such as collecting water, fetching fuel wood and rearing children. These 
services, together with the fact that women have a high opportunity cost of time, may 
motivate women to form networks with  individuals who are geographically close to 
reduce the length of time required to travel for social interaction. In contrast, men may 
be engaged in more geographically dispersed social networks, such as community 
projects, and may participate more in civic engagement and such participation 
provides them with greater access to information and stimulates information exchange 
with others (Maluccio et al. 2003). 
Research documenting the role of social capital on information flows in 
developing economies has been growing. Limited attention has been given to gender 
aspects that may influence both social learning processes and accumulation of social 
capital. Emerging empirical evidence provides support for the role of gender in 
information exchange through different, gender-related stocks of information and 
usage of social capital (Maluccio et al. 2003). In many rural areas, where small-scale 
agriculture takes place, gender differences have been found to have a significant 
impact on resource allocation and productivity in agriculture (Alderman et al. 2003). 
 26 
 
 
2.7 Forms of Social Capital 
               Attempts to more thoroughly conceptualize social capital have resulted in 
many authors identifying different types and characteristics, the most common being 
the distinction of structural and cognitive, and bonding and bridging. Although not 
always called the same thing, the distinction between bridging and bonding (and often 
linking as well) is common in the literature. Aldridge, Halpern et al (2002) identify 
these main types of social capital. Bonding is horizontal, among equals within a 
community whereas bridging is vertical between communities (Dolfsma and 
Dannreuther 2003; Narayan 2002; Narayan and Pritchett 1999). Wallis (1998) and 
Wallis and Crocker et al (1998) refer to bonding capital as localized which they 
define as being found among people who live in the same or adjacent communities, 
and bridging capital, which extends to individuals and organizations that are more 
removed. Bridging social capital is closely related to thin trust, as opposed to the 
bonding (splitting) social capital of thick trust (Anheier and Kendal 2002).  
               The other important distinction of social capital, developed by Norman 
Uphoff and Wijayaratna (2000) spans the range from structural manifestations of 
social capital to cognitive ones (Grootaert and Van Bastelaer 2002a). Structural social 
capital facilitates mutually beneficial collective action through established roles and 
social networks supplemented by rules, procedures and precedents (Hitt et al. 2002). 
Cognitive social capital, which includes shared norms, values, attitudes, and beliefs, 
predisposes people towards mutually beneficial collective action (Krishna and Uphoff 
2002; Uphoff 1999). Cognitive and structural forms of social capital are commonly 
connected and mutually reinforcing (Uphoff and Wijayaratna 2000).   
              Michael Woolcock, has helpfully argued that many of the key contributions 
prior to Bowling Alone have failed to make a proper distinction between different 
types of Social capital. He distinguished between: Bonding Social capital which 
denotes ties between people in similar situations, such as immediate family, close 
friends and neighbours. Bridging Social capital, which encompasses more distant ties 
of like persons, such as loose friendships and workmates. Linking Social capital, 
which reaches out to unlike people in dissimilar situations, such as those who are 
entirely outside of the community, thus enabling members to leverage a far wider 
range of resources than are available in the community. (Woolcock 2001)  
 27 
 
                   There are numerous other examples in the literature; for example, whether 
its ties are strong (intensive and repeated) or weak (temporary and contingent); 
vertical (operating through formal hierarchical structures) or horizontal (in which 
authority is more decentralized); open (civically engaged and exercising open 
membership) or closed (protective and exercising closed membership); geographically 
dispersed or circumscribed; and instrumental (membership as social collateral for 
individual wants) or principled (membership as bounded solidarity) (Heffron 2000). 
These varieties of types of social capital require further exploration to establish a 
widely agreed upon framework, vital for empirical analysis (Van Deth 2003).  
  2.8 Importance of Social Capital 
The importance of social capital theory is apparent from the literature with 
many empirical studies that purport to show the importance of social capital to a very 
wide-ranging set of socioeconomic phenomena (Durlauf 2002a; Krishna 2001). Adam 
and Roncevic (2003) state that:  
'despite problems with its definition as well as its operationalization, and despite its 
(almost) metaphorical character, social capital has facilitated a series of very 
important empirical investigations and theoretical debates which have stimulated 
reconsideration of the significance of human relations, of networks, of organizational 
forms for the quality of life and of developmental performance'.  Existing studies have 
provided ample evidence of its pervasiveness and offered useful impressions of its 
political, economic and social influence (Fine 2001; Jack and Jordan (1999).  
Montgomery (2000) suggests that the importance of social capital lies in that it 
brings together several important sociological concepts such as social support, 
integration and social cohesion. This view is supported by Rothstein (2003) who 
states that the real strength of social capital theory is the combination of macro-
sociological historical structures with micro-level causal mechanisms, a rare feature in 
the social sciences. The literature recognizes social capital as important to the 
efficient functioning of modern economies, and stable liberal democracy (Fukuyama 
2001; Kenworthy 1997), as an important base for cooperation across sector and power 
differences, and an important product of such cooperation (Brown and Ashman 1996), 
and Lyon (2000) described the importance of social capital in shaping regional 
development patterns.  
 28 
 
It is clear that social capital is of importance in societal well-being. Some 
aspects of the concept, such as inter-personal trust, are clearly desirable in themselves 
while other aspects are more instrumental (Bankston and Zhou 2002). Optimism, 
satisfaction with life, perceptions of government institutions and political involvement 
all stem from the fundamental dimensions of social capital (Narayan and Cassidy 
2001). Social capital is charged with a range of potential beneficial effects including: 
facilitation of higher levels of, and growth in, gross domestic product (GDP); 
facilitation of more efficient functioning of labour markets; lower levels of crime; and 
improvements in the effectiveness of institutions of government (Aldridge et al. 2002; 
Halpern 2001; Kawachi et al. 1999b; Putnam et al. 1993).  
Social capital is an important variable in educational attainment (Aldridge et 
al. 2002; Israel et al. 2001), public health (Coulthard et al. 2001; Subramanian et al. 
2003), community governance, and economic problems (Bowles and Gintis 2002), 
and is also an important element in production (Day 2002). Economic and business 
performance at both the national and sub-national level is also affected by social 
capital (Aldridge et al. 2002). Others have emphasized the importance of social 
capital for problem solving and how only certain types of social capital contribute to 
this (Boyte, 1995; Sirianni & Friedland, 1997).In addition, social capital has the 
following significance: 
It allows citizens to resolve collective problems more easily… People often might be 
better off if they cooperate, with each doing her share. ... 
Social capital greases the wheels that allow communities to advance 
smoothly. Where people are trusting and trustworthy, and where they are subject to 
repeated interactions with fellow citizens, everyday business and social transactions 
are less costly 
It improves people‘s lot by widening their awareness of the many ways in which their 
fate are linked. When people lack connection to others, they are unable to test the 
veracity of their own views, whether in the give or take of casual conversation or in 
more formal deliberation. Without such an opportunity, people are more likely to be 
swayed by their worse impulses. 
 The networks that constitute Social capital also serve as conduits for the flow 
of helpful information that facilitates achieving people‘ goals…. Social capital 
also operates through psychological and biological processes to improve 
 29 
 
individual‘s lives.  … Community connectedness is not just about warm fuzzy 
tales of civic triumph. In measurable and well-documented ways, Social 
capital makes an enormous difference to human lives, Putnam (2000). Child 
development is powerfully shaped by social capital. Trust, networks, and 
norms of reciprocity within a child‘s family, school, peer group, and larger 
community have far reaching effects on their opportunities and choices, 
educational achievement, and hence on their behaviour and development. 
 In high social-capital areas public spaces are cleaner, people are friendlier, and 
the streets are safer. Traditional neighbourhood ―risk factors‖ such as high 
poverty and residential mobility are not as significant as most people assume. 
Places have higher crime rates in large part because people don‘t participate in 
community organizations, don‘t supervise younger people, and aren‘t linked 
through networks of friends .Those communities with 'collective efficacy' - the 
confidence to intervene born of higher rates of social capital - are 
characterized by lower crime rates Sampson et.al(2005). 
 A growing body of research suggests that where trust and social networks 
flourish, individuals, firms, neighbourhoods, and even nations prosper 
economically. Social capital can help to mitigate the insidious effects of 
socioeconomic disadvantage. The growing presence of non-profit 
organizations in some areas as one aspect of this (Sampson et. al. 2005). 
Another is the quality of the networks in the 'underground economy of the 
urban poor' (Venkatesh 2006), Smith (2000, 2001, 2007, 2009). 
 There appears to be a strong relationship between the possession of social 
capital and better health. Regular club attendance, volunteering, entertaining, 
or church attendance is the happiness equivalent of getting a college degree or 
more than doubling your income. Civic connections rival marriage and 
affluence as predictors of life happiness, Wilkinson and Pickett (2009) Haidt 
(2006), Offer (2006). 
The World Bank (1999) has also brought together a range of statistics to make the 
case for the social and economic benefits of social capital. For example they argue 
that there is evidence that schools are more effective when parents and local citizens 
are actively involved. 'Teachers are more committed, students achieve higher test 
 30 
 
scores, and better use is made of school facilities in those communities where parents 
and citizens take an active interest in children‘s educational well-being'.   
 
2.9 Channels of Social Capital  
Any form of social capital, material or non-material represents an asset or a 
class of asset that produces a stream of benefits. The stream of benefits from social 
capital or the channels through which it affects development includes several related 
elements, such as information sharing, collective action and decision- making as well 
as reduction of opportunistic behaviour. Participation by individuals in social 
networks increases the availability of information and lower its cost. The information, 
especially if it relates to such things as crop prices, location of new markets, sources 
of credit, or how to deal with livestock disease, can play a critical role in increasing 
the returns from agriculture and trading.  
Participation in local networks and attitudes of mutual trust makes it easier for 
any group to reach collective decision and implement collective action. Social capital 
is seen in the contest of its contributions it makes to sustain development. Sustainable 
development refers to a process whereby future generations receive as much or more 
capital per capita as the current generation has available (Serageldin, 1996). 
Traditionally, this include natural capital, physical or produced capital and human 
capital the wealth of nations on which economic development and growth are based.. 
It is now recognized that these three types of capital determine only partially the 
process of economic growth because they overlook the way in which the economic 
actors interact and organize themselves to generate growth and development. The 
missing link is social capital (Grootaert 1997). 
2.10 Attributes of Social Capital 
At this broad level conceptualisation, there is little disagreement about the 
relevance of social capital and some academicians have questioned the use of the 
word capital to capture the essence of social interactions and attitudes. Indeed, social 
capital exhibits a number of characteristics that distinguish it from other types of 
capital.  
1. Unlike physical capital, but like human capital, social capital can accumulate 
as a result of its use, so, social capital is both an input into and output of 
collective actions. 
 31 
 
2. Although, every form of capital has a potential productive impact in a typical 
Robbinson Crusore economy. Social capital does not, creating and activating 
social capital requires at least two people i.e it has public good characteristics 
that have direct implications for the optimality of its production level. 
3. It is not costless to produce as it requires an investment, at least in terms of 
time and efforts if not always money that can be significant. Putnam (2003) 
shows in his analysis of civic associations in Italy that embodied social capital 
can take generations to build and to come fully effective. And as many of 
examples of civil conflict around the world can testify, trust is more easily 
destroyed than built. Thus, there is a distinct maintenance expense to social 
capital, usually in the form of time. 
The key attribute of social capital is that it is an accumulated stock from which a 
stream of benefits flows. On the input side, the additional dimension lies in the 
investment required to create a lasting asset; on the output side, it lies in the resulting 
ability to generate a stream of benefits. Social capital can directly enhance output and 
lead to higher productivity of other resources, such as human and physical capital.            
   
2.11 Production of social capital  
Mainstream economists have criticized the concept of social capital because it 
lacks a conceptual or analytical framework (Sobel, 2002). Social capital is usually 
considered to be a community-level attribute. Given their presumption that behaviour 
is based upon individual choice, economists are reluctant to accept this 
characterization, especially when the focus is on the causes or sources of social 
capital. While some behaviour of individuals may be forced upon them by the 
community, to economists it is reasonable to characterize social capital as a collective 
manifestation of behaviours, attitudes, and values of individual members of a 
community. Becker‘s (1965, 1974) work on household allocation of time and theory 
of social interactions provides a theoretical basis for economic analysis of the 
formation of social capital.  
The following formulation is a theory of individual decision-making in which 
the production of social capital reflects a conscious decision to invest in building 
social relations that have a direct implication for the level of individual utility. As 
such, we provide a means to embed social capital theory within the broad traditions of 
 32 
 
economic analysis. Although some aspects of individual behaviour may be imposed 
by the community, it is possible to characterize a large portion of social capital as a 
collective manifestation of individual behaviours, attitudes, and values of individual 
members of a community. Individuals choose how much social capital to produce and 
their choice depends upon both the opportunity cost of allocating time and resources 
to the production of social capital and the marginal benefits associated with additional 
units of social capital. 
This framework has been used in various studies of allocation of time among 
market and non-market economic activities, including the economics of religious 
participation (Azzi and Ehrenberg, 1975). Since individuals‘ participation in 
associational activities and other social and political activities requires the allocation 
of time and other resources, it is logical to use this framework in the present context.  
We employ this framework in this paper as a basis for analyzing variations in social 
capital activities such as associational densities, voting in elections, and participation 
in the decennial census. We assume without loss of generality that the population size 
of the observational unit considered here, the county, is normalized to one.  
The representative household of county i is assumed to have the following 
quasi-concave utility function: 
Ui ≡ U (Ci, SKi) where i = 1, . . . , n-------------------------------------------------- (1) 
where Ci is composite consumption and SKi denotes social capital. Becker (1965) 
argues that households utilize time and market goods to produce more basic goods 
that enter their utility function. Each argument in the utility function in Eq. (1) can be 
represented as a household production function that determines how much of these 
commodities can be produced using market and non-market goods (x), quantities of a 
household‘s own time (t), and characteristics of one‘s own (E) as well as other 
households (R) (Becker, 1965, 1974). 
This formulation assumes that households are both producers and utility maximizing 
consumers. The production functions are assumed to be concave and continuously 
differentiable. To simplify, we assume that composite consumption is of the form: 
C = C(xC, tC) = fC -------------------------------------------------------------------------(2) 
where xC denotes market goods and tC denotes allocation of time by household i for 
production of C. The time allocated to produce composite consumption and social 
capital is different from the time that is allocated to work (to earn wages). The 
 33 
 
implicit assumption here is that time allocated to household production (producing 
composite consumption and social capital) also has an opportunity cost: time not 
spent producing these goods could have be used in other productive activities. The 
production of social capital is a function of the household‘s personal social capital 
goods (xS), the household‘s allocation of time to producing this particular good (tS), 
the household‘s own characteristics (Ei), and the characteristics of other households 
(Rj) in the community. Personal social capital goods in our case may include non-
market activities, such as, membership in associations, voting in elections, and 
participation in the decennial census. The time variable indicates that participation in 
these various personal social capital activities requires time. Production of social 
capital goods also depends on personal characteristics of households and 
characteristics of the communities in which they live. We abstract from the possibility 
that participation in personal social capital goods may also require market goods such 
as food and transportation. 
SK = SK(xS, tS,Ei,Rj) = fS, and i _= j.---------------------------------------------- (3) 
The usual utility maximization problem may be written as 
U = U(Ci, Si) = U(fC, fS) = U(C(xC, tC), SK(xS, tS,Ei,Rj)),-------------------- (4) 
subject to a budget constraint. Let px be the price of market good (xC), pS the price of 
non-market social capital goods and wi the household‘s wage rate. The prices of 
social capital goods may entail expenses such as membership association fees and 
charitable contributions. These prices also depend upon the type and nature of 
associations. For example, participation in community based voluntary associations 
likely is less costly than participation in rent-seeking associations such as business, 
professional, and political organizations. Wage income is assumed to be the only 
source of income available to the household, which faces a budget constraint 
pxxC + pSxS = witl,--------------------------------------------------------------------------- (5) 
where tl is household‘s hours of work. Ignoring leisure as a use of time, the time 
constraint for the household is 
T = tC + tS + tl, and tC, tS, tl ≥ 0 for all t, ------------------------------------------------- (6) 
where T denotes total time available per period. The household‘s utility maximization 
problem can then be re-written as 
L = U(C(xC, tC), SK(xS, tS,Ei,Rj)) + λ[wi(T − tC − tS) − (pxxC + pSxS)] ------------(7) 
 34 
 
It follows from the first-order conditions (FOC) that the two choice variables, xC and 
xS, are ―separable‖ in the sense that one can be solved independently of the other. 
This separability of the xC and xS choices allows us to focus on the production of 
social capital goods. The FOC for production of social capital goods is: 
(U_SK_ (·) 
λ = pS ------------------------------------------------------------------------------------------- (8) 
The household chooses an optimal level of social capital (x∗s ) to maximize total 
utility. Although the FOC in Eq. (8) assumes an interior solution, it is possible that 
x∗s = 0. The condition that x∗s is strictly positive may be characterized by the 
inequality that net marginal utility of the social capital good exceeds its marginal 
opportunity cost: 
(U_S_(·) 
λ − pS > 0-------------------------------------------------------------------------------------- (9) 
Eq. (9) provides the basis for our empirical analysis. The FOC for individual social 
capital goods provide the stipulation that the household participates in associational 
activities if the perceive marginal utility from these activities minus the opportunity 
cost is positive. This may be expressed as 
Y∗ = 
(U_S_(·) 
λ − pS > 0------------------------------------------------------------------------------------- (10) 
The observable elements in this expression are the household‘s wage rate and, 
as is usually the case in empirical work, additional exogenous variables such as socio-
economic, demographic, and community attributes, which condition the household‘s 
participation. These factors are incorporated into a model of county-level social 
capital activities in the US. They are captured in the vector of explanatory variables, 
X, and expressed in the regression relationship 
Y∗i = βxi + μi, -------------------------------------------------------------------------------- (11) 
where μ is an error term.  
 
2.12 Determinants of Social capital 
The determinants are numerous and varied and there is both a lack of 
consensus and a lack of evidence to support the propositions. Several influential 
studies have suggested that Social capital capital's roots are buried in centuries of 
 35 
 
cultural evolution (Fukuyama 1995; Putnam et al. 1993).  Other investigators suggest 
that Social capital can be created in the short term to support political and economic 
development (Brown and Ashman 1996; Fox 1994; Tendler and Freedheim 1994). 
Aldridge, Halpern et al (2002) suggest that the main determinants of Social capital 
include: history and culture; whether Social structures are flat or hierarchical; the 
family; education; the built environment; residential mobility; economic inequalities 
and Social class; the strength and characteristics of civil society; and patterns of 
individual consumption and personal values.  
Pantoja (1999) identifies a different set again, including: family and kinship 
connections; wider Social networks of associational life covers the full range of 
formal and informal horizontal arrangements; networks; political society; institutional 
and policy framework which includes the formal rules and norms that regulate public 
life; and Social norms and values. The majority of these claims originate in applied 
theory and stem from much work done on other concepts such as network analysis, 
civic society, cultural studies, education, psychology, and many others. Even where 
empirical research has been performed, the findings have questionable validity. 
 
2.13 Measuring social capital 
  Another shortcoming of the social capital concept has been the lack of 
consensus on how it can be measured, largely due to the complexity of the concept. 
Researchers have used counts of associations or associational memberships, on the 
one hand, and survey data on levels of trust and civic engagement, on the other. 
Researchers have also drawn on a number of data sources, including the National 
Opinion Research Council‘s General Social Survey and the University of Michigan‘s 
World Values Survey. These surveys ask questions about individuals‘ associational 
membership, attitudes about trust, and political participation. Glaeser et al. (2000) 
raise questions about the reliability of survey data measuring social capital. In a 
laboratory setting they found that subjects who reported that they are trusting did not 
cooperate in a standard trust game.  
A general criticism of survey methods is that survey responses vary according 
to the manner in which questions are phrased, and who is asking them. Among other 
measures, researchers have also used crime rates, voter turnout, volunteering, car-
pooling and charitable-giving as measures of social capital. These measures have been 
 36 
 
used with varying degrees of success, but we contend that a single measure that 
captures completely a concept with complex and multiple dimensions, such as social 
capital, may not exist. We are not aware of any other study that attempts to identify at 
the county-level the determinants of social capital production in as comprehensive a 
manner as we have done here. Our approach to dealing with measurement issue 
follows from the argument that one form of social capital manifests itself in 
individuals through their participation in associational activities. Researchers have 
argued that social capital is enhanced when people belong to voluntary groups and 
organizations.  
In particular, Putnam (1993) maintains that participation in political and social 
activities and collective organizations is the primary means of civic engagement, and 
credits the economic success of northern Italy, relative to that of southern Italy, to it‘s 
the latter‘s rich organizational participation. He claims that individuals‘ participation 
in social and political organizations ―instill(s) in their members habits of economic 
cooperation, solidarity, and public spiritedness‖ (Putnam, 1993). From an economist‘s 
point of view, cooperation and information sharing are facilitated when individuals 
have the opportunity to interact within organizations. Such activities facilitate 
information-sharing through repeated interactions and these interactions promote 
reciprocity. People who belong to such groups tend to trust others who belong to the 
same group, and they are therefore more likely to cooperate.  
Activities and strengths of civic organizations can be measured by their 
membership numbers, the number of organizations per capita, or the frequency of 
meetings. We argue that differences in these numbers provide one of the best 
indicators of cross-sectional differences in social capital. We use primary data 
covering the entire study area in Osun and Ondo states  to compile an extensive and 
comprehensive set of variables representing membership organizations at the 
household to community level. Associations such as civic groups, religious 
organizations, sports clubs, labour unions, political and business organizations 
directly enable community interaction. 
Our measure of principal interest is the number of the following 
establishments in each county: (a) civic organizations; (b) bowling centers; (c) golf 
clubs; (d) fitness centers; (e) sports organizations; (f) religious organizations; (g) 
political organizations; (h) labor organizations; (i) business organizations; and (j) 
 37 
 
professional organizations. Alesina and La Ferrara (2000).  We also differentiate 
among associations following Knack and Keefer (1997), by dividing the above 
organizations into ―Olson-type‖ (O-Groups) and ―Putnam-type‖ groups (P-Groups): 
groups (a–f) are ―P-Groups‖ that are not rent-seeking, but which involve social 
interaction that promotes trust and cooperation. Groups (g–j) are ―O-Groups,‖ or rent-
seeking organizations. Knack and Keefer (1997) argue that in the case of rent-seeking 
activity there is a financial incentive to form and join associations because they are a 
mechanism for transferring income or wealth from other parts of society to members. 
For example, farmers join various cooperative societies and farmers groups such as 
All Farmers Association of Nigeria AFAN because they are instrumental in 
persuading the government to provide farm program payments. For P-groups the 
potentially higher level of return from membership may lead to individuals to be 
willing to invest additional time and perhaps other resources such as dues, 
contributions, or labour. Clearly such outlays can be seen as a form of investment in 
the expectation that future levels of utility will be higher than might otherwise be the 
case. 
2.14 Social Capital and Asset Accumulation 
An asset is generally defined as ‗a stock of financial, human, natural or social 
resources that can be acquired, developed, improved and transferred across 
generations. It generates flows of consumption, as well as additional stock‘ (Ford 
2004). In the current poverty–related development debates, the concept of assets or 
capital endowments includes both tangible and intangible assets, with capital assets of 
the poor commonly identified as natural, physical, social, financial and human capital.  
Physical capital (also known as produced or man-made capital) comprises the stock of 
plant, equipment, infrastructure and other productive resources owned by individuals, 
the business sector or the country itself.  
Financial capital: The financial resources available to people (savings, 
supplies of credit). Human capital includes investments in education, health, and the 
nutrition of individuals. Labour is a critical asset linked to investments in human 
capital; health status determines people‘s capacity to work, and skill and education 
determine the returns from their labour. 
Social capital, an intangible asset, is defined as the rules, norms, obligations, 
reciprocity, and trust embedded in social relations, social structures, and societies‘ 
 38 
 
institutional arrangements, which enable its members to achieve their individual and 
community objectives. Social capital is embedded in social institutions at the micro-
institutional level-communities and households-as well as referring to the rules and 
regulations governing formalised institutions in the market- place, the political 
system, and civil society. 
Natural capital includes the stocks of environmentally provided assets such as 
soil, atmosphere, forests, minerals, water and wetlands. In rural communities land is a 
critical productive asset for the poor; while in urban areas land for shelter is also a 
critical productive asset (Bebbington 1999; Carney, 1998; Moser 1998; Narayan 
1997; Portes 1998; Putnam 1993).    
Social capital has assisted households to accumulate the physical capital 
associated with building their house, acquiring land titles and in-filling their plots 
with earth.  Moser (2005) reports that Spaniards over time incrementally up-graded  
their house, replacing bamboo walls with cement blocks and earth or wooden floors 
with cement to consolidate the value of their asset. She shows that from 1978 to 1992 
housing grew the fastest of all assets, saying this is the first critical asset households 
seek to accumulate. However, she shows that the rates were in reverse order from 
1992 to 2004. According to her, once housing is established, parents made tradeoffs 
between their own consumption and their children‘s human capital, in terms of 
investing in their education as a longer term strategy for poverty reduction.  
Livelihood: A livelihood comprises the capabilities, assets and activities required for a 
means of living. A livelihood is identified as sustainable when it can cope with and 
recover from stresses and shocks and maintain or enhance capabilities and assets both 
now and in the future, while not undermining the natural resource base‘ (Carney 
1998, 1; DFID 2000).   
Social Protection: This has been very broadly defined as ‗longer-term policies that 
aim to protect and promote economic and social security or well-being of the poor. 
Social protection policies are designed to confer benefits at both the household and 
societal level that provide a buffer against short term shocks, and also enhance the 
capacity of households to accumulate assets and improve their well-being so that they 
are better protected in times of hardship‘ (Cook, Kabeer and Suwannarat, 2005). A 
narrower interpretation by the World Bank‘s Social Risk Management framework 
consists of public interventions ‗to assist individuals, households and communities in 
 39 
 
better managing income risks‘ (Holtzmann and  Jorgensen 1999) by ‗preventing, 
mitigating and coping with risks and shocks (World Bank 2000). Interventions 
include a range from ‗public, private and voluntary organizations and informal 
networks to support communities, households and individuals in their efforts to 
prevent, manage and overcome risks and vulnerabilities‘ (Barrientos and DeJong 
2004).  
2.15 Social Capital and Community participation. 
Social Capital has contributed immensely to the theories exploring the realities and 
experiences of family and work life Bookman (2004). While expressing the need to 
appreciate what constitutes community participation, especially the role of women, 
she draws attention to the informal connections formed to help with family care - and 
which do not register with many social capital commentators.  
New forms of "social capital" - just as important as money in the bank - are 
developing among working families in both urban and suburban environments. These 
new relationships are binding people together and reshaping communities in a literal 
and social sense. (Bookman 2004). 
Bookman charts the ways in which working families reach out to each other and to 
community-based programmes to address the issues they face - especially around 
caring for children and relatives. In addition she draws attention to the impact of what 
she describes as the 'stalled gender revolution' - and the extent to which women are 
still expected to shoulder disproportionate responsibilities for care, community 
engagement and domestic functioning. 
 
  2.16 Gender Dimensions and Social Capital. 
   The growing feminist literature on the social capital debate has shared the 
criticism of the naïve equation of social networks as promoting growth as well as 
reducing poverty and vulnerability Portes and Landolt (2000). Various authors have 
highlighted a gender dimension in the exclusion from social networks. Babar (2006) 
finds that women tend to outnumber men in organisations formed around community-
based disaster management; the situation is reversed in more formalised emergency 
planning. There, women are not only excluded from decision-making bodies, but also 
from the text of any significant decisions regarding disaster response (Babar, 2006). 
Agrawal (2000) while investigating gender dimensions of social networks in natural 
 40 
 
resources management, reports similar results. Even where rules for Community 
Forestry Groups (CFGs) are not restricting women‘s entry, especially gender norms 
and gender-differentiated access to resources becomes an effective barrier to women‘s 
participation. She highlights the implications on distributional equity, amongst others. 
Whereas, for example, cash benefits from CFGs are commonly accessed by the 
predominantly male group members who represent their households, they are seldom 
shared equitably within the family. On the other hand, since the main responsibility 
for firewood and fodder collection, animal care, cooking etc. falls on women, they 
also shoulder the burden of finding alternative resources when access to the forest is 
limited. Mayoux (2001) therefore warns that although households may be important 
sources of social capital, there is also a need to address the norms which regulate 
relations within them.  
Babar (2006) also narrates the experience of the El Niño in a Peruvian fishing 
village. The warnings regarding the upcoming El Niño that is commonly associated 
with thunderstorms and flooding had only reached men, but not women who are in 
charge of household‘s budget management in the region. The exclusion from male 
networks of information severely constrained households‘ ability to recover from the 
natural disaster as women did not allocate savings as financial buffers (Babar, 2006). 
Agrawal (2000) points out that such exclusion from male-centered information flows 
can prove particularly acute in regions of high male out migration. Silvey and 
Elmhirst (2003) describe kin-based networks amongst female labour migrants in 
Indonesia that prevent them from accessing potentially more powerful associations, 
such as trade unions, that would enable them to support their interests. Weaker female 
networks can also be a result of the fewer economic resources that women can 
typically mobilise. In case of business or political favours, valuable contacts typically 
operate through male in-groups, implying that women are usually excluded from 
networks that bring economic advantage (Molyneux, 2002). Dannecker (2005) 
describes networks of male migrants‘ from Bangladesh that not only exclude female 
compatriots but also appear to strategically improve their own position in the global 
labour market through transformation of the gender order in Bangladesh. This is 
undertaken through demands to install the cultural ideal of ‗purdah’, that is, the 
segregation of sexes, which hampers women‘s access to paid employment and their 
 41 
 
(transnational) mobility. If existent, women‘s ties to more influential networks are 
often only indirect through their relationships with men (Silvey and Elmhirst, 2003).  
 2.17 Gender and Involvement in Politics 
The family is the main institution of patriarchy (Kate Millet, 1970), which is an 
important concept in explaining gender inequality. Literarily, it means ―the rule of the 
father‖; more broadly, it refers to a society ruled and dominated by men over women. 
This is inherent in most African families. Giving men a higher social status over 
females has crept into public life, which reflects in state activities. The family plays 
an important role in maintaining this patriarchal order across generations. The 
socialization of children to expect and accept different roles in life has created a social 
mechanism for the development of values that engender the several forms of 
discrimination against the female sex. 
  The greatest psychological weapon available to man is the length of time they 
have enjoyed dominance over women, who have taken it for granted especially in the 
area of politics that often continue to stereotype women and justify their 
subordination.  
Virility deficiency – women‘s conception of politics: Some consensus has been of the 
belief that Nigerian politics is based on high political virility – those who have all it 
takes to compete in the turbulent environment; those who possess the wherewithal to 
take it by force when force is required; those that can march violence with violence. 
This consensus belief that men possess the superior strength, competitiveness, are self 
reliant and are prepared to tussle in political endeavour, whereas women are 
considered too passive to engage in politics and governance. This consensus is also 
constructed by societal norms and values, which through socialization has defined 
different gender roles according to biological differences. Women‘s perception of 
politics as a dirty game and continued fright at the thought of violence has further 
alienated them from mainstream politics. 
 While severally, emphasis is laid on women‘s numerical strength, translating 
such into the attainment of power has been difficult as women are perceived as 
―supporters club, team of cheerers and clappers‖ in contrast to their male counterparts. 
Women politicians seek offices on the premise of being different; most believe they 
 42 
 
must do what men are doing to succeed. And the meekness of women is not to their 
advantage in political tussle. 
Lack of economic and financial incentives: Women‘s historical experience of 
discrimination puts them at a disadvantage economically. Political campaigns are 
expensive and require solid financial backing for success. Over the years, sexual 
division of labour and job opportunities offered on sex basis has given men 
productive gender roles, enabling them to possess more purchasing power over their 
female counterparts. As an implication, the Nigerian labour market has about 75% of 
labour being supplied by men. This economic disparity favours men to the 
disadvantage of women. Only few women that are affluent possess the economic 
power to bankroll political campaigns. Societal value assumes that political activities 
are masculine and this makes it worse as financiers and sponsors of politicians prefer 
male candidates over female ones, since they believe they stand a better chance. Most 
success achieved by women in politics has been through women movements that 
sponsor women political aspirations financially and otherwise. Women dependence 
on men financially made manifest through wife‘s dependence on their husbands in 
families reveals the extent of financial incapacitation of women in Nigerian politics. 
As a result, women political aspirations have been grossly hampered by lack of 
financial bedrock to subsist their endeavour. 
Discriminatory customs and laws: The customary practices of many contemporary 
societies are biased by subjugating women to men and undermining their self-esteem. 
The overall impact of gender bias, cultural norms and practices has entrenched a 
feeling of inferiority in women and place them at a disadvantage vis-à-vis their male 
counterpart in the socio-political scene even in urban centres. 
These socially constructed norms and stereotype roles make women overplay 
their ‗feminity‘ by accepting that they are ‗weaker sexes‘, overemphasizing the dainty 
nature of their sex and regarding exceptional achievement as masculine. For example, 
most customs often prefer sending the male child to school over the female, who is 
expected to nurture siblings and to be married off. This marginally increases the 
illiterate women and stiffens their competition with their male counterparts in politics. 
 43 
 
Lack of affirmative action quota: Affirmative Action is usually a measure 
intended to supplement non-discrimination; it is a broad term encompassing a host of 
policies that seek to support weak groups in society. They include policies where 
deliberate action is used to stop discrimination. A policy process of this kind allows 
for rules that have the objective of enhancing equal opportunity for individuals and 
the improvement, in the situation of marginalized groups. In 1979, the United Nations 
General Assembly adopted the Convention on the Elimination of All Forms of 
Discrimination against Women (CEDAW). This convention has variously been 
described as the ―Bible of women empowerment‖ and ―Women‘s International Bill of 
Rights.‖ Since its adoption it has become a reference point for the women‘s 
movement in the demand for gender equality.  
The Convention ―reflects the depth of the exclusion and restriction practised 
against women solely on the basis of their sex by calling for equal rights for women, 
regardless of their marital status in all fields – political, economic, social, cultural and 
civil. It calls for national legislations to ban discrimination, recommends temporary 
special measures to speed equality in fact between men and women‖ (UNESCO, 
1999:6). The Convention provides that: Adoption by States Parties of temporary 
special measures aimed at accelerating de facto equality between men and women 
shall not be considered discrimination as defined in the present Convention, but shall 
in no way entail as a consequence the maintenance of unequal or separate standards; 
these measures shall be discontinued when the objectives of equality of opportunity 
and treatment have been achieved.. 
The 1999 Constitution made provision somewhat similar affirmative action to 
supplement non-discrimination of contending parties. The Constitution provides that: 
―the composition of the government of the federation or any of its agencies and the 
conduct of its affairs shall be carried out in such a manner as to reflect the federal 
character of Nigeria and the need to promote national unity, and also command 
loyalty, thereby ensuring that there shall be no predominance of persons from a few 
states or from a few ethnic or other sectional groups in that Government or any of its 
agencies.‖ It is not the use of Affirmative Action that seems to be the problem but the 
practical effects and its linkage to fundamental ideas of fairness and justice. By the 
same token there can hardly be a stronger argument for gender based affirmative 
 44 
 
action than equal representation in a country where women who constitute about half 
of the population have been continuously sidelined in public life to the extent that 
they have never held more than 15% of both appointive and elective offices (See 
Table 1 for statistics of elected positions). However, the Constitution was not explicit 
in ensuring equal representation on sexual bases. Unlike the constitutions of some 
African countries, notably South Africa and Uganda, the Constitution of the Federal 
Republic of Nigeria takes no cognizance of the disadvantaged position of women and 
has no provision for gender equality. Apart from the general reference to non 
discrimination on the basis of sex etc, there is nothing in the constitution that is aimed 
at redressing the disparities that exist along gender lines in Nigeria. On the other hand, 
the Federal Character Principle, which is meant to ensure equitable representation of 
states and ethnic groups in national appointments, actually places women at additional 
disadvantage by implying that they can only represent their states of origin ( Afri. J. 
Pol. Sci. Int. Relat).  
 45 
 
Table 1 Comparison of women representation in 2003 and 2007 general elections. 
S/No Position No of No of % in No of % Total 
available Women 2003 Women in 2007 
seats elected elected in 
2007 
1 Presidency 1 0 0 0 0 
2 Senate 109 3 2.27 9 8.26 
3 House of 360 21 5.83 25 6.98 
Representatives 
4 Governorship 36 0 0 0 0 
5 State House of 990 38 3.84 54 5.45 
Assembly 
  
Source: Gender Audit and IPU PARLINE database (2003 and 2008). 
 Where culture does not permit a woman to represent her place of birth, she loses a 
golden opportunity. There have been many cases where a woman‘s state of origin 
disallows her appointment and the husband‘s state also refuses to endorse her. In 
many of these instances the government plays safe by appointing a man instead. And 
this has continued to consolidate women‘s under-representation in national politics. 
Other factors 
i. Inadequate knowledge of written and unwritten rules protecting women‘s 
political rights. 
ii. Religious Doctrine: Some religious doctrines militate against the active 
participation of women in politics and position of authority. As Millet puts it: 
―patriarchy has God on its side‖ that is, Christianity portrays Eve as an after 
thought produced from Adam‘s spare rib. Islamic doctrines strictly bar women 
from some political endeavour – public speaking etc. – that can facilitate their 
political ambitions. In recent times, however, there have been a number of 
 46 
 
movements to the commitment, both to the personal and social change of 
women in their status in public life. 
Through series of women enlightenment, emancipation and conscious raising 
of groups on women movement, women subordination in politics have been reduced 
to an extent. Women through several of these platforms have played influential roles 
and this has further spurred more women in to politics.  
   2.18 Social capital and Social inclusion  
 Social exclusion is described in a shorthand term for what happens when 
people or areas suffer from a combination of linked problems such as unemployment, 
poor skills, low incomes, unfair discrimination, poor housing, high crime, bad health 
and family breakdown.  
It is important to understand that social exclusion is not the same as poverty. It 
is often caused by poverty but there are people living above the poverty line who can 
be socially excluded, for example frail older people. The term social exclusion seeks 
to capture the less tangible aspects that is associated with being poor, such as low 
morale, isolation from social or spiritual networks or cultural resources. 
 For example it can be difficult for young people to secure housing because of; 
 The pace of modern life,  
 family members scattering,  
 people relocating.  
A cohesive community is one where: 
 there is a common vision and a sense of belonging for all communities  
 the diversity of people's different backgrounds and circumstances are 
appreciated and positively valued   
 those from different backgrounds have similar life opportunities  
 strong and positive relationships are being developed between people from 
different backgrounds in the workplace, in schools and within neighborhoods. 
 
 47 
 
2.19 Social Capital and Social Cohesion 
 The Council of Europe has made an attempt to put forward a benchmark 
definition. It defines ‗social cohesion‘ of a modern society as ―society‘s ability to 
secure the long-term well-being of all its members, including equitable access to 
available resources, respect for human dignity with due regard for diversity, personal 
and collective autonomy and responsible participation‖ (Council of Europe, 2005,). 
First of all, the Council stresses that social cohesion is about abilities and capacities of 
certain societies. Second, the definition reveals that social cohesion is also 
multidimensional. The states‘ abilities, as described above, need to be used for the 
protection of a wide range of basic individual rights, namely (1) the well-being of all 
its members, (2) equal access to resources just like labour market but, implicitly, also 
to more extended civil, political and social rights, (3) respect for human dignity and 
(4) the importance of participation in society. Thus, ‗social cohesion‘ in this respect 
seems to be a process which is influenced, to a large extent, by governmental policies 
and leads to some basic rights for citizens of the European Union.  
The Council stresses that ―social cohesion is not a ‗nostalgic‘ concept 
hankering after a ‗lost social harmony‘, but a highly topical one that encompasses key 
aspects of political strategy for a modern society based on the recognition of rights,‖ 
the Council rather seems to opt for a more communitarian view on social cohesion by 
seeing it as the responsibility and ability of the state to secure an environment in 
which citizens can express themselves, can freely participate in society, enjoy 
assistance to keep them out of poverty and marginalization, and so on.  
 Jenson (1998) mentions five dimensions in the concept of social cohesion to 
include belonging/isolation which means that ―a cohesive society is one in which 
citizens ‗share values‘‘. The second, dimension, inclusion/exclusion refers to the fact 
that high cohesive societies are characterized by equal access to economic institutions. 
Third, along the participation/non-involvement dimension, it is possible to distinguish 
high cohesive societies from low ones on the basis of the involvement of the 
population on the local level with respect to democratic practices. According to the 
fourth dimension, recognition/rejection, high cohesive societies are the ones in which 
diversity is recognized. Fifth, the legitimacy/ illegitimacy dimension refers to the fact 
 48 
 
that a society cannot be cohesive if the institutions miss a sufficient level of 
legitimacy. A couple of years later, Kearns and Forrest (2000) described social 
cohesion in urban societies and arrive as well to five dimensions. (1) Common values 
and a civic culture; in accordance with Jenson, a society which somewhat holds on to 
the same common values and is committed to the political system is rather a cohesive 
one. (2) Social order and social control; in a cohesive society, there are mechanisms 
that retain social order and social order, other and more subtle means than coercion 
and repression; (3) Social solidarity and reductions in wealth disparities; in a high 
cohesive society, there are forms of social solidarities and formal and informal 
institutions that reduce large inequalities. (4) Social networks and social capital; in 
this respect, high cohesive societies are societies with lots of interactions. (5) 
Territorial belonging and identity; strong adherence to a certain territory facilitates 
living together because of the application of common rules and the strive for a 
prosperous society.  
 
 
 
 
 
 49 
 
CHAPTER THREE 
Research Methodology 
3.1 Study Area. 
The study was conducted in Osun and Ondo states, Nigeria.  Osun state is one 
of the twelve pilot states for the Community Based Poverty Reduction Agency 
programme by the World Bank and Federal Government of Nigeria (NPC, 2000; FOS 
2000). It also has a relatively well organized Agricultural Development Programme 
ADP coupled with a large number of co operative societies and other formal and 
informal associations (World Bank, 2000). The state has a tropical type of climate 
marked by a distinct dry (November – March) and wet (April - October) season. Its 
0
average temperature is 30 C while relative humidity could be as high as 95 percent. 
Osun State has thirty Local Government Areas (LGAs) and Modakeke- Ife 
area office. It covers an area of approximately 14,875 square kilometres and lies 
between longitude 0400E and latitude 05558 N. It has a population of 3.4 million ( 
NPC,2006) and falls in the humidity forest / derived savannah zone with elevation of 
between 200m to 1000m above sea level. It shares borders with Kwara state in the 
North, Ondo in the South, Ekiti in the East and Oyo/ Ogun in the West. The indigenes 
are Yorubas and are composed of the Oyos, Ifes, Ijeshas and Ibolos. Traditionally, the 
people engage in Agriculture and are into food crops such as cassava, yam, rice, 
plantain, banana, sweet potatoes, and vegetables while cash crops such as cocoa, kola 
nuts, oil palm and citrus are produced in large quantities. Other occupations of the 
people include hand- weaving, mat-weaving, tie and dying, wood- carving, drumming 
and drum- making among others.    
 Ondo State   is one of the oil producing states in Nigeria and one of the richest 
states in the south west with relatively high number of cooperative societies 
2 
(NEEDS,2006, Ondo State, 2003). It has a land area of 14,769km with a population 
of 3.44102 million people (NPC, 2006) and consists of eighteen local government 
0 0
areas. Geographically, Ondo is located between longitude 4.30 E and 6.00 E of the 
0 1 0 1
Greenwhich and Latitude 5 45 and 8 15  of the equator. Kwara, Kogi and Ekiti 
states bound the state to the North. Edo and Delta states to the East: Ogun and Osun 
states to the West and the Atlantic Ocean to the South.  Osun and Ondo states have 
the same climatic conditions, although in recent times, minor alterations are 
noticeable in rainfall regimes due to global climate change. Ondo state is blessed with 
 50 
 
0 
a moderate year temperature of around 25 C. Annual Rainfall varies from 2000mm in 
the southern part to 1,150mm in the northern extremes (Ondo – State, 2003). The 
major tribes are the Akures, Akokos, Owos, Ondos and the Ilajes. The people engage 
in Agriculture and are into food crops such as cassava, yam, rice, plantain, banana, 
and vegetables while cash crops such as cocoa, kola nuts, oil palm and citrus are also 
produced in large quantities. Other occupations of the people include fishing, hand 
weaving and mat weaving among others.    
 
3.2 Method of data collection 
Both primary and secondary data are utilized in this study. Primary data were 
collected by means of well – structured questionnaire and personal interviews. The 
study employed multistage sampling techniques. The first stage involved the 
purposive selection of Osun and Ondo states from the six States that make up the 
south west. The choice was based on the fact that they have the highest number of 
cooperative societies as well as organised professional and local associations 
(NEEDS, 2006). Osun and Ondo states have three senatorial districts each. Two of 
these districts were purposively selected in each state based on the number of 
registered cooperatives. (SEEDS, 2006) In Osun state, these are Osun central and 
Osun East while in Ondo state; they are Ondo central and Ondo north. This 
constitutes the first stage of data collection. Four Local Government Areas LGAs 
each were randomly selected from the ten local government areas of Osun Central and 
the ten LGAs of Osun East for a total of eight. Four LGAs each were also randomly 
selected from the six Ondo central and the six LGAs of Ondo North.  In all, the 
selection of 16 LGAs from the 38 LGAs in the two states formed the second stage. 
The third stage was the random selection of five communities each from the selected 
LGAs.   
Finally, from Osun Central, 90 respondents were randomly selected and 100s 
respondents were selected from Osun East, thereby making a total of 190 respondents 
from Osun State.  Also, 90 respondents   were randomly selected from Ondo central 
and another 90 from Ondo north. In all, 180 respondents were sampled from Ondo 
State. However, of the 190 respondents from Osun state, only 160 gave consistent 
responses. Also in Ondo state, only 160 out of the 180 respondents gave correct 
responses. In all, a total of 320 responses were analysed in this study. The remaining 
 51 
 
50 respondents were excluded due to inconsistencies in their responses. This study 
measures social capital at the local government level, using households, to enable it 
compare the results with those obtained previously in the state level analyses. The 
work of Putnam (1993) which shows that associational activities enable communities 
to solve collective action problems by promoting cooperation will be adjusted to solve 
and modify productive resources problem in the study area. A more general 
household-level social capital index would be formulated using several measures 
including associational densities. 
 
  
 
 
 
 52 
 
Fig. 5 Map of Osun and Ondo States showing the Senatorial Districts 
 
 53 
 
Table 2 Sample Frame for the study 
State Senatorial Zone LGAs Number of Number of Number of Number of 
communities households questionnaire questionnaire 
distributed retrieved 
Osun  Osun Central Odo-Otin 5 24 24 23 
  Olorunda 5 24 24 24 
  Ifelodun 5 25 25 20 
  Boripe 5 25 25 20 
 Osun East Atakumosa East 5 25 25 22 
  Atakumosa West 5 25 25 18 
  Ilesa West 5 24 24 20 
  Ilesa East 5 24 24 18 
Ondo Ondo Central Ondo West 5 22 22 18 
  Ile-Oluji Okegbo 5 22 22 20 
  Odigbo 5 22 22 20 
  Ifedore 5 22 22 20 
 Ondo North Akoko North 5 21 21 19 
West 
  Akoko North East 5 22 22 20 
  Owo  5 22 22 19 
  Ose 5 21 21 19 
Total 4 16 80 370 370 320 
Source; Field Survey: 2007 
 
 
 
 
 
 
 
 
 
 
  
 54 
 
3.3 Analytical Techniques 
The study employs analytical techniques based on its objectives. The tools include: 
1. Descriptive Statistics 
2. Principal component 
3. Multiple Regressions : Social Capital Index, Household Welfare Model, 
Household Income model  
4. Tobit regression model 
 3.3.1     Descriptive Statistics 
This is used to identify various dimensions of Social Capital. It includes 
frequency distribution, mean, mode, median, percentages, graphs and coefficient of 
variation. These are used to catalogue and categorize households by associations and 
welfare status.  
3.3.2 Principal component analysis  
This was used to pool all the asset items together as an index. The principal 
component analysis involves resolution of a set of variables into a new set of 
composite variables or principal components that are uncorrelated with one another. 
This is accomplished by the analysis of the correlation among the variables. The result 
of this is a yield of factors which convey all the essential information of the original 
set of variables. Principal component analysis (PCA) is a multivariate statistical 
technique that addresses itself to the study of interrelationships among a set of 
observed variables.  All the variables in PCA are considered as dependent variables 
that is a function of some underlying latent are supposed to be orthogonal that is, 
uncorrelated one therefore look for the best linear combination of these variables that 
account for more of the variance in the data as a whole than any other linear 
combination of variables (Mazlum, et al, 1999). 
 The first principal component may be viewed as the single best summary of 
linear relationships exhibited in the data. The second component is the next best linear 
combination of variables under the condition that the second component is orthogonal 
to the first components. The second one must account for the proportion of variance 
not accounted for by the first one. Subsequent components are similarly defined until 
all the data are exhausted. PC requires as many components as there are variables. 
 
 
 55 
 
 Principal component model may be compactly specified as  
                    Zj = ajiFi + aj2F2 + aj3F3 + ………+ajnFn      
…………………………………. (12) 
 
Where each of the n observed variables is described linearly in terms of the 
 n new uncorrelated components F1, F2, F3, ……. Fn each of which in turn is defined 
as a linear combination of the n original variables. 
In this study, household asset index will be determined following Principal 
Component Analysis (PCA) approach by (Filmer and Pritchett 1998 cited in 
Prakonhsai 2006). Principle component analysis (PCA) is a statistical technique 
closely related to factor analysis. PCA can determine the weight as a factor score for 
each asset variable. It seeks a linear combination of variables such that the maximum 
variance is extracted from the variables. It then removes this variance and seeks a 
second linear combination which explains the maximum proportion of the remaining 
variance. The first principal component is the linear index of variables with the largest 
amount of information common to all of the variables. The asset index derived from 
PCA for each household asset can be written as follows: 
 
……………………………………………………….. (13) 
 Where 
 
A j is an asset index for each household (j =1,…….,n) 
fi is the scoring factor for each durable asset of household (i =1,……,n) 
aji is the i th asset of j th household (i ,j =1,……,n) 
ai is the mean of i th asset of household (i =1,……,n) 
si is the standard deviation of i th asset of household (i =1,……,n) 
Z is the standardized variables of each household 
Derived from PCA, scoring factors of the first principal component (the 
efficient component) would be used for constructing the asset index of each 
household. Using the asset index computed by this formula, each household would be 
grouped into quintiles and deciles. The first quintile or decile is the poorest, while the 
fifth quintile or the tenth decile is the richest. 
  
 56 
 
3.3.3 Construction of Social Capital Index 
  Social Capital Index is used to classify respondents in terms of their 
participation in the identified social capital dimensions. It is an input-based index that 
quantifies each level of participation of the respondent‘s priorities in terms of the 
degree of participation. This index will show the degree of participation of the 
respondents in the identified dimension. 
 
 
 
 ……………………………………………………..(14) 
  
 
                         
                                       
 
 
I is the typical composite indicator of social capital index of the respondents 
Wi`s are weights assigned to degree of participation of respondents to social capital 
dimensions. 
Where n (number of identified social capital dimensions) = 6 
The social capital dimensions used are  GNY = Group and Network,  TSY = Trust 
and Solidarity,CAC = Collective action and Cooperation,  IFC = Information and 
Communication, SCX = Social Cohesion and Inclusion,  and EPA = Empowerment 
and Political Action. 
Before the method of standardization, re-scaled values are created in order to 
assign an identical range for the standardized scores for every indicator. Re-scaling 
ensures that the transformed indicators are given a value relative to the global 
maximum and that the re-scaled index takes a value from 0 (worst) to 1 (best) as 
follows:  
                 …………………………… (15) 
 
Where Уin = The Standardization score 
 57 
 
In this example, standardization is based on the range rather than on the 
standard deviation and the extreme values (minimum and maximum) may in fact be 
unreliable outliers. While the method may be more robust where there are numerous 
outliers, the range for indicators with very little variation will increase and these will 
contribute more to the composite indicator than they would if the un-scaled method 
was used. This technique is therefore more dependent on the value of the weights for 
each indicator than the un-scaled method where the contribution of each indicator to 
the composite depends on both the weighting and the variance of the indicator. Thus 
the re-scaling method is linked to the issue of choice of weights. In other words, the 
overall index will be affected by the performance of the worst and best country. 
Therefore the Social Capital Index SC is constructed as follows: 
SCit = β(GNYit) + α(TSYit) + δ(CACit) + γ(IFCit) + λ(SCXit) +  D(EPAit) ………..(16) 
Where  the variables are as defined earlier.        
Social Capital Index Model is used to estimate the effects of social economic 
variables on households‘ Social Capital. Social Capital Index (SCl) =This is an 
aggregation of the responses of each household to the questions on the various social 
capital dimension mentioned above, On each of the six dimensions‘, each household 
answered questions on it. Therefore, for each of the factors a yes response is coded 1 
while no response is coded 0. A maximum score of 10 for each association represents 
the highest level of heterogeneity. The scores by the six dimensions for each 
household are then divided by the maximum score of 60 to obtain an index.  
 
3.3.4 The Aggregate Model     
A conventional model of household economic behaviour can readily be 
adjusted to reflect the role of social capital (Grootaert 2002). Such a model consists of 
three sets of equations; the first set of equations explains the income generation 
behaviour of the household and describes how the household combines its various 
asset endowments to make decisions regarding labour supply for each of its members, 
taking the wage rates and demand situation in the labour market as given. In this 
formulation, social capital can be considered as one among several classes of assets 
available to the household to make its decisions. Social capital is combined with 
human capital, physical capital and the ownership of land to make productive 
decisions. 
 58 
 
The second set of equations portrays the household‘s demand for inputs 
(agricultural inputs, credit) and services (education, health) which may need to be 
combined with labour supply in order to generate income. Here too, social capital is 
one category of capital which determines these decisions.  
A third set of equations explains the households‘ consumption and savings 
behaviour as a function of the level and composition of income. The customary 
reduced-form model of these structural equations relates household expenditure 
directly to the exogenous asset endowment of the household.   
The key feature of this model is the assumption that social capital is truly 
―capital‖ and hence has a measurable return to the household. Social capital has many 
―capital‖ features: it requires resources (especially time) to be produced and it is 
subject to accumulation and de-accumulation.  Social capital can be acquired in 
formal or informal settings, just like human capital (e.g., schools versus learning-by-
doing). Much social capital is built during interactions which occur for social, 
religious, or cultural reasons. The key assumption is that the networks built through 
these interactions have measurable benefits to the participating individuals, and lead, 
directly or indirectly to a higher level of well-being. This is the proposition which we 
test empirically in the study by means of equations.   
Various functions which determine access to credit, agricultural inputs or 
other factors which enhance the productivity of a household enterprise could be used 
but in these estimations, we  focused on credit. The dependent variable of the equation 
is the natural logarithm of household income per capita. The explanatory variables 
consist of the asset endowment of the household, demographic control variables, and 
locational dummy variables. Household assets are assumed to consist of human 
capital, social capital, land, and physical assets. Human capital is measured 
conventionally by the years of education of the adult members of the household. The 
LLI study data set contains information on land, crops, cattle and farm equipment 
owned by the household. Direct inclusion of these variables as regresses in equation  
is problematic due to possible endogeneity.   
Social capital and Household Expenditure (welfare) .Following Marayan and 
Pritchett (1999) and Grootaert (1999), we estimate cross sectional household level 
logarithmic per Capita expenditure function, augmented by the inclusion of proxy 
 59 
 
measures for social capital. The functional form used is similar to those estimated by 
May (2000) 
Model Specification       
The model of household economic behaviour as adjusted by Grootaert (2002) is used 
to reflect the role of social capital on household‘s welfare where  
Ei = f(S1 , S2, S3,  .  .  .  ,S19) 
The linear estimating function form of the functional form is given as : 
EI= a0 + a1 S1+ a2 S2 + a3 S3  +  .  .  .  +  a19 S19 +  ξ1  ---------------------------------(18) 
E1= household per capita expenditure on all items (e.g food and non food) 
S1 =   Household involvement in Groups and networks (%) 
S2 = =   Household involvement in Trust and Solidarity (%)  
S3 = Household head involvement in Collective Action and Cooperation (%) 
S4 = Household head involvement in Information and Communication (%) 
S5 = Household head involvement in Empowerment and Political Action (%)  
S6 = Household head involvement in Social cohesion and Inclusion (%) 
 S7 = Household head Cash contribution index (%) 
S8 = Household head Labour contribution (%)  
S9 =     Density of Membership of household heads (%) 
S10 = Heterogeneous Index (%)   
S11=Meeting attendance (Mandays) 
S12 =Participation in Decision Making(%) 
S13 = Membership in Financial Institution S13 = 1 if yes and= 0 if otherwise    
S14 = Household Size (Number) 
S15 = Educational Status per Household Head Yr) 
S16 =Age of Household Head (Yr) 
S17 = Age of Household Head Squared (Yr) 
S18 = Household asset score (Naira) 
S19 = Sex of household heads S19 = 1 if sex is male and =0 female if otherwise 
Φi =     Error term      
The aggregate social capital index is obtained by the multiplication of groups and 
networks, collective action and cooperative, information and communication, social 
cohesion and inclusion  and empowerment and political action index ( Grootaet 2002) 
the resultant index is normalized to  value of 100. 
 60 
 
   
3.3.5    The Disaggregate Model; Household welfare model 
The disaggregate model of social capital endowment by gender is used to 
capture the links among house holds welfare, poverty and social capital  The 
aggregate index made use of some dimensions which are assumed to interact with one 
another in multiplicative way. The disaggregate model however considers that each 
social capital dimension acts independently and that the effects are multiplicative and 
additives. Both multiplicative and additives social capital index are used to determine 
the impact of social capital on welfare proxied by per capita expenditure of 
household. The use of both multiplicative and additive social capital is hinged on the 
fact that to date literature on conceptual and theoretical underpinning of social capital 
has not proved the superiority of one over the other. Grootaet etal (2002) Narayan and 
Pritchett (1997) use both approaches and conclude that additive and multiplicative 
variables are valid approaches and can be introduced into a behavioural model   
    E1= F(W1, W2, W3, W4, .  .  .  , W17) 
In E1= co +   c1W1 +  c2 W2+ c3 W3  + .  .  .  + c 15 W15  +ηI ------------------------(19) 
When E1 = Household per capita total expenditure on all items  
W1 = Male Household involvement in Groups and networks (%) 
W2 =Female Household involvement in Groups and networks (%) 
W3 = Male Household involvement in Trust and Solidarity (%) 
W4 =Female Household involvement in Trust and Solidarity (%)  
W5 = Male Household head involvement in Collective Action and Cooperation (%) 
W6 = Female Household head involvement in Collective Action and Cooperation (%)  
W7= Male Household head involvement in Information and Communication (%) 
W8=Female Household head involvement in Information and Communication (%) 
W9 = Male Household head involvement in Empowerment and Political Action (%) 
W10 = Female Household head involvement in Empowerment and Political Action (%) 
W11= Male Household head involvement in Social cohesion and Inclusion (%)  
W12= Female Household head involvement in Social cohesion and Inclusion (%) 
 W13 = Household head Cash contribution index (%) 
W14 = Household head Cash contribution index (%)  
W15 =Male Household head Labour contribution (%)  
 W16 =Female Household head Labour contribution (%) 
 61 
 
W17 =    Male Household head Density of Membership of household heads (%)  
W18 =    Female household head Density of Membership of household heads (%) 
W19 = Male household head Heterogeneous Index (%)   
W20 = Female household head Heterogeneous Index (%)   
W21= male household head Meeting attendance (Mandays) 
W22=FemaleMeetingattendance(Mandays)  
W23 =Participation in Decision- Making(%) 
W24 =Participation in Decision- Making (%) 
W25 = Membership in Financial Institution S13 = 1 if yes and= 0 if otherwise    
W26 = Household Size (Number) 
W27 = Educational Status per Household Head Yr) 
W28 =Age of Household Head (Yr) 
W29 = Age of Household Head Squared (Yr) 
W30= Household asset score (Naira) 
W31 = Sex of household heads S19 = 1 if sex is male and =0 female if otherwise 
λ1 = error term   
 
3.3.6 Tobit Regression model: Asset Accumulation. 
    Following a Tobit decomposition framework suggested by McDonald and 
Moffitt (1980), the effects of changes in socio-economic and social capital variables 
on asset accumulation by household heads can be obtained. The model has the 
capability of estimating an equation system whereby the probability of an event 
happening or not can be captured in the dependent variable. This is the reason Tobit 
model is usually used in regression modelling to solve the problem of zero 
observation(s) in the dependent variable (Blundell and Meghir. 2002; Wen et al, 2002: 
Blaylock and Blissard. 2000). Therefore, Tobit model will be used in this asset 
modelling to analyse asset accumulation by househeads in the study area. The model 
follows the general form of OLS and is stated as below: 
Asset index (AI) = Vi + pi if Xi + pi > 0 ………………………………… (20) 
AI= Vi + pi if Xi + pi ≤ 0  ……………………………………………….. (21) 
Where:- 
 =  Vector of unknown parameters: 
th
AI  = Asset Index by i  household head  
 62 
 
Xi   = vector of explanatory variables: 
Pi  = random error term 
The independent explanatory variables, (Xi) which are the socio-economic/social 
capital dimensions included in the model, are: 
X1   = Gender of household head (X1 = 1 if male and 0 if otherwise) 
X2  =  Household size (number) 
X3  =  Educational level household head (Years) 
X4  =  Age of household head 
X5 = Age of Household Head Squared (Yr)  
X6  =  Farm size (hectares) 
X7  =  Primary occupation  ( 1 if farming and 0 otherwise) 
X8  =  Membership of association ( 1 if household head belongs and 0 otherwise) 
X9  =  Amount requested Cooperative societies, banks, friends and relatives etc 
(Naira) 
X10  =  Source of credit  (X9= 1 if from farmer association and 0 otherwise) 
X11 = Source of credit (X10= 1 if from community association and 0 otherwise) 
X12 = Source of credit (X11= 1 if from cooperatives and 0 otherwise) 
X13 = Source of credit (X12= 1 if from bank and 0 otherwise) 
X14 = Source of credit (X13= 1 if from friends and family and 0 otherwise) 
X15 = Source of credit (X14= 1 if from money lenders and 0 otherwise) 
X16 = Time lag between application and disbursement (months) 
X17 = Interest rate (%) 
X18 = Request for collateral for loan (X17= 1 if requested and 0 otherwise) 
X19 = Savings (X18= 1 if household head has social savings and 0 otherwise) 
X20 = Presence of collateral (X19= 1 if household head has collateral and 0 otherwise) 
X21 = Type of saving (X20= 1 household head saves in the bank and 0 otherwise) 
X22 = Land Tenure (X21= 1 if household head inherited land and 0 otherwise) 
X23 = Groups and Network %  
X24 = Trust and solidarity % 
X25 = Collective action and cooperation % 
X26 = Information and communication % 
X27 = Social cohesion and inclusion % 
X28 = Empowerment and political action % 
 63 
 
X29 = Aggregate social capital index %  
 
3.3.7 Tobit Regression model; Access to Credit 
    Following a Tobit decomposition framework suggested by McDonald and 
Moffitt (1980), the effects of changes in socio-economic and social capital variables 
on credit access by household heads can be obtained. The model has the capability of 
estimating an equation system whereby the probability of an event happening or not 
can be captured in the dependent variable. This is the reason Tobit model is usually 
used in regression modelling to solve the problem of zero observation(s) in the 
dependent variable (Blundell and Meghir. 2002; Wen et al, 2002: Blaylock and 
Blissard. 2000). Therefore, Tobit model will be used in this credit modelling to 
analyse credit access by househeads in the study area. The model follows the general 
form of OLS and is stated as below: 
AC= Vi + pi if Xi + pi > 0  ………………………………………………… (22) 
AC= Vi + pi if Xi + pi ≤ 0  ……………………………………………….. (23) 
Where:- 
    =  Vector of unknown parameters: 
th
AC  = access to credit by i  household head  
Xi   = vector of explanatory variables: 
Pi  = random error term 
The explanatory variables, which are the socio-economic/social capital dimensions 
included in the model, are: 
The independent variables (Xi) are itemized below: 
X1   =  Gender of household head (X1  1 if male and 0 if otherwise) 
X2  =  Household size (number) 
X3  =  Educational level household head (Years) 
X4  =  Age of household head 
X5 = Age of Household Head Squared (Yr)  
X6  =  Farm size (hectares) 
X7  =  Primary occupation  ( 1 if farming and 0 otherwise) 
X8  =  Membership of association ( 1 if household head belongs and 0 otherwise) 
X9  =  Amount requested (Naira) 
X10  =  Source of credit  ( 1 if from farmer association and 0 otherwise) 
 64 
 
X11 =  Source of credit  ( 1 if from community association and 0 otherwise) 
X12 =  Source of credit ( 1 if from cooperatives and 0 otherwise) 
X13 =  Source of credit  ( 1 if from bank and 0 otherwise) 
X14 =  Source of credit  ( 1 if from friends and family and 0 otherwise) 
X15 =  Source of 1 if from money lenders and 0 credit  (otherwise) 
X16 =  Time lag between application and disbursement (months) 
X17 =  Interest rate (%) 
X18 =  Request for collateral for loan ( 1 if requested and 0 otherwise) 
X19 =  Savings  ( 1 if household head has social savings and 0 otherwise) 
X20 =  Presence of collateral  ( 1 if household head  has collateral and 0 otherwise) 
X21 =  Type of saving ( 1 household head saves in the bank and 0 otherwise) 
X22 =  Land Tenure  ( 1 if household head inherited land and 0 otherwise) 
X23 =  Groups and Network %  
X24 =  Trust and solidarity % 
X25 =  Collective action and cooperation % 
X26 =  Information and communication % 
X27 =  Social cohesion and inclusion % 
X28 =  Empowerment and political action % 
X29 =  Aggregate social capital index % 
 
3.3.8 OLS Regression model: Participation in collective action 
Model Specification. 
Participation in Collective Action (PCA) = f (X1, X2, X3, .  .  .  ,X16) 
The estimated linear equation arising from the functional form is 
PCA = B0 + B1 X1 + B2 X2+ B3X3 +  .  .  .  +  B16X16 + U1--------------------------------------------(24) 
Where PCA = participation in collective action, Ui= error term, B`s= parameters to be 
estimated. The explanatory variables, which are the socio-economic/social capital 
dimensions included in the model, are: 
The independent variables (Xi) are itemized below: 
X1   = Primary occupation of household head (1=farming, 0 otherwise) 
X2  =  Household size (number) 
X3  =  Educational level household head (Years)  
X4  =  Male household head (1=yes  0 otherwise) 
 65 
 
X5  =  Age of household head(Year) 
2 
X6  =  Age squared of household head (Year)
 
X7 =  Number of Memberships  %  
X8 = Membership in Financial Institution   (1=yes 0 otherwise) 
X9 = Participation in Decision- Making % 
X10 = Meeting Attendance % 
X11 = Groups and networks % 
X12 = Trust and Solidarity % 
X13 = Collective Action and Cooperation % 
X14 = Information and Communication % 
X15 =   Social Cohesion and Inclusion % 
X16= Empowerment and political action%  
 
3.4  Definition of Variables and Concepts.  
The explanatory variables used in the models are as follows; 
Age; It measures the age of household‘s head in years. 
Age squared; Age Squared measures the life cycle of the household‘s head 
Gender; Gender is exacerbated by the different power relations between male and 
female. 
Educational level; This is the number of years spent in formal school. 
Household size; This is the number of people eating from the same pot. 
Marital status: this is whether the house hold head is married or not. It is represented 
by a dummy variable. 
Primary occupation; It is a dummy variable which indicates household‘s head nature 
of job. It is represented if household head engages in farming as primary occupation 
and 0 if otherwise. 
Household total expenditure; Household total expenditure on food and non food items 
(proxy for income). 
Social capital dimensions description: Social capital dimension measurement 
was carried out to examine the influence of social capital on rural household welfare 
on gender basis. The effectiveness with which social capital , in the form of local 
associations, can fulfil its role in disseminating information, reducing opportunistic 
behaviour, and facilitating collective decision- making depends on many aspects of 
 66 
 
the association, reflecting its structure, its membership and its function. For this study 
we focus on twelve of the dimensions adopted by the World Bank (2004), Grootaert 
and Narayan, (2000), Okunmadewa et al, (2005), Okumadewa et al (2007) and 
Yusuf,(2008). The social capital (SC) variables that were used include: Group and 
Network, Trust and Solidarity, Collective action and Cooperation, Social cohesion 
and Inclusion, Information and Communication and Empowerment and Political 
action. Others include Density of membership, Heterogeneity index, Meeting 
attendance, Cash contribution, Labour contribution and Decision making index.  
(A) Groups and Networks: This comprises the summation of density of membership, 
heterogeneity index, meeting attendance, cash contribution, labour contribution and 
decision making index. The measurement of each of the indices is explained 
following Grooteart 2002, Okumadewa et al; 2005, and Yusuf, 2008.  
(i) Density of membership: This is captured by the summation of the total number of 
associations to which each household belongs. A complete inventory of all 
associations was made at local level institutions; each household was then given that 
inventory and asked which associations they are members. In other words, the 
proportion of membership of associations by individuals is found and rescaled to 100 
(ii) Heterogeneity Index : This is an aggregation of the responses of each household to 
the questions on the density of the three most important institutions to the households. 
On each of the three associations, each household answered questions on whether 
members live in same neighbourhood, are of the same kin group, same occupation, 
same gender, age group and religion. Hence for each of the factors, a yes response is 
coded one while no response is coded zero. A maximum score of 10 for each 
association represents the highest level of heterogeneity. The scores by the three 
associations for each household are then divided by the maximum score of 30 to 
obtain an index. The index was then multiplied by hundred with a zero value 
representing complete homogeneity). 
(iii) Meeting attendance index: This is obtained by summing up the attendance of 
household members at meetings and relating it to the number of scheduled meetings 
by associations they belong to. This value was then multiplied by 100. 
(iv) Cash contribution: This was obtained by the various associations which the 
household belongs. The actual cash contribution for each household is rescaled by 
 67 
 
dividing this amount by the maximum fee amount in the data and multiplying the 
resultant fraction by 100. 
(v) Labour contribution: This is the number of days that household members 
belonging to institutions claimed to have worked for their institutions. This represents 
the total number of man hour‘s days worked by household members. This is also 
rescaled to 100 using the same method of cash contribution. 
(vi)  Decision- making index; it has been argued that associations, which follow a 
democratic pattern of decision-making, are more effective than others. The 
questionnaire asked association members to evaluate subjectively whether they were 
‗‗very active‘‘ ‗‗active‘‘ ‗‗not very active‘‘ or ‗‗passive‘‘ or not participating in group 
decision making. The response was scaled from 4 to 0 respectively, and averaged 
across the three most important groups in each household. The summation was 
calculated from subjective responses from the households‘ members on their rating in 
participation in three important associations to them. The responses were averaged 
across the three associations and multiplied by 100 for each household. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 68 
 
 
CHAPTER FOUR 
RESULTS AND DISCUSSION 
This section presents the result of the descriptive analysis of the demographic 
and socio-economic characteristics of household heads in the study area. The 
discussion covers the age of household heads, educational status of household heads, 
household size,  household heads economic activities, group and network, trust and 
solidarity, social cohesion and inclusion, information and communication, density of 
membership of household , household labour contribution, households‘ empowerment 
and political action, households‘ cash contribution and household per capita 
expenditure as well as other households‘ associational activities. 
 
4.1 Socio-economic/demographic characteristics of respondents 
The socio-economic characteristics normally have effects on involvement in 
social capital and welfare of households in the study area. The households in the study 
area have varying socio-economic characteristics. A descriptive analysis of selected 
socio-economic and demographic variables used in the study area is presented in 
Table 3.  The table shows the age distribution of household heads in the study area. 
The age of the households‘ heads shows that majority of the respondents (42.8%) fell 
into age bracket 41-50 years. The mean age of household heads is estimated at 
44.1±2.2 years for male household heads and 42.3± 1.2 years for female household 
heads. The average age of the household heads for both male and female in the study 
area are below the national average age of 41.7 years. About 33 percent of the male 
household heads are headed by persons aged between 41 and 50 years while about 32 
percent of the male household are between 31 and 40 years of age. Similarly, about 55 
percent of the female household heads are between 41 and 50 years of age while only 
25 percent of the female headed persons are between 31 and 40 years of age. More 
importantly, it is observed that only 23 percent of the male household heads are 
between 21 and 30 years while about 25 percent female house hold heads are between 
21 and 30 years of age. About 13 percent of the male sampled household heads are 
aged 51 years and above while about 4 percent of the female headed households are 
aged 51 years and above. In essence, the age distributions showed that most of the 
 69 
 
respondents sampled (84 percent) are still economically active with just 16 percent in 
the retirement category. 
        The age of the household head is expected to be negatively related to their 
involvement in social capital dimensions. Due to African culture and belief, most 
households are made up of a man, wife/wives, children and most often extended 
family members. All these form the household size.  The result reveals that majority 
of respondents (29.8%) in the study area have household size of between 7and9 
members. While about 32 percent of the male household heads have between 7 to 9 
members, 28 percent of the female household heads have 7 – 9 members. It also 
indicates that about 26 percent of male household heads have between 4 and 6 
members while about 35 percent of female household have between 4 and 6 members. 
The result also shows that about 16 percent of male household heads have above 9 
members while about 15 percent of female household heads have above 9 members. 
The level of education may indicate productivity potential both in farming and non-
farming activities (Abdulai and Delgado, 1990). The more educated an individual is 
the more his/her involvement in non- farming enterprises and likelihood higher 
welfare. The number of years of formal education is known to influence the 
behaviour, values, exposure and households opportunities  
The distribution of sampled household heads based on the years of formal 
education is captured in Table 3. From the table, about 4 percent of the male 
household heads do not have formal education while just about 5 percent of the 
female household heads do not have formal education. The distribution also shows 
that 42 percent of the male headed households have primary school education while 
about 45 percent of the female household heads have primary school education. 
About 35 percent of the female household heads have secondary education attainment 
while 24 percent of the male household heads have secondary education. For post 
secondary education, the female household heads have the lowest post secondary 
education attainment (16 percent) while male household heads have 29 percent. For 
both sexes, the result shows a progressive decrease in the proportion of educated 
household heads as we move from primary through secondary and post- secondary.  
 
 
 
 70 
 
Table 3 Distribution of household heads based on selected socio-economic 
characteristics   
 Male Female Pooled 
Age (Year) % % % 
<    30     23.2  25.0 24.1 
 31-40     32.3 16.0 24.4 
 41-50     31.7 54.5 42.8 
 51-above     12.8 4.5 8.8 
Mean     44.1 42.3 41.7 
Minimum    20.0 21.3 20.0 
Maximum   71.5 67.2 71.5 
Standard deviation     2.2 1.2 1.8 
Household size    
1-3     26.2              25.6 25.9 
 4-6     26.2 31.4 28.8 
7-9      31.7 28.3 29.8 
Greater than 9      15.9 14.8 15.5 
Mean      6.2 5.1 5.7 
Standard deviation       2.3 1.4  
Minimum 1 1 1 
Maximum 15 13 15 
Educational status(yr)     
 Primary       4.3 4.5 4.4 
Secondary       42.1 44.9 43.4 
Specialised       24.4 16.0 20.3 
Tertiary       29.3 34.6 31.9 
Marital status    
 Single     24.4 23.1 23.8 
Married     58.9 52.6 53.6 
Separated     9.1 9.6 9.4 
Divorced     7.3 11.5 9.4 
Widowed     4.3 3.2 3.8 
Source: Field Survey 2007 
 71 
 
Table 4 shows that almost all the sampled households (76.6%) in the study 
area were into crop farming. In the same vein majority of the male household heads 
(79.3%) were into crop farming, the same applied to female household heads (73.7%). 
The study shows that only 6.1% of the male household heads were into livestock 
while 10.3% of female household heads were into livestock business. It also reveals 
that 11.0% of the male respondents were into non- farming activities while just 5.8% 
of female respondents were into non-farming activities. The reason may be due to 
agrarian nature of the study area.  More importantly, most of the farmers (25.6%) 
cultivate between 2.0 and2.49 ha. While 27.4% of male respondents cultivate between 
2.0 and 2.49 ha, just 23.7% female household heads cultivate between 2.0 and2.49 ha.  
The study reveals that majority of the respondents (48.3%) in the study area 
sourced credit from local associations such as cooperatives. While 48.8% of male 
household heads obtained credit from local associations, half of the female household 
heads sourced credit from local associations. Due to lack of collateral security, only 
10.3% of the respondents obtained credit from banks while it was 15.8% and 4.5% of 
male and female respectively that sourced credit from banks.  The study indicates that 
majority of respondents (47.4%) in the study area belong to between 2 and 4 associations. It 
shows that most male household heads (46.2%) belong to between 2 and 4 associations ditto 
female household heads (48.3%). Table 4 revealed that 36.4 % of male household heads 
actively participated in decision- making process while (30.8%) of female household 
heads were involved in active decision making activities. It shows that 37.4% of both 
male and female respondents somewhat participated in decision making while 25.3% 
never participated in decision- making in their respective local associations.  
The proportion of the married male household heads in the area is 58.9% 
while that of female is 52.6%. Others are single, widowed or single parents. Household 
asset value reveals that majority of both male and female household heads (49.3 and 49.8%) 
had asset value of between N 50.001 and 100,000. Only 2.6% of male household heads had 
asset value of less  than N10, 000 while just 3.4% female respondents had asset value of less 
than 10,000. The average asset value of male household heads in the study area was N70, 
147.38 while that of female was N58351.32 and for the pooled it was N58144.72. Asset value 
is one of welfare indicators of the respondents in the study area and could stand as collateral 
for obtaining credit from financial institutions or even local money lenders. 
 72 
 
 Table 4 Distribution of the Respondents by the Household heads’ characteristics   
 Male Female Pooled 
 Means of    
livelihood  
Cop farming      79.3 73.7 76.6 
Livestock farming         6.1 10.3 8.1 
Fish farming        1.2 2.6 1.9 
Trading        2.4 7.7 5.0 
Paid employment       11.0 5.8 8.4 
Farm size    
(Hectares)  
<0.99      11.0 17.3 14.1 
1.0-1.49       15.2 19.2 17.3 
1.50-1.99      14.0 21.8 17.8 
2.0-2.49      27.4 23.7 25.6 
2.50-2.99      14.6 11.5 13.1 
3.0-3.49      14.0 3.9 9.1 
> 3.49       3.7 2.6 3.1 
Mean     2.62 2.31 2.44 
Standard deviation     1.76 1.58 1.73 
Source of credit        
Family and friends     24.4 25.6 20.8 
Local associations     48.8 50.0 48.3 
Banks     15.8 4.5 10.3 
ROSCAS      11.0 19.9 21.6 
Asset value    
< 10,000 2.6 3.4 2.8 
10,000-50,000 49.3 49.8 48.7 
50,0001-100,000 23.5 24.2 19.7 
> 100,000 24.6 22.6 28.8 
Total 100.0 100.0 100.0 
Mean 70,147.38 71,106.53 70,451.65 
SD 57342.13 58351.32 58144.72 
Source: Field Survey, 2007 
  
 73 
 
4.2 Types of Local Level Institutions and household membership  
 Households in the study area belong to various associations from which they 
obtain social capital and subsequent enhancement of their welfare. These include 
Farmers associations, Traders associations, Town/Ethnic groups, Cooperative 
societies, Professional associations, Religious groups, Neighbourhood/ Village 
committees, Political parties, and Non-governmental associations among others. 
Table 5 shows the different types of local level institutions (LLIs) in the study area 
and household membership. The profile in Table 6 shows that household heads in the 
study area belonged to more than one association. The most prominent among them is 
cooperative societies representing about 29% and 33.9%    for male household heads 
and female household heads respectively.  This is followed by Religious groups 18% 
and 16.1% for male and female house heads while household heads‘ involvement in 
political parties, 2.8% and 1.2%, for male and female respondents respectively was 
not encouraging. Of all the household members in the study area, none claimed to be 
involved in environmental protection/ natural resources group. This confirms the 
findings of Ajani and Tijani (2009) that rural households prefer local level 
associations such as cooperative societies, religious groups, political associations and 
occupational associations because of economic and spiritual benefits/ empowerment 
derived from being members of those associations. 
4.3 Sampled Households’ Density of Membership Index  
Table 6 shows the index of density of membership of both male and female 
household heads in the study area. The result reveals that about 31 percent of the male 
household heads belong to at least three associations while about 40 percent of the 
female household heads belong to at least three associations. Also it is discovered that 
about 29 percent of male household heads belong to at least six associations while 25 
percent of female household heads belong to at least six associations. About 4 percent 
of the male respondents belong to about 8 different associations while about 2 percent 
of female household heads belong to about 8 different associations. Most of the 
associations the male household heads belong to are formal such as professional 
groups, farmers association, artisan, religion, cooperative societies, road transport 
workers, and ethnic groups while most of the associations of the female respondents 
are informal such as religion, ethnic or town associations, cooperative societies, local 
money lenders, rotating contributions and so on.  
 74 
 
Table 5: Types of Local Level Institutions and household membership 
Local level Male Female % of total % of total for 
Institutions Household Household for male female 
number number  
Gender Association 55 49 12.7 11.8 
Community based 24 19 5.5 4.6 
Association 
Age Group 31 41 7.1 9.9 
Cooperative 126 141 29.0 33.9 
Societies 
Occupational 56 14 12.9 3.4 
Groups 
Environmental 0 0 0.0 0.0 
Protection/ Natural 
Resources Group 
Religious Groups 78 67 18.0 16.1 
Cultural Group  11 21 2.5 5.1 
Ethnic Group 32 52 7.4 12.5 
Political Parties 12 05 2.8 1.2 
NGO 9 7 2.1 1.7 
Total 434 416 100 100 
Source; Field Survey, 2007  
 
 
 
 75 
 
 Table 6 Sampled Households’ Density of Membership Index 
 
 Male Female Pooled 
Density of % % % 
membership 
(%) 
1-2 31.10 28.20 29.69 
3-4 30.49 39.74 35.00 
5-6 28.66 25.00 26.88 
7-8 6.10 5.13 5.63 
>8 3.66 1.92 2.81 
Total 100 100 100 
Mean 30.0 30.4  
Min 5 10 5 
Max 85 76 85 
 
Source: Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 76 
 
4.4 Households’ Group and Network Index 
Table 7 shows the different types of association the household heads belong to 
in the study area. The result indicates that about 48 percent of male household heads 
belong to cooperative societies while about 40 percent of female household heads 
belong to cooperative societies. About 25 percent of both sexes belong to farmers 
groups. About 28 percent of female household heads belong to religious groups while 
about 4 percent male respondents belong to religious groups.  More importantly, 
about 22 percent of male respondents belong to professional associations while just 5 
percent of female belong to professional associations. The respondents‘ motives of 
joining associations are determined by the benefits (finance, empowerment, security 
etc) being derived from the associations, may be this is why majority of the 
respondents belong to cooperative and farmers groups. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 77 
 
 
 
Table 7 Sampled Households Group and Network index    
 Male Female Pooled 
Participation in % % % 
Network  
Ethnic/Religion 3.05 28.21 15.31 
Professional 21.95 5.13 13.75 
Association 
Farmers Group 24.40 25.00 24.67 
 46.95 39.74 43.44 
Cooperative 
Society 
Others 3.66 1.92 2.81 
Total 100 100 100 
Mean    
Source: Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 
 78 
 
4.5 Households’ Information and Communication Index  
The distribution of sampled household heads on the dimension of information 
and communication is captured in Table 8. From the table, it is discovered that about 
28 percent of women household heads gather most of their information through 
friends and other informal sources while about 8 percent of male household heads do 
so. The information included new entrants into the market, prices of goods and 
services, and outbreak of poultry diseases among others.  Also, about 35 percent of 
male household heads obtain information through electronic media such as radio and 
television while about 24 percent of female household heads obtain information 
through the same source. More importantly, the result indicates that about 36 percent 
of female household heads gather necessary information through Global System of 
Mobile telecommunication (GSM) while about 23 percent of male household heads 
still engage in postal services to exchange information among them. The distribution 
of sampled household heads on the dimension of information and communication is 
captured in Table 8. 
 From the table, it is discovered that about 28 percent of women household 
heads gather most of their information through friends other informal sources while 
about 8 percent of male household heads do so. The information included new 
entrants into the market, prices of goods and services, and outbreak of poultry 
diseases among others.  Also, about 35 percent of male household heads obtain 
information through electronic media such as radio and television while about 24 
percent of female household heads  obtain information through the same source. More 
importantly, the result indicates that about 36 percent of female household heads 
gather necessary information through global system of mobile telecommunication 
GSM while about 23 percent of male household heads still engage in postal services 
to exchange information among themselves. Women are often more dependent on 
informal networks based on everyday forms of collaboration, such as collecting water, 
fetching fuel wood and rearing children. These services, together with the fact that 
women have a high opportunity cost of time, may motivate women to form networks 
with  individuals who are geographically close to reduce the length of time required 
for travel for social interaction. In contrast, men may be engaged in more 
geographically dispersed social networks, such as community projects, and may 
participate more in civic engagement and such participation provides them with 
greater access to information and stimulates information exchange with others 
(Maluccio et al. 2003). 
 79 
 
 Table 8 Households’ Information and Communication Index 
 Male Female Pooled 
 Information and % % % 
Communication 
Friends 7.93 28.08 15.31 
Radio/Television 34.76 24.36 29.69 
Postal Service 21.95 7.05 14.68 
G S M 23,17 35.90 29.38 
>Others 12.20 9.62 10.94 
Total 100 100 100 
Mean 46.0 69.0 51,43 
 Source: Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 80 
 
4.6: Households’ Empowerment and Political Action Index  
Table 9 shows both male and female household heads‘ involvement in politics 
in the study area. The result indicates that about 67 percent of male household head 
are involved in politics while about 22 percent of female household heads are into 
politics. They are those who participated in the 2007 general election. Some of them 
contested for various positions while others only voted in elections. The reason for 
low female participation may be due to virility deficiency, lack of economic and 
financial incentives, discriminatory customs and laws, men domination of politics , 
religious doctrine and lack of affirmative action to mention a few.  
4.7 Households’ Meeting Attendance 
Due to the term of meeting attendance and the importance attached to regular 
meetings, most respondents in the study area attended meeting regularly. As indicated 
in Table (10), female headed households attended meeting more (63%) than male 
headed households (49.6%). The reason for regular meeting attendance may be due to 
the need to source credit and other social benefits from the local level institutions. 
However, average meeting attendance of household in the study area is approximately 
two out of five meetings  
4.8 Households’ Decision Making Index  
Table 11 shows the household participation in decision making activities. The 
result indicates that only about 5 percent of male household heads are leaders while 
about 4 percent of female household heads are into leadership position of the 
associations. Furthermore, the result shows that about 24 percent of the male 
respondents are very active in decision making activities while about 14 percent of 
female respondents are active participators in decision making activities. More 
importantly, over 51 percent of male household heads are somewhat active in decision 
making while about 56 percent of female household heads are somewhat active in 
decision making. The decision making index of male household heads is 73.2 while 
that of female household heads is 57.8. The result shows that male household heads 
are more involved in decision- making activities, hence the tendency to dominate their 
female counterparts. 
 
 
 
 81 
 
Table 9; Households’ Empowerment and Political Action Index 
 
 Male Female Pooled 
Empowerment % % % 
and Political 
Action 
Yes 67.30 21.40 45.00 
No 32.70 78.60 55.00 
Total 100 100 100 
Source: Field Survey, 2007  
 
Table 10 Households’ Meeting Attendance 
 
Meeting Attendance Index % Male Female Pooled 
0-20 0 0 0 
21-40 42.8 28.7 33.7 
41-60 49.6 63.0 60.3 
61-80 2.1 4. 5 5.4 
>80 1.7 3.8 0.6 
Total 100.0 100.0 100.0 
Mean  47.2 38.2 45.0 
SD 11.8 12.3 14.0 
Minimum 31.0 34.0 30.0 
Maximum 58.0 59.4 90.0 
Source; Field Survey, 2007 
 
 
 
 
 
 82 
 
Table 11 Households’ Decision Making Index 
 Male Female Pooled 
Decision % % % 
Making 
Index (%) 
0-20 4.88 3.85 4.38 
21-60 23.78 14.74 19.38 
61-80 51.83 55.77 53.75 
>80 19.51 25.64 22.50 
Total 100 100 100 
Mean 73.0 58.0 61.2 
 Min 4.88 3.85 3.85 
Max 51.83s 55.77 55.75 
Source: Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 83 
 
4.9 Household Heterogeneity Index 
 Heterogeneity index of household heads in associations in Table 12 shows that 
in 21- 40% sub group, male household heads had higher level of heterogeneity 
(70.7%) while that of female headed household is 65.4%. This indicates a diverse 
relationship among household heads in the study area, especially with the mean 
heterogeneity index of 68.4% the household heads relate with each other and readily 
come to the aid of each other in terms of sourcing for credit and other social 
engagements such as wedding, burial and naming ceremonies. 
4.10: Households’ Cash Contribution (Naira)  
Table 13 shows the monthly cash contributions of household heads in the 
study area. The result indicates that about 53 percent of male household heads 
contribute between five hundred and one thousand naira every month while about 62 
percent of female household heads make a monthly contribution of between five 
hundred and one thousand naira only. In addition, about 4 percent of male 
respondents contribute more than two thousand five hundred naira every month while 
about 3 percent of female household heads contribute more than two thousand five 
hundred naira monthly. More importantly, the mean monthly contribution of male 
household heads is N895.90 while that of female household head is N985.67. 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 84 
 
 Table 12 Household Heterogeneity Index 
Heterogeneity Male Female Pooled 
Index % 
0-20 21.0 20.0 30.4 
21-40 70.7 65.4 23.3 
41-60 8.3 14.6 23.5 
61-80 0 0 22.1 
>80 0 0 0.7 
Total  100 100 100.0 
Mean 34.2 36.3 68.4 
SD 5.4 6.8 4.2 
Minimum 26.0 34.0 33.5 
 
Maximum 56.0 59.0 100 
 
Source; Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 85 
 
Table 13: Households’ Cash Contribution (Naira) 
 Male Female Pooled 
Cash % % % 
Contribution 
(Naira) 
0- 500 6.09 10.25 8.13 
501-1000 53.05 62.82 57.81 
1001-1500 18.29 12.18 15.31 
1501-2000 10.98 7.69 9.38 
2001-2500 7.32 4.49 5.94 
>2500 4.27 2.56 3.44 
Total 100 100 100 
Mean N895.90  N985.67 N921.35 
SD N55.37 N72.11 N87.19 
Min N495.00 N450.50 N495.50 
Max N10,000 N15000.50 N15000.50 
Source; Field Survey 2007 
 
 
 
 
 
 
 
 
 
 86 
 
   4.11:  Household Labour Contribution (Man-day)  
Table 14 shows the number of days the sampled household heads claimed to 
have worked for their institutions in the study area. The result indicates that about 43 
percent of male household heads work for 3 to 4 mandays for their associations while 
about 55 percent of female respondents work for between 3 and 4 mandays. About 5 
percent of male household heads actually work for more than 8 mandays for the 
associations while about 6 percent of female household heads work for more than 8 
mandays. The male average labour contribution is 2.4 mandays while that of female 
household heads is 3.2 mandays. 
 
4.12: Household Per capita Expenditure   
As shown in Table 15, the result  indicates that male household head spends 
about N6106.16 monthly on food which accounts for about 36 percent of the total 
expenditure while the female household head  per capita expenditure on food is 
N6027.95 amounting to 43.96 percent. This is followed by the amount spent on 
education of children which is N2568.18 and N1726.84 (15.01 and 12.59 percent) for 
male and female household heads respectively. The result also indicates that male 
household head spends N1908.55 (11.19 percent) on transport while female 
household head spends N1130.73 (8.25 percent) on transport monthly. More 
importantly, the monthly average per capita expenditure for male household head is 
N2, 936.67 while that of female household head is N3, 221.82. The monthly per 
capita expenditure of female household head is a little bit higher than that of male 
because women generally tend to be more responsible for household‘s welfare and 
child rearing more than men (Maluccio et al 2003). Also women have been found to 
join groups that mobilize fewer resources than men because they are resources 
constrained.  
 
 
 
 
 
  
 
 87 
 
 
Table 14:  Household Labour Contribution (Man-day) 
 Male Female Pooled 
Labour % % % 
contribution 
(man-day) 
<1 23.17 22.44 22.81 
2-4 43.29 50.64 46.88 
5-6 17.68 10.26 14.06 
7-8 10.98 10.90 10.94 
>8 4.88 5.77 5.31 
Total 100 100 100 
Mean 2.4  3.2 2.8 
SD 0.3 0.1 0.2 
Min 1 1.5 1 
Max 10 12 12 
 Source: Field Survey, 2007 
 
 
 
 
 
 
 
 
 
 
 88 
 
 
Table 15: Household Per capita Expenditure (Naira) 
  
Expenditure Male Female Pool % Pool 
Items Expenditure 
Food 6106.16 6027.95 12136.06 39.44 12136.06 
 1123.36 1345.68 2469.06 8.02 2469.06 
Clothing 
Medical 682.71 695.34 1378.05 4.48 1378.05 
Education 2568.18 1726.84 4295.02 13.96 4295.02 
Fuel and 1750.93 731.48 2482.41 8.07 2482.41 
Light 
Transport 1908.55 1130.73 3039.28 9.88 3039.28 
Remittance 210.11 220.52 430.63 1.40 430.63 
Rent 1187.56 747.65 1935.21 6.29 1935.21 
Toiletries 532.35 424.15 956.50 3.11 956.50 
Others 987.76 659.74 1647.50 5.35  
Total 17057.67 13712.04 30769.71 100 30769.71 
Mean 2,936.67 3,221.82 11266.77  11266.77 
Monthly per 
capita 
expenditure 
  
 Source; Field Survey, 2007 
 
 
 
 
 
 
  
   
 
 89 
 
 
4.13 Summary Statistics of Social Capital Dimensions and Gender 
Twelve dimensions of social capital and other variables were studied. These 
include Group and Networks, Trust and Solidarity, Collective Action and 
Cooperation, Information and Communication, Social Cohesion and Inclusion and 
Empowerment and Political Action. Others include density of membership, 
heterogeneity index, cash contribution, labour contribution, meeting attendance and 
decision making  
Table 16 indicates that the female headed households have higher values of 
social capital in information and communication (58) and social cohesions and 
inclusion (61) than their male counterparts. The higher information and 
communication (53.70%) may be due to the fact that females naturally have the 
tendency to always gather information about location of new markets as well as 
introduction of new entrants and products into the market including current market 
prices of their products. Also, female headed households have higher social cohesion 
and inclusion (53.50%) to indicate their natural ability to join local associations 
purposely to enhance their households‘ welfare. Conversely, male headed households 
have higher social capital index in groups and networks, trust and solidarity, 
collective action and cooperation and empowerment and political action.  
The male dominance of groups and network may not be unconnected with the 
need to join various social groups and associations to boost their mean per capita 
expenditure while their dominance of collective action and cooperation may be due to 
their involvement in community based poverty reduction projects or communal 
activities.  Male headed households are also more involved in empowerment and 
political action because of the need to enhance their economic and social status 
through political activities. 
 
 
 
 
 
 
 
 90 
 
 
Table 16: Social Capital Dimensions and Gender  
Social Capital Dimension Male (%) Female (%) 
Groups and Networks   53.2 47.8 
Trust and Solidarity  52.9 47.0 
Collective Action and Cooperation  53.1 46.8 
Information and Communication  46.0 69.0 
Social Cohesion and Inclusion  47.0 65.0 
Empowerment and Political Action  67.0 21.0 
Density of Membership (%)  30.0 34.0 
Decision Making Index (%)  73.0 58.0 
Meeting Attendance Index (%)  58.4 64.3 
Labour Contribution Index (%)  56.2 59.1 
Cash Contribution Index (%)  57.4 60.2 
Heterogeneity Index (%)  59.5 61.0 
Mean  56.2 58.9 
Source: Field Survey, 2007 
 
 
 
   
 
 
 
 
 91 
 
4.14: Social Capital Dimensions and Educational Status  
Table 17 shows that both male and female households‘ heads with secondary school 
education seem to have highest level of social capital dimensions index. This may be 
due to their involvement in agriculture and the need to enhance their economic 
activities through local level associations like joining cooperative societies, ethnic 
groups and religious institutions. However, information and communication seems to 
increase with the level of education as households with tertiary education were seen to 
be sharing information and communicating effectively among each other with little or 
no hindrance. This is closely followed by those with those with tertiary education 
either male or female household heads.  Household heads with no formal education or 
primary school education however have low dimensions of social capital due to their 
level of education. 
 92 
 
Table 17: Social Capital Dimensions and Educational Status  
 Male% Female% 
Social Capital Dimension Primary Secondary Specialized Tertiary Primary Secondary Specialized Tertiary 
School School School Institutions School School School Institutions 
Groups and Networks 2.5 24.4 10.6 16.9 1.9 19.6 9.7 15.5 
Trust and Solidarity 6.8 25.0 8.7   14.4 9.7 19.0 9.7 6.6 
Collective Action and 10.6 29.4 1..0   3.4 7.5 27.5 9.1 2.5 
Cooperation 
Information and 2.5   12.8 7.2 16.6 3.1 15.9 15.0 26.9 
Communication 
Social Cohesions and Inclusion 2.8 16.9 7.8   12.2 5.0 30.4 9.3 15.0 
Empowerment and Political 6.1 27.8 15.9   13.8 4.1 14.1 9.1 9.1 
Action 
Density of Membership (%) 5.9 28.1 15.6   13.1 4.4 13.6 9.4 9.7 
Decision Making Index (%) 10.4 29.4 10.6   3.8 7.2 27.5 8.4 2.2 
Meeting Attendance Index (%) 5.9 26.6 15.0   12.5 4.4 15.3 10.0 10.3 
Labour Contribution Index (%) 2.2 23.4 9.3 16.2 2.2 20.0 10.9 15.6 
Cash Contribution Index (%) 3.1 17.8 7.8   10.9 4.6 30.0 10.6 15.0 
Heterogeneity Index (%) 7.2 24.0 9.3   14.1 9.4 20.0 9.0 6.9 
Source: Field Survey, 2007  
 
  
 
 93 
 
 4.15   Social Capital Dimensions and Age of Household Heads 
Table 18 implies that both male and female household heads aged between 31 
and 40 have the highest value of social capital in all its dimensions and this could be 
attributed to the fact that the group easily joins local level institutions as well as 
political associations. This may also be due to the fact that the age group knows the 
importance of joining local and political associations especially people with other 
status, cultures, beliefs, religions and ethnics. It was also observed that male headed 
household between 41 and 50 years of age are mostly involved in collective action 
and cooperation especially in community projects such as monthly environmental 
sanitation, rehabilitation of access roads and bridges. Conversely, female house heads 
aged between 31 and 40 are more involved in collective action and cooperation. More 
importantly, the percentage of household members belonging to local level 
institutions and ability to communicate effectively decreases with age of households. 
 
4.16: Social Capital Dimensions and Household Size  
Table 19  shows that household sizes between 4 and 6 members have the 
highest value of social capital  dimensions including Groups and Networks, Trust and 
Solidarity, Collective action and Cooperation, Information and Communication Social 
Cohesion and inclusion as well as Empowerment and Political action. Their values are 
lowest with household size less than 3 members while household sizes with members 
between 7 and 9 have the highest value of information and Communication and 
density of membership. Also it was discovered that households‘ sizes between 4 and 6 
are more involved in groups and network, trust and solidarity, collective action and 
cooperation, meeting attendance as well as empowerment and political action and 
participation in decision - making. 
 
 
 
 
 
 
 
 
 94 
 
  Table 18: Social Capital Dimensions and Age of Household Heads  
 Age of Households (Years) 
 Male  Female 
Items <    30 31-40 41-50 >  50 <  30 31-40 41-50 >  50 
Groups and Networks (%) 1.9 24.1 11.9 16.6 3.8 15.3 14.1 12.5 
Trust and Solidarity(%) 5.9 13.6 14.7   14.4 10.0 19.7 15.9 5.6 
Collective Action /  Cooperation (%) 9.7 17.5 20.3   5.0 7.5 23.4 9.1 7.5 
Information and Communication (%) 3.1   11.6 12.8 14.7 10.0 15.9 15.0 16.9 
Social Cohesion and Inclusion (%) 3.4 16.6 11.9   12.8 7.5 25.0 11.9 10.9 
Empowerment / political action (%) 8.4 26.9 15.9   13.6 4.1 14.1 9.1 7.8 
Density of Membership (%) 5.6 22.5 14.7   10.9 5.9 15.3 17.5 7.5 
Decision Making Index (%) 10.9 11.1 26.1   5.6 9.1 9.4 22.8 4.7 
Meeting Attendance Index (%) 5.0 20.3 12.8   11.9 4.1 18.7 14.1 13.1 
Labour Contribution Index (%) 4.1 18.1 14.1 13.6 1.9 20.3 19.1 8.8 
Cash Contribution Index (%) 4.4 16.9 13.1   10.9 4.7 20.3 17.2 12.5 
Heterogeneity Index (%) 6.1 23.4 10.3   14.1 9.7 19.7 8.4 8.1 
 
   Source; Field Survey, 2007  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 95 
 
 Table 19: Social Capital Dimensions and Household Size 
Social Capital Dimension Male Female 
Items 1-3 4-6 7-9 >9 1-3 4-6 7-9 >9 
Groups and Networks 3.8 24.1 12.2 11.2 3.8 20.1 15.6 9.1 
Trust and Solidarity 6.8 24.4 15.0   5.0 10.0 19.7 15.9 3.1 
Collective Action and Cooperation 10.3 20.3 17.5   3.1 9.1 23.4 8.4 7.8 
Information and Communication 4.0   12.5 18.8 15.9 10.0 12.5 15.0 11.3 
Social Cohesions and Inclusion 5.9 12.8 16.9   15.6 6.3 23.8 12.2 6.6 
Empowerment and Political Action 7.8 22.8 11.9   8.8 5.3 11.9 15.9 15.7 
Density of Membership (%) 5.6 14.7 22.5   8.4 5.9 15.3 17.5 10.0 
Decision Making Index (%) 9.4 20.0 12.8   9.1 9.7 23.1 8.8 7.2 
Meeting Attendance Index (%) 5.3 18.1 14.7   13.1 4.3 18.4 13.8 12.2 
Labour Contribution Index (%) 4.7 18.1 14.0 14.4 5.0 14.1 19.1 10.6 
Cash Contribution Index (%) 5.0 17.8 15.0   13.4 5.6 18.4 15.0 9.7 
Heterogeneity Index (%) 6.6 23.6 11.6   9.4 10.6 20.0 9.7 8.4 
Source; Field survey, 2007 
 
 
 
 
 
 
 
 96 
 
4.17 Gender Dimensions in Building-up Social Capital. 
Several studies have found that men and women‘s personal networks differ in 
composition, although they are similar in size. Men‘s networks tend to be more 
formal since men are more often involved in formal employment. Moore (1990) 
highlights that men‘s networks include more fellow workers and fewer kin than 
women‘s networks do. This feature was observed in the study areas with the 
formation of the farmers‘ group, and the roles of women in agricultural productions. 
Women have their respective organizations; formal organizations created to 
strengthen the weak social ties between the farmers and the labour class. Women‘s 
networks tend to be informal (eg. ―Esusu‖ group, mutual finance group/chit fund 
group, the Rotating Contributions Associations ROSCA ―alajo‖) and include more kin 
relative to men‘s networks.  
Contrary to evidence from the literature, it was found that women who were 
working on the farm as family labour or as paid labour were more aggressive in 
coming together as a group and discussing their socio-economic and probably marital 
problems and trying to find some solutions to the problems. This was so because they 
realized that as a group they could work out solutions and ways to solve their 
problems and not necessarily depend on the male members of the household. A good 
example of this was the introduction of vocational training for young girls of the 
village who had dropped out of school (Akoko land and Ileoluji/Okeigbo) as well as 
teenage pregnancy that are rampart in Atakumosa East and West and Ilesa East local 
governments. Through their participation in different groups, women were also 
involved in decisions on how the household spends the extra income gained either 
through participation in the different groups e.g. whether to invest in the farm, 
purchase consumption goods, and/or invest in health and education of children.  
Households are grouped in quintiles based on their ranking on an additive 
social capital index. Following Grootaert (2002), we selected the number of 
memberships and the index of active participation in decision- making to construct 
(with equal weights) an additive social capital index. The regression is done because 
an alternative additive index based on all six, equally weighted, social capital 
dimensions yielded similar result. It turns out to that households with higher social 
capital have higher household expenditure per capita, more assets, better access to 
credit and more  likely to have increased their savings in the past year. Furthermore, 
 97 
 
there was no relation between the level of social capital and the need to sell assets to 
make ends meet or perceive hunger. While the strength of the correlation between 
social capital and welfare outcomes differs by indicator, the overall pattern is quite 
strong: social capital correlates positively with household welfare.  
In calculating the threshold to delineate household that are welfare better off and vice-
versa, two-third of income was used (Aigbokhan, 2000; Okurat et a;, 2002). The 
threshold was computed to be N69165.59 Naira. Using this income criterion, 121 
(37.81%) households were discovered to have ―welfare better off‖ 
   
4.18: Household Welfare Indicators, by Levels of Social Capital  
Table 20 indicates that 6% of households were on forced livelihood i;e welfare 
worst off while 25%  of households were welfare better off . We created a dummy 
variable to indicate whether the head of households was a farmer or not. This must be 
seen as an occupational variable as well as a proxy for ownership of agricultural 
assets. The regressions include demographic variables, such as household size and 
gender of the head of household. Age of the head of household and its squared term 
were included to capture the life cycle of household welfare. Lastly, two dummy 
variables were included to indicate state. These variables captured the general 
economic and social conditions of the states along dimensions other than those which 
we were able to include in the model. 
Table 20 consists of one aggregate social capital index, which is a 
multiplicative index between the density of associations, their internal heterogeneity 
and the index of active participation in decision- making. The questionnaire recorded 
only the level of educational achievement of each adult in the household and the 
number of years of education was imputed from that information. 
 In order to assess the impact of this decision, we re-estimated all equations reported 
in this study with three asset variables capturing ownership of land, crops and farm 
equipment.  The model results suggest that human capital as well as social capital 
each have a significant positive effect on household welfare. 
 
 
 
 
 98 
 
 Table 20: Household Welfare Indicators, by Levels of Social  Capital 
1
Variables                     Social Capital Quintiles  
         1 2 3 4      5 All 
(Welfare (Welfare 
Worse off) Better off) 
Income generation  per       156       350       5200 1599.6 
ACaspseitta I n(‘d0eNx2a ira per        0.32      0.41  07.3408  01.55622      0  . 4  2                  0.43   
year                             
% of Children Not      26.7 18.1 1  2  .5        15 1  1  . 2    16.7 
attending School          
% of Households          22.8 20.2  1 5  . 3   1  9   .6  1 7  . 2     19.02 
Going Hungry               
% of Households with          12.4 14.5 1  8   .1 1  8  .1        19.8 12.96 
Access to Credit          
Amount of Credit           250        271  500 500        650 434 
Received (‘00 Naira)             
% of Households with 08.5 12.4 15.4 11.5 09.4      11.4 
Increased Saving in                       
Past year 
% of Households with            05.6 15.6 21.6    2  3  . 5               25.4 18.34 
Forced Livelihood 
Source: Field Survey, 2007 
Notes: 1. Households were grouped in quintiles based on their ranking on the social capital 
index calculated at the average of all the six dimensions considered for this study.  
The asset index ranges from 0 to 3 and is based on a principal component analysis household 
ownership of durable goods. 
 
 
 
   
 
 99 
 
4.19: Households heads Income Model 
Table (21) shows the t-statistics as well as F statistics of the social capital 
index in the 2SLS equation. Also, several combinations of instruments were tested 
and all combinations lead to significant increase in R square in the first stage 
equation. 
Eight variables were significant. These include human capital endowment (9.610), 
household primary occupation (15.890), household farm size (2.510), household 
membership of professional association (16.630), membership of cooperative society 
(3.440), household location (4.280),  participation in community development 
activities (7.040) and participation in peace making activities (-1.782). The coefficient 
of household human capital endowment is .337 p< 0.1 meaning that a 10% increase in 
human capital would lead to  a .337 unit increase in social capital index while the 
coefficient of household primary occupation is 15.2 p<0.1 meaning that a 10% 
increase in household primary occupation would lead to .113 unit increase in social 
capital index. Similarly, the coefficient of household farm size is .802p<0.1 indicating 
that 10% increase in household farm size would lead to .802 unit increase in 
household social capital index while a 10% increase in household involvement in 
professional association would lead to 0.097 unit increase in social capital index.  
Furthermore, the coefficient of household membership of cooperative society 
is 0.731 p< 0.1 meaning that a 10% increase in household membership of cooperative 
society would yield a .731 increase in social capital index while the coefficient of 
household location is .669 meaning that the location of household matters as those in 
urban centres were found to have higher social capital index than those in rural areas. 
More importantly, the coefficient of household involvement in community 
development activities is 0.482 p <0.1 signifying that a 10% increase in household 
involvement in community development projects would lead to 0.482 unit increase in 
social capital index while the coefficient of participation in peace- making activities is 
.076 p<.001 meaning that a unit increase in household participation in peace- keeping 
would lead to .076 decrease in social capital index. 
 
 
 
 
 100 
 
Table 21: Household Income Model 
Variables Coefficients 
Intercept                          .923        (5.768***)  
Household‘s  per capita expenditure                          0.307       (-1.024*) 
Human capital endowment                                                                 0.337          (9.610***) 
Household‘s total asset                                                                       0.666        ( -0.432) 
Sex of household                                                                           0.850          (0.190) 
Marital status household head                                                            0.664        ( -0.434) 
Primary occupation of household                                                                         0 .113        (15.890***) 
Household size                                                                               0.282      ( -1.079*) 
 Household Farm size                                                                         0.802          (2.510**) 
 Household Membership of cooperative                                             0  . 7  3  1           (3.440***) 
Membership of professional association                                            0  . 0  9  7         ( 16.630**) 
Groups and Networks                          0.0178       (0.55) 
Trust and Solidarity                        0.0019        (0.76) 
Collective Action and Cooperation                        0.0001       (1.70*) 
Information and Communication                         0.0159       (1.87*) 
Social Cohesions and Inclusion                        1.0121        (1.103*) 
Empowerment and Political Action                        0.0421       (0.215) 
Density of Membership (%)                          0.0002        (-0.010) 
Heterogeneity Index (%)                             0.0159    (1.883*) 
Decision Making Index (%)                         0.267        ( -1.112*) 
Meeting Attendance Index (%)                           0.410      ( -0.826) 
Cash Contribution Index (%)                            -0.1629    (-0.102)  
Labour Contribution (%) 0.007 (1.782*) 
R2 .510 
Adjusted  R 0.4832 
F-statistics 12.300 
Notes: 1. Dependent variable = In (income per capita) 
           2. t-statistics are in parenthesis and are based on robust standard errors 
 *Significant at 10%, ** significant at 5%, *** Significant at 1% 
 Source : Field Survey, 2007  
 
 
 101 
 
4.20 Household Welfare and Social Capital: The Aggregate Model  
  Social capital has returns to the household that are similar in magnitude to 
those from human capital and it provides little guidance as to which aspect of social 
capital produces this result. It is also possible to consider that each social capital 
dimension acts independently, and that the effects are additive. The conceptual 
literature on social capital is not advanced to the stage that theoretical arguments can 
be put forth to select one approach over the other, hence the use of additive model. In 
this section we have attempted to get a step closer to the structural equation which 
underlies the reduced-form model of equation (1), by estimating the impact of social 
capital on variables portraying the ways in which social capital contributes to 
household welfare. We found that households with high social capital are better able 
to accumulate physical assets and savings and to obtain credit. This should help 
households cope better with the risk of income fluctuations. The number of 
memberships, trust and solidarity, social cohesion and inclusion, and active 
participation in decision- making were the key dimensions.  We suggest that different   
mechanisms are at work. The benefits to household welfare are primarily the result of 
exchanges in knowledge, which are maximized among association members of 
different economic backgrounds.    
 This section presents the impact of social capital on welfare within the 
context of the methodology proposed in the analytical framework. Both multiplicative 
and additive social capital indices are used to determine the impact of social capital on 
welfare proxied by per capita expenditure of households. The use of both 
multiplicative and additive social capital is hinged on the fact that to date, literature 
on conceptual and theoretical underpinnings of social capital has not proved the 
superiority of one over the other. Grootaert et al (2002), Narayan and Pritchett(1997), 
Grootaert (2001), Okunmadewa et al (2005) and Yusuf (2008) use both approaches 
and conclude that additive and multiplicative variables are valid approaches for 
introducing social capital in the household behavioural model. 
Table 22 presents the effect of social capital on household welfare. In the first 
column of the table is the basic model of household welfare behaviour. This model 
shows that about 26.00 percent of the variations in per capita expenditure of 
households are explained by the specified human capital and demographic factors. 
 102 
 
The larger household especially, those engaging in non-farming activities, and 
residing in rural areas significantly reduced the household welfare. 
In the second column of the table, the multiplicative social capital variable is 
introduced. The inclusion of this variable led to slight improvement in the adjusted 
R2. Along with the demographic variables, aggregate social capital index significantly 
influences the welfare status of households. At mean social capita index of 20.25, the 
coefficient of the variables shows that a one unit increase in social capital (4.18 
percent) would increase household per capita expenditure by 0.3134 percent. 
Including social capital increases the R-squared from 0.2613% to 0.3134% 
 The third column of Table 22 shows the dissagregation of female household 
members in the study area with the inclusion of nine additive social capital variables. 
The coefficient of the variables shows that a one unit increase in social capital (4.18 
percent) would increase female household per capita expenditure by 0.681 percent. 
   The variables include Groups and networks, Trust and solidarity, Collective 
action and cooperation, Information and communication, social cohesion and 
inclusion, empowerment and political action, household memberships in associations, 
index of participation in decision making, and membership of financial institutions. 
The disaggregation shows that the effects of social capital on welfare of female 
households are traceable to groups and networks (2.0), trust and solidarity(1.3%), 
collective action and cooperation(9.1%), information and communication(2.8%), 
social cohesion and inclusion(6.5%), household memberships in associations (4.8%), 
index of participation in decision making ( 2.5%), and membership of financial 
institutions (1.8%).  
 Conversely female household‘s attendance of meeting negatively affects their 
welfare as too much meeting attendance reduced welfare by 2.5%. Also, large 
household size dampens female household welfare as a unit increase in household size 
reduced female household welfare by 0.782%. In the same vein, a unit increase in age 
reduces female house hold welfare by 0.319%. However, a unit increase in years of 
formal education enhanced female household welfare by 0.913 5%.  Introduction of 
heterogeneity index in the new model has a better explanatory power as reflected in 
the adjusted R2 of 0.5821. Heterogeneity of associations can be source of information 
for improved welfare status as well as being a source of conflict between members of 
the associations  
 103 
 
 The fourth column indicates the effects of social capital dimensions on male 
households in the study area using ten additive social capital variables such as and 
networks, Trust and solidarity, Collective action and cooperation, Information and 
communication, social cohesion and inclusion, empowerment and political action, 
household memberships in associations, index of participation in decision- making, 
meeting attendance and membership of financial institutions. The coefficient of the 
variables shows that a one unit increase in social capital (4.18 percent) would increase 
male household per capita expenditure by 0.503%. The social capital variables that 
were significant include: Groups and networks (2.0%), Trust and solidarity (1.3%), 
Collective action and cooperation (9.1%), Information and communication (2.8%), 
social cohesion and inclusion (6.5%), empowerment and political action (9.1%), 
household memberships in associations (2.2%), meeting attendance (-2.5%) 
participation in decision making (2.5%), and membership of financial institutions 
(10.1%). Large household size also dampens male household welfare as a unit 
increase in household size reduced female household welfare by 0.782%. However, 
male participation in politics enhanced their welfare more than their female 
counterparts.  Similarly, a unit increase in years of formal education enhanced welfare 
of male households by 0.123%.  
The fifth column of Table 22 reveals the inclusion of nine additive social 
capital variables. These are: Groups and networks, Trust and solidarity, Collective 
action and cooperation, Information and communication, social cohesion and 
inclusion, empowerment and political action, household memberships in associations, 
index of participation in decision making, and membership of financial institutions. In 
this respect, heterogeneity of associations can be source of information for improved 
welfare stats as well as being a source of conflict between members of the 
associations. This new model has a better explanatory power as reflected in the 
adjusted R2 of 0.433. This disaggregation shows that the effects of social capital on 
welfare are positively related  to household involvement in group and network (8.1%), 
Trust and solidarity (2.2%), collective action and cooperation (2.6%), information and 
communication (5.2%), social cohesion and inclusion (4.2%) , empowerment and 
political action ()  membership of association (6.3%) decision making (0.026%) 
meeting attendance (-0.017%) and membership of financial institutions ( 7.6%). 
 104 
 
 In addition to the estimated effects from human and social capital 
endowments, the model results show that household welfare is also influenced 
strongly by the household‘s demographic characteristics and location. The column 
suggests that the benefits from participating in internally heterogeneous associations 
are higher than from associations whose members are more alike. The reasons for this 
may have to do with the exchanges of knowledge and information that occur among 
members. Members from different backgrounds may learn more from each other 
because they have different knowledge to start with. A further analysis of 
heterogeneity (by including each dimension as a separate regressor in the model) 
supported this conclusion: the economic dimensions of heterogeneity (occupation, 
economic status and education) matter the most. In other words, associations where 
members differ in economic attributes yield more benefits to their members than 
associations where members differ primarily in demographic attributes.  
Location also matters: benefits are greater if the association brings together 
people from different neighbourhoods. Differences in location and economic 
characteristics indeed maximize the chance that association members have different 
knowledge and hence maximize the potential gain from exchange. We argued that 
there are several ways in which social capital is truly ―social.‖ First, there are spill 
over effects from social interaction undertaken in one sphere (e.g. social, religion, 
cultural) into other spheres, leading to improved access to financial and other 
resources. 
 
 
 
 
 
 
 105 
 
Table 22: Gender and Social Capital. 
  
 Basic Multiplicative Additive 
Characteristics         Women1,2    Men1,2 Pooled 
Social Capital Dimensions      
            
Groups and networks           0. 0200 (4.03***) 0.1204 (1.17*)        0.0814 (3.21***) 
    
Trust and Solidarity            0.0136 (2.51***) 0.0610 (2.42**)         0.0218 (3.19***) 
    
Collective Action and Cooperation           0.0915 (0.93***) 0.0319 (1.25*)         0.0256 (3.51***) 
    
Information and Communication            0.0281 (2.74) 0.0812 (0.93)         0.0518 (4.13***) 
    
 Social cohesion and Inclusion            0.0649 (4.05***) 0.4183 (3.16**)         0.0417 (2.41**) 
   
Empowerment and Political Action           0.00091 (1.34*) 0.0719 (3.21**)         0.0016 (4.93***) 
   
Cash contribution index      
0.0027 (0.12) 
     0.0059 (1.26*) 0.0364  ( 3.17***)  
Labour contribution           0.0649 (4.05***) 0.4183 (3.16***)         0.0317 (2.41*) 
   
Density of Membership           0.048 (4.61***) 0.0216 (2.82***)         0.0625 (1.26*) 
    
Heterogeneous Index    0.0327(0.74) 0.0234(0.74) 0.0218(0.76) 
Meeting Attendance          - 0.0254 (0.96) -0.0245 (1.09*)        - 0.0017 (2.25**) 
   
 Participation in Decision Making          0.02581(3.21**) 0.2582 (2.16**)        00.0258 (0.93) 
   
 Membership in Financial Institution              0.0181 (2.94***) 0.1091 (2.63***)         0.0755 (5.14***) 
Household Size     -0.0638(7.16)    -0.0732  (9.16)       - 0.0782 (-1.06*) - 0.0781 (-1.41*)       -0.0782 (6.71***) 
Educational Status per Household Head       0.0285(5.41)      0.0152 (4.12)     0.913 (1.18*)  0.123 (2.97***)        0.681 (4.17***) 
Age of Household Head     -0.0013 (0.71)    0.00912 (0.95)        - 0.319 (1.30*)   0.225 (1.37*)       -0.0016 (1.18*) 
Age of Household Head Squared       0.0391 (4.01)      0.0417 (4.19)      -0.0017 (1.47*) -0.0317 (1.17*)        0.0081 (3.41**) 
Household Asset Score   -0.00273 (3.48)    -0.00126 (3.23)        0.0118 (3.31***)  0.0115 (1.90*)      -0.0031 (4.15***) 
Social Capital Index  .0052(4.18)       0.681          0.503       0.487 
Intercept 13.19(14.12) 15.35(23.11)       -2.9418 (8.682***)  -2.1103 (8.081***)     14.29 (45.19***) 
Adjusted R2  0.2613 0.3134       0.5821          0.4684       0.4332 
     
F-Statitic 28.11 32.7 26.45 24.78 25.16 
Source : Field Survey, 2007 
 106 
 
4.21 Social Capital and Household Welfare: Two-Way Causality? 
Following Grootaert (1999),  Okunmadewa et al (2005) and Yusuf (2008), 
social capital can be regarded as an input in the household‘s production function and 
can be modelled similar to human capital and other household asset endowments 
.According to them, like human capital, social capital can be, at least partly, 
consumption good. In consonance with this assumption, this study has tested for 
existence of two-way causality with the aid of instrumental variable. The instrument 
chosen is a multiplicative index of whether the members of the most important local 
level institutions that a household belongs to are of the same religion, culture or trust. 
The real challenge is to find a suitable instrument set for social capital and the 
instrument must determine social capital and not welfare (nor is to be determined by 
household welfare). Using the aggregate social capital model as indicated in Table 22, 
the original social capital index was replaced by the instrumental variable. The 
instrumental variables used for social capital are: 
(1) Ethnic and religious diversity in the study area which affects directly the 
potential heterogeneity of associations, a key component of aggregate social 
capital index. 
(2) The density and effectiveness of institutions in the study area. 
(3) The village‘s involvement in the procurement of social services and 
infrastructure, these include education, primary health, roads, boreholes, 
sanitation and other infrastructure. 
The choice of the instrument used for social capital is guided by available information 
and submissions by Grooteart(2001) and Grooteart et al (2002). In this context eight 
possible instruments were used; an index of ethnic and religious diversity, the number 
of existing associations in the study area, the percent of institutions that were 
effective, and indexes of community involvement in the provision of primary health, 
education services, deep wells, road maintenance and communications 
Table 23 shows the test-statistic‘s p-value as well as the coefficient and t- 
statistic of the social capital index in the 2SLS equation. Several combinations of 
instruments were tested and all combinations lead to significant increases in R-
squared in the first stage equation. 
.The instrumental variables method leads to higher coefficients (ranging from 0.0059 
to 0.0127) for the social capital index than in the OLS model (where it was 0.0052). 
 107 
 
This indicates that equation (1) is correctly specified and that social capital is an 
exogenous determinant of household welfare. If there were significant reverse 
causality, the coefficient of the social capital index in the 2SLS regression would have 
been lower than the OLS coefficient Grooteart (2001),Yusuf (2008) and Okumadewa 
et al (2005). The higher coefficient of the instrumented social capital index implies 
that a 1% increase in the household‘s social capital endowment leads to 0.41 percent 
increase in household expenditure per capita. The corresponding increase in 
household expenditure using OLS estimate for the social capital index is 0.31 percent  
 
Table 23: Social Capital and Household Welfare: Instrumental Variable Results 
Instrument Set          Social Capital Index  Incremental p-value 
Coefficient  t-statistics R-squared (Test) 
 1. Diversity, institutional effectiveness      0.0216    2.51**    0.041    0.41 
2. Diversity, institutional effectiveness,      
     institutional density      0.0059    3.17**     0.051    0.61 
3. Diversity, institutional effectiveness,     
community involvement in health, education,     
water supply, roads     0.0127    2.58**     0.41    0.64 
4. Diversity, institutional effectiveness,     
institutional density, community involvement in     
health, education, water supply, roads     0.0715    2.91**     0.058    0.67 
Source: Field Survey 2007 
 
    
 
 
  
 
 
 
 
 
 
 
 
 108 
 
4.22   Social Capital Effects on Asset Accumulation 
There are different reasons why households in the study area acquired social 
capital either by investing time and/ money in local associations. 13% of households 
cite that they joined the groups by birth, 21% cite mandatory membership as the 
prime reason while others voluntarily become members because of the direct impact 
on the household‘s livelihood, the impact on the community, and assistance in case of 
emergency (Grootaert, 2006).  
Being a mixture of rural and semi urban setting, a prime consideration for 
households is to build up coping strategies to deal with the risk of income 
fluctuations. This involves accumulating assets (which can be sold or borrowed 
against the time of need) or arranging access to credit. Out of a list of durable goods, 
the average household owned only 3.4 items. Most frequently owned were  houses, 
radio, motorcycle, and sprayer. Improving access to credit and savings is a major 
reason why households in the study area join local associations. 65% of all 
memberships are primarily for this purpose, with a stronger concentration in 
Atakumosa East, Oriade and Ilesha East local government areas of Osun State as well 
as Akoko North and Idanre Ifedore Local government areas of Ondo State which have 
tradition of rotating credit (ROSCA) saving associations. Many other groups have the 
provision of credit as a secondary objective.  
We re-estimated the equation with an asset score variable as dependent 
variable to see whether social capital is effective in contributing to asset 
accumulation. Since the data do not contain price information, this score was 
calculated using weights derived from a principal component analysis of the 15 
durable goods.  The results indicate that membership of financial institutions, 
belonging to internally heterogeneous associations and participating actively in them 
is linked with higher asset ownership.  The variables that were significant include 
groups and networks, trust and solidarity, collective action and cooperation, social 
cohesion and inclusion, number of membership, decision- making, household size, 
educational status of household head, age of household head and age of other 
members of the household while social capital plays a positive role in asset 
accumulation by the household, its importance relative to education is less than was 
the case for current expenditure. 
 109 
 
 The coefficient of group and network was significant at p< 0.005. A unit 
increase in group and network by household heads would lead to 0.0017% increase in 
asset accumulation. while the coefficient of trust and solidarity is 0.0023 p< 0.005 
indicating that a five percent increase in trust and solidarity by household heads 
would lead to 0.0023 unit increases in asset accumulation. In addition, Household size 
had 0.0025(p<0.05) which means that as the size of the household increases in 
number, assets accumulation increases at a very slow rate of 0.0025. This could be 
explained by the fact that available money would be spent on taking care of large 
family. The coefficient of age of household head is 0.0611 (p<0.5) meaning that as 
the age of household head increases, asset ownership would be high especially as 
number of years in local association increases. Furthermore, the coefficient of 
participation in decision- making is 0.0319(p<0.5) which indicated that asset 
accumulation by household head increases as the household head gets more involved 
in decision making (Grootaert, 2006) . However, the coefficient of meeting attendance 
is -0.0081 (p<0.05) which means that the opportunity cost of household‘s attendance 
of meetings is his inability to acquire more assets. 
 Membership of financial institution is insignificant in asset accumulation 
while male household heads tend to acquire more assets 0.0016 than their female 
counterparts 0.0072. This may be due to the fact that women naturally prefer to use 
their proceeds for the overall well-being and economic advancement of the family 
(Author 2008). 
 Another aspect of asset accumulation is the ability to have savings. The 
questionnaire did ask respondents about record of the amount of savings and whether 
households had been able to increase savings in the past year. It was revealed that 
households with more memberships in local associations were significantly more able 
to do so than others (Column 2, Table 24). The effect was especially strong from 
memberships in cooperative as well as credit and savings associations indicating that 
such organizations actually achieve their professed objective. The initial wealth 
position of the household also mattered, as richer households were significantly more 
likely to increase their savings. This underscores, of course, the importance of credit 
and savings associations for the poor.  
 
 
 110 
 
Table 24: Social Capital and Asset Accumulation  
1 2
Variables  Asset Ownership  Increasing Savings  
.Groups and networks         0.0017 (4.19***) 0.0041 (2.91**) 
Trust and Solidarity          0.0023 (2.51**)  0.0071 (0.49)  
Collective Action and Cooperation 0.0091 (5.13***) 0.0081 (3.18***) 
Information and Communication  0.0119 (1.41*) 0.0061 (4.18***) 
Social Cohesion and Inclusion  0.0028 (1.93*) 0.0061 (2.18**) 
Empowerment and Political Action. 0.0009 (0.96) 0.0009 (1.18*) 
Cash contribution index 0.0218(2.12**) 0.0058(1.44*) 
Labour contribution index  0.0025(1.14*) 0.0037(0.57) 
Heterogeneity index 0.0036(1.09*) 0.0562(0.34) 
Density of Membership         0.0083 (3.67***) 0.0010 (2.91**) 
Meeting Attendance        -0.0081 (0.72) -0.0047(1.27*) 
Participation in Decision Making 0.0319 (6.82***) 0.0091 (1.39*) 
 Membership in Financial Institution   - 0.0193 (3.18***) 
Household Size        0.0025 (3.89***) -0.0007 (0.94) 
Educational Status per Household Head        0.0072 (5.41***) 0.0085 (1.20*) 
Female Head of Household     0.0072 (1.11*)   0.0041 (0.62) 
Male Head of Household   0.0016 (1.18*)   0.0074 (0.91) 
Age of Household Head        0.0611 (2.15**) -0.0071 (1.29*) 
Age of Household Head Squared      -0.0914 (5.10***)  0.0031 (0.92) 
Household Asset Score                -  0.0031 (4.82***) 
Intercept     -01.29 (1.27)            - 
R-squared       0.42            - 
F-statistics     41.52            - 
Log Likelihood         -     -351.09 
Chi-squared         -      138.5 
Probability > Chi-squared         -           0.00 
Notes: 1. OLS model with asset score  as dependent variable;  
                  reported are coefficient and t-values based on robust standard errors. 
2. Probit model of households who increased savings in the past year; reported are 
        probability derivates at the mean of the explanatory variables (or for 0 to 1 change in 
        the case of dummy variables) and z-scores based on robust standard errors. 
Source: Field Survey, 2007  
 
 
  
 
 111 
 
4.23 Social Capital and Access to Credit  
Table 25 confirms the importance of financial associations for access to credit 
and amount received. Nine variables were significant; Trust and Solidarity(3.72), 
Collective action and Cooperation(2.05) Number of Memberships(2.36), Social 
Cohesion and Inclusion(3.81 ), Meeting attendance(3.02) Index of Participation in 
Decision Making( 3.63), Membership of Financial Institution(2.94), Age of 
Household head (2.81) and Age of Household squarer(3.18). 
The coefficient of Trust and Solidarity is 0.0925 (p<0.001) meaning that a 1% 
increase in trust and solidarity would lead to 0.93 unit increase in the amount 
received. This may be due to high premium placed on trust and solidarity by most 
local associations especially when the beneficiary is a member. In addition, the 
coefficient of Collective Action and Cooperation is 0.0315 (p<0.01) meaning that a 
10% increase in Collective Action and Cooperation would lead to 3.15 increase in 
amount received. The reason may be due to the fact that most financial institutions 
and government assistance are readily available to those belonging to cooperative 
societies.  
The coefficient of Social Cohesion and Inclusion is 0.0913 (p<0.001) which 
means that a 10% increase in Social Cohesion and Inclusion would lead to 9.13 
increase in amount received. This is because Social Cohesion and Inclusion promotes 
trust and cooperation needed to access credit by members of local associations. This 
proposition supports the allusions of Grootaert, (2006), Molyneux( 2002), Lawal and 
Shittu (2006) and Lawal( 2004). More importantly, the coefficient of index of 
participation in decision- making is 0.0518 (p<0.001) indicating that a 10% increase 
in decision making would lead to 5.18 1ncrease in amount received especially when 
one considers the social status of members in local associations while the coefficient 
of female household head is 0.0913(p<0.0010) which means that a 10% increase in 
membership in local association would lead to a 9.13 increase in loan accessibility by 
female members.   
However, Table 25 also makes it clear that membership and active participation in 
other local associations, whose prime objective is not financial, also contributes to 
access to credit. This is perhaps the sense in which social capital is truly ―social,‖ in 
that the building of networks and trust among members in the context of a social 
setting spills over into financial benefits, e.g. by easier access to credit. This 
 112 
 
interpretation of social capital has been proposed by several authors such as Putnam 
(1993), Dasgupta (1988) and Fukuyama (1995). Sharma and Zeller (1997) report that 
the number of self-help groups in communities in Bangladesh has a positive spillover 
effect on the performance of credit groups. Similar spillovers have been documented 
in other sectors as well.  
 
 113 
 
Table 25: Social Capital and Access to Credit  
Characteristics  Access to Credit  Ln (Amount of 
1
     (probit ) Credit Received) 
2
(tobit)  
Social Capital Dimensions   
Groups and networks   0.0107 (1.19*) 0.0415 (1.91*) 
Trust and Solidarity 0.0627 (3.07***) 0.0925 (3.72***) 
Collective Action and Cooperation 0.0913 (0.93) 0.0315 (2.05**) 
Information and Communication 0.0319 (0.74) 0.0510 (0.34) 
Social Cohesion and Inclusion 0.0915 (5.15***) 0.0913 (3.81***) 
Empowerment and Political Action. 0.0218 (1.04*) 0.0179 (1.08*) 
Membership in Financial Institution    0.1531 (3.18***) 2.1093 (2.94***) 
Household Size  0.0192 (1.16*)  0.0241 (1.14*) 
Educational Status per Household Head  -0.0316 (1.31*) -0.0611 (0.91) 
Female Head of Household  -0.0311 (0.71) 0.0913 (0.93) 
Male Head of Household  -0.0162 (1.04*) 0.0413 (0.72) 
Age of Household Head    0.0163 (1.05*)   0.0623 (2.81**) 
Age of Household Head Squared   -0.0319 (2.74**) 0.0031 (3.18***) 
Asset index      -0.0814 (0.39)  0.0914 (0.71) 
Density of Membership (%) 0.0109 (1.17*) 0.2019 (2.36**) 
Decision Making Index (%) 0.0180 (1.12*) 0.0518 (3.63***) 
Meeting Attendance Index (%) 0.0009 (0.61) 0.0031 (3.02) 
Labour Contribution Index (%) 0.02141(0.13) 0.01131(0.13) 
Cash Contribution Index (%) -0.0056(0.21) -0.0047(0.42) 
Heterogeneity Index (%) -0.0076(0.24) -0.0064(0.31) 
Farmers association 0.2315(2.01*) 0.3315(1.40*) 
Cooperative Societies 0.0241(0.11) 0.0351(0.21) 
ROSCAS 0.0032(0.03) 0.0088(0.47) 
Friends and families  -4.7501(-2.42) -3.5420(-1.25*) 
Local money lenders 0.0305(0.18**) 0.01273(0.28) 
Personal savings 0.0218(0.18) 0.0249(0.22) 
Banks 0.0158(0.27) 0.02312(0.34) 
Intercept                -  -2.3016 (0.61) 
Log Likelihood      -515.3   -1001.4 
Chi-squared        121      149.2 
Probability > Chi-squared         0.00        0.00 
Notes: 1. Probability derivatives at the mean of each explanatory variable (or for 0 to 1 change in the 
                 case of dummy variables) and z-scores based on robust standard errors 
2. Tobit coefficients and t-statistics        
Source: Field Survey, 2007  
 114 
 
 
 4.24   Social Capital and Collective Action  
Apart from contributing to asset accumulation and access to credit, social 
capital has also been documented to aid in collective action and collective decision 
making. This is especially relevant in rural settings where common property 
resources, such as construction and rehabilitation of access roads, environmental 
sanitation, sinking of deep wells, forestry or grazing land, need to be managed by a 
community (Narayan, 1995; Uphoff, 1992). This tradition manifests itself also in 
collective action often undertaken for the purpose of constructing or maintaining local 
infrastructure. 
We regressed the number of times per year households participated in 
collective action against the social capital variables and the usual control variables 
(Table 28). Four variables are significant; Social cohesion and inclusion (3.38), 
Number of Membership (2.36), Member of Financial Institutions (2.11) and Age of 
Household head (2 .93). The coefficient of Social Cohesion and inclusion is 0.3172 ( 
p<0.001% ) meaning that a one- percent increase in social cohesion would lead to 
3.172 increase in collective action, while the coefficient of number of membership is 
0.4100 (p<0.01) indicating that a ten percent increase in number of membership 
would lead to 0.4100 increase in collective action. The coefficients of member of 
financial institution is 1.0177 (p<0.01) signifying that a ten- percent increase in 
membership of financial institution would yield 2.18 increase in collective action 
while a one percent increase in age of household head would lead to 2.93 increase in 
collective action. Households who are members of more associations are more likely 
to participate in collective action. This attests again to the ―social‖ nature of social 
capital—networks and interactions engaged in as part of social, religious, financial, or 
other objectives spillover into higher participation in activities which benefit the 
community at large.  
The role of these socio- demographic factors is a noteworthy contrast with the 
role of the economic factors such as education, occupation and economic status which 
were the key contributing factors to increased household welfare. The benefits to 
household welfare come primarily from exchanges in knowledge, while the ability to 
organize collective action is more a function of trust and a shared perception of a 
common good.  
 115 
 
It is observed that households which provide in-kind contributions (i.e. 
through working) to their associations are more likely to participate in collective 
action (Grooteart 2006) .Another observation from the collective action regression is 
that wealthier households participate less in collective action.  Collective action is 
organized at the level of a community, and it is discovered that collective action 
regression using the village as unit of observation revealed that villages with a high 
density of associations are not necessarily better able to organize collective action 
while villages where there is a tradition of paying membership dues in kind are more 
successful in organizing collective action (Benu 2001). This finding strengthens the 
case for viewing social capital as an input in the household‘s production function. 
This in turn opens up the case for investing in social capital, just as investments are 
made in human capital. 
 
 116 
 
Table 26: Social Capital and Collective Action  
1
Characteristics                  Collective Action   
Household Level of Association 
 Groups and networks          0.1167 (1.08*) 0.0121 (1.01*) 
   
Trust and Solidarity         0.0549 (1.21*) 0.0114 (1.03*) 
  
Collective Action and Cooperation                          0.0115 (1.13*) 0.0115 (1.21*) 
  
 Information and Communication          0.0116 (1.25*)   0.1520 (0.89) 
  
Social Cohesion and Inclusion         0.1168 (3.08***) 0.3172 (3.38***) 
  
Empowerment and Political Action.          0.0413 (1.18*) 
         0.0117 (1.41*)  
 
Number of Memberships          0.4100 (2.36**) 
         0.0048 (3.07***)  
 
Meeting Attendance         -0.1173 (0.61) -1.0423 (1.10*) 
  
 Participation in Decision Making          0.9113 (1.21*)   0.0713 (0.63) 
  
  Membership in Financial Institution             1.1531 (2.18*) 1.0177 (2.11**) 
Household Size         0.5180 (1.09*)  2.0473 (1.52*) 
Educational Status  Household Head         0.0632 (1.52*) -0.0611 (0.42) 
Female Head of Household        -0.0511 (0.17)   3.0811 (0.97) 
Male Head of Household         0.0715 (1.18*) -0.0514 (1.43*) 
Age of Household Head         0.0923 (1.40*)   0.0991 (2.93**) 
Age of Household Head Squared        -0.0491 (2.49**) -0.0517 (0.26) 
Household Asset Score        -0.2190 (2.97**) -4.3016 (1.07) 
Intercept        -13.4290  -32.0917 (0.87) 
(1.82**) 
R-squared          0.27       0.54 
F-statistics        18.16       8.4 
Notes: 1. Dependent variable is the number of times household participated in collective action .During 
the last year. Reported are OLS coefficients and t-statistics based on robust Standard errors.        
Source: Field Survey, 2007  
 117 
 
CHAPTER FIVE 
 
5.0 SUMMARY, CONCLUSION AND POLICY RECOMMENDATIONS 
The study has examined the gender dimension of social capital and its effects on rural 
household welfare in Osun and Ondo states, Nigeria. Primary data were collected by 
means of structured questionnaire. The major findings and policy recommendations 
are summarized in this chapter. Also contained in this chapter is suggestion for further 
research. 
   
 5.1 MAJOR FINDINGS 
Socio-economic and Demographic Characteristics. 
The result of the descriptive statistics revealed that majority of the households 
(51.3%) are headed by males while 48.7% are headed by females. Most of the 
household heads sampled were still in the economically active age bracket as average 
age of male household heads is 44.10 years while that of female household heads is 
42.3 years. The average household size for male household heads is 6 while that of 
female is 5. For the educated ones, the educational attainment varies from primary 
(42.07%)  through secondary (24.39%) and post- secondary (29.27%) for male 
household heads while that of female decreased for primary (44.87%) through  
secondary (34.62%) and  post secondary (16.03%) levels. The main economic activity 
of the sampled household heads (79.23% for male) and (73.72% for female) is crop 
farming. Majority of household heads (24.39% male) and (22.44% female) cultivated 
between 2-5 hectares of land. The main source of credit for the sampled household 
heads (48.78% male) and (50% female) is through local level institutions.  
5.2 Dimensions of Social Capital and Welfare 
 The study examined on gender basis, contributions of social capital 
dimensions to welfare of household heads in the study area. Twelve dimensions of 
social capital were identified in the study area; these are groups and networks, trust 
and solidarity, collective action and cooperation, social cohesion and inclusion, 
information and communication and empowerment and political action, density of 
membership, meeting attendance, heterogeneity index, labour contribution, cash 
contribution, and participation in decision- making.  Average household head sampled 
in the study area belongs to at least three associations. Average meeting attendance by 
 118 
 
both sexes is two while density of membership in association is 30% for male 
household heads and 34% for female household heads. Also, male respondents 
participated in three out of five decisions taken while females participated in just two. 
Index of group and network is 73.2% for male household heads while it is 57.8% for 
female, while that of information and communication is 46.30% and 68.70% 
respectively.  
  The result indicated that male household heads were more in formal network 
of associations while female household heads were into informal local level 
associations. Index of empowerment and political action was 67.30% for male 
household heads while it was 21.00% for their female counterpart. The decision 
making index was 73.2% for male household heads and 57.8% for female. The 
average monthly cash contributions for male household heads was N895.67 and 
N985.67 for female while the average annual labour contribution was 2.4 mandays for 
male household heads and 3.2 mandays for female. The results indicate that 
membership of financial institutions, belonging to internally heterogeneous 
associations and participating actively in them is linked with higher asset ownership. 
Membership of financial institution is insignificant in asset accumulation 
while male household heads tend to acquire more assets than their female 
counterparts. This may be due to the fact that women naturally prefer to use their 
proceeds for the overall well-being and economic advancement of the family. 
Participation in decision- making activities leads to higher asset accumulation by both 
sexes. However, meeting attendance negatively affected household heads per capita 
expenditure which means that the opportunity cost of household‘s attendance of 
meetings is his inability to acquire more assets. 
   Household heads‘ involvement in trust and solidarity index leads to higher 
increase in the amount received from local level associations. This may be due to high 
premium placed on trust and solidarity by most local associations especially when the 
beneficiary is a member. In addition, the result indicated that Collective Action and 
Cooperation increased the amount of credit received by household heads in the study 
area. The reason may be due to the fact that services of most financial institutions and 
government assistance are readily available to those belonging to cooperative 
societies and other local level institutions especially the registered ones. The same 
applied to Social Cohesion and Inclusion which lead to significant increase in the 
 119 
 
amount received by household heads in the study area. This is because Social 
Cohesion and Inclusion promotes trust and cooperation needed to access credit by 
members of local associations, this proposition supports the allusions of Grootaert, 
(2006), Molyneux,( 2002), Lawal and Shittu, (2006) and Lawal ( 2004). More 
importantly, active participation in decision making activities lead to higher increase 
in the amount received especially when one considers the social status of members in 
local associations. 
With the use of actual social capital index, the explanatory variable is 0.682 
for female household heads and 0.511 for male household heads. There is also higher 
coefficient (0.0940) for female household heads and 0.0327 for male. This means that 
an increase in social capital by one unit would lead to 9.4 percent increase in female 
household per capita expenditure and 3.27 percent increase in male household per 
capita expenditure. 
More importantly, using one third of total income of 69,165.59 Naira as basis 
for determining the level of poverty, it was discovered that 52.52 percent of women 
were better off while 42.07 percent of the men were better off.   
The disaggregation of social capital into twelve dimensions indicates the level 
of diversity among members of local associations with meeting attendance having 
negative influence on the per capita expenditure of households. Meeting attendance led 
to 2.5% reduction in welfare for both sexes. In addition, a unit increase in the level of 
education of female household head would lead to 9.1% increase in her per capita 
expenditure while a unit increase in the level of education of male household head 
would lead to 1.2% increase in his per capital expenditure. In the same vein, a unit 
increase in women participation in decision making would lead to 8.1% rise in their 
households overall well-being while a unit increase in men‘s involvement in decision- 
making would lead to 7.1% increase in their households per capital expenditure.  The 
coefficient of household size is 0.0782 indicating that a unit increase in household 
size would reduce the welfare of both sexes by 7.8%  
  The relative importance of social capital is further understood by comparing 
the model with or without the social capital variables and it was discovered that R2 
increases from 0.26 to 0.31 meaning that social capital strongly influences household 
welfare. The basic data from the study area indicate that households with higher social 
capital are better off in terms of welfare using different dimensions of well-being. 
 120 
 
Social capital affects household welfare but the test of reverse causality using 
instrumental variables indicates that the effect of social capital on welfare dominates 
the reverse effect in explaining the correlation between the two variables. 
Using a reduced form model of households‘ welfare which controls for 
relevant household characteristics, the contributions of social capital to households‘ 
welfare was estimated and the result showed that a unit increase in social capital for a 
woman household head would lead to 0.94% increase in her welfare while a unit 
increase in a man household would lead to 0.33% increase in his welfare status. When 
household expenditure is related to the exogenous asset endowment of the household 
on gender basis, it was discovered that social capital enhances the welfare of women 
more easily than men especially when one considers the impact of social capital 
dimensions like groups and network, trust and solidarity, information and 
communication, social cohesion and inclusion, number of membership, participation 
in decision making and membership of financial institution. More importantly, the 
monthly average per capita expenditure of male household head in the study area was 
N2936.67 while it was N3221.82 for female household heads.  
It was discovered that female household heads spent more money on clothing 
and medical (N1345.68 and N695.34 respectively than their male counterparts while 
male household heads spent more on food and education of children.  
5.3  Conclusion 
  In this study, we have estimated, empirically, gender dimensions and the 
impact of social capital on household welfare in Osun and Ondo states, Nigeria. The 
focus was on households‘ memberships in local level institutions/associations—an 
aspect of social capital which is particularly relevant for households‘ day-to-day 
decisions are affecting their welfare. The basic data indicated a positive correlation 
between social capital and household welfare: households with high social capital 
have higher expenditure per capita, more assets, higher savings and better access to 
credit. 
 The magnitude of the social capital effect was found to be similar to the 
underlying structural equations that treat social capital as an input, together with 
human and physical capital, in the household‘s production function. The effects of 
social capital operate through (at least) three mechanisms: sharing of information 
among association members, reduction of opportunistic behaviour, and knowledge to 
 121 
 
be shared is larger and hence the potential benefit to members is higher. We found 
indeed that heterogeneity along dimensions such as education, occupation and 
economic status confers the greatest benefits .Social capital reduces the probability of 
being poor and the returns to household investment in social capital are higher  for 
female household heads than their male counterparts. This is especially the case for 
the number of memberships and households‘ active participation in decision making. 
This underscores the potential pay-off to female household heads investing more time 
in creating social capital by participating actively in local associations. Social capital 
is hypothesized to have several long-term benefits, such as better access to credit and 
a resulting better ability to smoothen out income fluctuations by borrowing and/or 
accumulating assets.  
Membership in associations whose primary role is financial (e.g. rotating 
credit and savings associations) has a strong positive effect. The findings support a 
policy by donors and governments to invest in social capital—either directly or by 
creating an environment friendly to the emergence of local associations. Our findings 
also indicate that investments in local social capital deserve to be part of poverty 
alleviation programs since the returns to investment in social capital are larger for 
female household heads than for male.  Our findings provide indications of the type of 
associations which are likely to impart the largest benefits (professional associations, 
religious associations, ethnic groups, and cooperative and thrift societies).  
5.3 Recommendations  
The findings of this study reveal that social capital and its dimensions have 
positive influence on per capita expenditure of rural households and also reduce the 
probability of being poor.  This is evident through household heads involvement in 
local level institutions like cooperative and thrift societies, professional associations, 
ethnic groups, religious groups and community development associations among 
others. Policies that enhance households‘ participation in social capital formations and 
their welfare are recommended.  
 Social capital enhances access to credit, savings, accumulation of assets and 
compliments human capital endowment in enhancing welfare and reducing 
poverty. Therefore, all policy initiated towards reducing rural poverty should 
involve social capital formations. 
 122 
 
 Based on the finding that mixed groups are an important type of organization 
where women‘s presence has greater effect when they participate in decision 
making, we would therefore recommend that attention should be exercised in 
forming and supporting mixed groups to ensure that women are given both a 
clear voice and decision- making power. 
 Since women have higher index of information and communications, 
government may increase the monitoring and enforcement of implementing 
agreements and contracts among women and their customers, while  
traditional and communal activities may be regularly organised to get them 
more involved in collective action and cooperation, trust and solidarity as 
well as empowerment and political action.  
 All tiers of government should accord priority to the formation of social 
networks since it has been a key instrument in undertaking social and 
productive projects, improving the living conditions and fighting social 
exclusion of households in the study area. The households that engaged in 
social capital are more successful especially in the area of assets 
accumulation, obtaining external resources and the development of more 
productive activities, because it enables those who possess it to obtain 
benefits that are unavailable to those who act individually or lack important 
connections.  
 Synergy must be established between social capital and government policy, 
whose task is to create local level institutions whose objectives are financial 
and social to facilitate active participation of male and female households in 
the associations while government policy on security and social 
transformation should involve social networks since social capital is a key 
factor for recovering from social, ethnic, religion and political problems. 
5.4   Contributions of the study to Knowledge   
Social capital components in the study area impacted positively on household welfare 
and enhanced asset accumulation, access to credit and savings, hence the need for 
rural households to engage in social capital formations to boost their agricultural 
productivities. 
 123 
 
Participation in local level associations and participation in collective action 
stimulates social capital formations thereby guarantee transfer of wealth, information 
and knowledge from the rich to the poor. 
The problem of income inequality, food and social insecurity could best be addressed 
through interactions generated from local level associations. 
5.5 Philosophy of the study 
Nigeria‘s social and development problems could be minimized through social capital 
at no cost to the government since members of these associations generate these 
among themselves; the resources could therefore be channelled to other 
developmental purposes.  
5.6 Suggestion for Further Research 
As identified throughout this study,   further work on estimating the influence 
of social capital on network base as well as the structural equations which portray the 
effects of social capital on access to credit or other inputs, and on group decision- 
making would further add to the case for treating social capital as genuine ―capital‖ in 
the household‘s production function. 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
      
 
 124 
 
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APPENDIX 
 
Table 1 Analyses of objectives  
 Objective Scope of the objective Data requirement Analytical Tools 
1 Identify various Gender To know households Associations, attendance Descriptive 
 dimensions of social involvement in social of meetings, records of statistics, 
capital in the study area. institutions and assess meetings, access to percentage, 
their social capital productive resources and composite 
formations input records e.t.c indicator. 
2 Estimate the influence of To know the impact of Age of households, Multiple regression 
 relevant socio-economic some socio economic educational status, 
variables on the social variables on various household‘s size, 
capital index, components of social primary occupation, farm 
capital size e.t.c 
3 Ascertain the effects of To determine the Components of social Aggregate Model 
social capital components influence of households‘ capital, welfare and Disaggregate 
and other factors on involvement in social indicators,  Model 
households welfare,. capital on their welfare 
4 determine  the effects of To verify the claim that Households‘ socio Tobit Regression 
social capital components social capital influences economic variables, analysis 
on assets accumulation, households‘ assets‘ financial institutions, 
accumulation household assets score 
and social capital 
components 
5 Examine the influence of To ascertain Households‘ socio Tobit Regression 
social capital components accessibility of economic variables, model 
on  access to  credit,  households to credit by financial institutions, 
 virtue of their household assets score 
involvement in network and social capital 
of associations components 
6 Quantify the effects of To the level of Households‘ socio- OLS regression 
social capital components households‘ involvement economic variables, model 
on collective action. in collective action social capital 
 activities especially in components, and 
communal activities collective action 
activities. 
 
 140 
 
UNIVERSITY OF IBADAN 
IBADAN 
Questionnaire on effect of Gender dimensions of Social Capital on rural household 
welfare in Ondo and Osun States. 
The questionnaire is purely meant for academic research.  Kindly ensure that the 
questions are faithfully answered to enable the researcher achieve the aims and 
objectives of the topic. 
1. Groups and Networks 
Which groups or organizations, networks, or associations do any of the 
members of your household belong?  These could be formal or just groups 
of people who get together regularly to do an activity. 
Types of Name of Code of Most How actively does 
Organisation or Organisation or Active Household this person 
Group Group Member participate in the 
group‘s decision 
making 
1= Leader 
2= Very Active 
3= Somewhat    
     Active 
4= Does not 
participate in 
decision making 
A. farmer    
Group or cooperative    
B. Traders or    
Business Association 
C. Professional    
Association (doctors, 
teachers Veterans) 
D Trade Union or    
Labour Union 
 141 
 
E.     
Neighborhood/village 
committee 
F. Religious or    
spiritual group (e.g. 
church, mmosque, 
temple, informal 
religious group, 
religious study 
group) 
G. Political groups or    
movement 
H.finance, credit or    
savings group 
I Education group    
(e.g parent-teacher 
association, school 
committee) 
J  NGO or civic    
group (e.g Rotary 
Club, Red Cross 
K  Ethnic-based    
community 
L Others groups    
 
 Compared to five years ago*, do members of your household participate in more 
or fewer groups or organizations? 
[*ENUMERATOR:  TIME PERIOD CAN BE CLARIFIED BY 
SITUATING IT BEFORE/AFTER MAJOR EVENT] 
1 More 
2 Same number 
3 Fewer 
 142 
 
 Of all the groups to which members of your household belong, which two are the 
most important to your household? 
[ENUMERATOR: WRITE DOWN NAMES OF GROUPS] 
Group 1 COOPERATIVE SOCIETY 
Group 2 Community Social Association 
 How many times in the past 12 months did anyone in this household participate in 
this group‘s activities, e.g. by attending meetings or doing group work? 
 
Group 1   Group 2 
 How does one become a member of this group? 
1 Born into the group 
2 Required to join 
3 Invited 
4 Voluntary choice 
5 Other (specify) 
Group 1   Group 2 
  
 How much money or goods did your household contribute to this group in the last 
12 months? 
 
Group 1   Group 2 
  
 How many days of work did your household give to this group in the past 12 
months? 
 
Group 1   Group 2 
 
  
 What is the main benefit from joining this group? 
      1. Improves my household‘s current livelihood or access to services. 
2. Important in times of emergency/in future 
3. Benefits the community 
4 Enjoyment/recreation 
 143 
 
5. Spiritual, Social status, self-esteem 
6. Other (specify)____________________________ 
 
Group 1   Group 2 
  
 Does the group help your household get access to any of the following services? 
1. Yes 
2. No 
          Group 1   Group 2 
A  Education or Training   
B  Health Services   
C  Water supply or sanitation   
D  Credit or Savings   
E  Agricultural input or technology   
F  Irrigation   
G  Other (specify)   
  
 Thinking about the members of this group, are most of them of the same….. 
1. Yes 
2. No 
     Group  1  Group 2 
A  Neighborhood/Village   
B  Family or Kin group   
C  Religion   
D  Gender   
E  Age   
F  Ethnic or linguistic   
group/race/caste/tribe 
 
 
 
 
 144 
 
 Do members mostly have the same…. 
1. Yes 
2. No 
     Group  1  Group 2 
A  Occupation   
B  Educational background or level   
 
 Are members mostly of the same political viewpoint or belong to the same 
political party? 
1. Yes 
2. No 
Group 1   Group 2 
 
Are some members richer or poorer than others, or do they all have mostly the same 
income level? 
1. Mostly same income level 
2. Mixed rich/poor 
 
Group 1   Group 2 
 
 In the past five years*, has membership in the group declined, remained the same, 
or increased? 
(*ENUMERATOR: TIME PERIOD CAN BE RIFIED BY 
SITUATING BEFORE/AFTER MAJOR EVENT) 
 1. Declined 
 2. Remained same 
 3. Increased 
 
Group 1   Group 2 
 
 
 
 
 145 
 
When there is a decision to be made in the group, how does this usually come about? 
1. Decision is imposed from outside 
2. The leader decides and informs the other group members 
3. The leader asks group members what they think and then 
decides. 
4. The group members hold a discussion and decide together 
5. Other (specify______________________________) 
    
Group 1   Group 2 
 
 How are leaders in this group selected? 
1. By an outside person or entity 
2. Each leader chooses his/her successor 
3. By a small group of members  
4. By decision/vote of all members 
5. Other (specify__________________________) 
Group 1   Group 2 
 
 Overall, how effective in this group‘s leadership? 
1. Very effective 
2. Somewhat effective 
3. Not effective 
Group 1   Group 2 
 
Does this group work or interact with other groups with similar goals in the 
village/neighborhood? 
1. No 
2. Yes, occasionally 
3. Yes, frequently 
Group 1   Group 2 
 
 
 146 
 
Does this group work or interact with other groups with similar goals outside the 
village/neighborhood? 
1. No 
2. Yes, occasionally 
3. Yes, frequently 
Group 1   Group 2 
 
Does this group work or interact with other groups with different goals in the 
village/neighborhood? 
1. No 
2. Yes, frequently 
Group 1   Group 2 
 
Does this group work or interact with other groups with different goals in the 
village/neighborhood? 
1. No 
2. Yes, frequently 
Group 1   Group 2 
 
 What is the most important source of funding of this group? 
1. From members‘ dues 
2. Other sources within the community 
3. Sources outside the community 
Group 1   Group 2 
 
What is the most important source of expertise or advice which this group receives? 
1. From within the membership 
2. From other sources within the community 
3. From sources outside the community 
Group 1   Group 2 
 
 
 
 147 
 
 Who originally founded the group? 
1. Central government 
2. Local Government 
3. Community members 
Group 1   Group 2 
 
Networks 
 About how many close friends do you have these days?  These are people you feel 
at ease with, can talk to about private matters, or call on for help. 
 
 
 If you suddenly needed a small amount of money (RURAL: enough to pay for 
expenses for your household for one week; URBAN: equal to about one week‘s 
wages), how many people beyond your immediate household could you turn to who 
would be willing to provide this money? 
1. No one 
2. One or two people 
3. Three or four people 
4. five or more people 
 (IF NOT ZERO) Of those people, how many do you think are currently able to 
provide this money? 
 
 
 IF NOT ZERO) Are most of these people of similar/higher/lower economic 
status? 
1. Similar  
2. Higher    
3. Lower   
 
 148 
 
If you suddenly had to go away for a day or two, could you count on your neighbors 
to take care of your children? 
1. Definitely 
2. Probably 
3. Probably not 
4. Definitely not 
 
If you suddenly faced a long-term emergency such as the death of breadwinner or 
(RURAL: harvest failure, URBAN: job loss), how many people beyond your 
immediate household could you turn to who would be willing to assist you? 
1. No one 
2. One or two people 
3. Three or four people 
4. Five or more people 
 
(IF NOT ZERO) Of those people, how many do you think are currently able to assist 
you? 
In the past 12 months, how many people with a personal problem have turned to you 
for assistance? 
(IF NOT ZERO) Are most of these people of similar/higher/lower economic status? 
1. Higher 
2. Lower 
2.  Trust and Solidarity 
In every community, some people get along with others and trust each other, 
while other people do not.  Now, I would like to talk to you about and solidarity in 
your community. 
2.1 Generally speaking, would you say that most people can be trusted, or that you 
can‘t be too carefully in your dealing with other people? 
1. Most people can be trusted 
2. You can‘t be too careful 
 
 
 
 149 
 
2.2  In general, do you agree or disagree with the following statements 
 1.  Agree strongly 
2.  Agree somewhat 
3.  Neither agree nor disagree 
4.  Disagree somewhat 
5.  Disagree strongly 
A.  Most people who live in this village/neighborhood  
can be trusted 
B.  In this village/neighborhood, one has to be alter or  
someone is likely to take advantage of you 
C.  Most people in this village/neighborhood are  
willing to help if you need 
D.  In this village/neighborhood, people generally Do  
not trust each other in mattes of lending and 
borrowing money. 
 
2.3   Now I want to ask you how much you trust different types of people.  On a scale of 1 to 5, 
where I means a very small extent and 5 means a very great extent, how much do you trust the 
people in that category? 
 1.  To a very small extent 
2.  To a small extent 
3.  Neither small nor great extent 
4.  To a great extent 
5.  To a very great extent 
A.  People from your ethnic or linguistic  
group/race/caste/tribe 
B.  People from other ethnic or linguistic  
groups/race/caste/tribe 
C. Shopkeepers  
D.  Local government officials.  
E.  Central government officials  
F.  Police  
G.  Teachers  
H.  Nurses and doctors  
I.  Strangers  
 
 150 
 
2.4   Do you think that over the last five years*, the level of trust in this village/neighborhood has 
gotten better, worse, or stayed about the same?  (*ENUMERATOR: TIME PERIOD CAN BE 
CLARIFIED BY SITUATION IT BEFORE/AFTER MAJOR EVENT) 
1. Gotten better 
2. Gotten worse 
3. Stayed about the same   
2.5   How well do people in your village/neighborhood help each other out these days?  Use a five 
point scale, where I means always helping and 5 means never helping. 
1. Always helping 
2. Helping most of the time 
3. Rarely helping 
4. Never helping 
 
 
2.6   If a community project does not directly benefit you, but has benefits for many others in the 
village/neighborhood, would you contribute time or money to the project? 
A. Time   B.  Money 
 
 1. Will not contribute time  1. Will not contribute money 
 2. Will contribute time   2. Will contribute money 
3. Collective Action and Cooperation 
3.1 In the past 12 months, have you worked with others in your village/neighborhood to do 
something for the benefit of the community? 
1. Yes    
 
3.2    What were the three main such activities in the past 12 months?  Was participation in these 
voluntary or required? 
Voluntary   Required 
   
   
   
 
3.3   All together, how many days in the past 12 months did you or anyone else in your household 
participates in community activities? 
   
 
 
 
 
 151 
 
3.4   How likely is it that people who do not participate in community activities will be criticized 
or sanctioned? 
1. Very likely 
2. Somewhat likely 
3. Neither likely nor unlikely 
4. Very unlikely 
3.5   What proportion of people in this village/neighborhood contribute time or money toward 
common development goals, such as (RURAL:  building a levy or repairing a road;  URBAN: 
repairing a road or maintaining a community center)? 
1. Everyone 
2. More than half 
3. About half 
4. Less than half 
5. No one 
   
3.6  If there was a water supply problem in this community, how likely is it that people will 
cooperate to try to solve the problem. 
1. Somewhat likely 
2. Neither likely or unlikely 
3. Somewhat unlikely 
4. Very unlikely 
 
3.7   Suppose something unfortunate happened to someone in the village/neighborhood, such as a 
serious illness, or the death of a parent.  How likely is it that some people in the community 
would get together to help them? 
1.  Very likely 
2.  Somewhat likely 
3.  Neither likely or unlikely 
4. Somewhat unlikely 
5. Every unlikely 
4.  Information and Communication 
4.1  How long does it take you to reach the nearest working post office? 
1.  Less than 15 minutes 
2. 31-60 minutes 
3.  More than one hour 
4.2 How many times in the last month have you or anyone in your household read a newspaper or 
had one read to you? 
 152 
 
 
4.3  How often do you listen to the radio? 
1. Every day 
2.  A few times a week 
3.  Once a week 
4.  Less than once a week 
5.  Never 
4.4  How often do you watch television? 
1.  Everyday 
2.  Once a week 
3.  Less than once a week 
4.  Never 
4.5  How long does it take you to get to the nearest working telephone? 
1.  Telephone in the house 
2.  Less than 15 minutes 
3.  31-60 minutes 
4.  More than 1 hour 
In the past month, how many times have you made or received a phone call? 
What are the three most important sources of information about what the government is doing (such as 
agricultural extension, workfare, family planning, etc.)? 
1. Relatives, friends and neighbors 
2. Community bulletin board 
3. Local market 
4. Community or local newspaper 
5. National newspaper 
6. Groups or association 
7. Business or work associates 
8. Political associates 
9. An agent of the government 
10. NGOs 
11. Internet 
 
 153 
 
What are the three most important sources of market information (such as jobs, prices of goods or 
crops)? 
1. Community bulletin board 
2. Local market 
3. Community or local newspaper 
4. National newspaper 
5. Groups or association 
6. Radio 
7. Television 
8. Group or Association 
9. Business or work associates 
10. An agent of the government 
11. NGOs 
12. Internet 
 In general, compared  to five years ago*,  has access to information improved, deteriorated, or 
stayed about the same? 
 
(ENUMERATOR: TIME PERIOD CAN BE CLARIFIED BY SITUATION IT BEFORE/AFTER 
MAJOR EVENT) 
1. Improved 
2. Deteriorated 
3. Stayed about the same 
     What part of the year is your easily accessible by road? 
1. All year long 
2. Never easily accessible 
   How many times have you traveled to (RURAL: a neighborhood village or town; URBAN: 
another part of the city) in the past 12 months. 
5. Social cohesion and Inclusion 
 How  strong is the feeling of togetherness or closeness in your village/neighborhood? 
Use a five point scale where I means feeling very distant and 5 means feeling very close. 
1. Very distant 
2. Neither distant nor close 
3. somewhat close 
4. Very close 
There are often differences in characteristics between people living in the same village/neighborhood.  
for example, differences in wealth, income, social status, ethnic background, race, caste, or tribe.  
There can also be differences in religious or political beliefs, or there can be differences due to age or 
sex.  To what extent do any such differences characterize your village/neighborhood?  Use a five point 
scale where I mean to a very great extent and 5 means to a very small extent. 
 154 
 
1. To a very great extent 
2. To a great extent 
3. Neither great nor small extent 
4. To a small extent 
5. To a very small extent. 
   Do any of these differences cause problems? 
1. Yes 
2. No  go to question 5.6 
  Which two differences most often cause problems? 
1. Differences in education 
2. Differences in landholding 
3. Differences between men and women 
4. Differences between younger and older generations 
5. Differences between long-term and recent residents 
6. Differences in political party affiliations 
7. Differences in religious beliefs 
8. Other differences 
 Have these problems ever led to violence? 
1. Yes 
2. No  
Are there groups of people in the village/neighborhood who are prevented from or do not have access 
to any of the following? 
 
 1.  Yes  How many are excluded? 
2.  No     1  Only a few people 
              2  Many people, but less than half of the           
                  village/neighborhood 
             3    More than half the  
                   village/neighborhood      
A.  Education/schools   
B   Health services/clinics  
C. Water  
D  Justice  
E   Transportation  
 
 
 
 155 
 
 Are there any community activities in which you are not allowed to participate? 
1. Yes 
2. No, I can participate in all 
Activities skip to question 5.10 
 In which activities are you not allowed to participate? 
(ENUMERATOR: LIST UP TO 3 ACTIVITIES) 
 
 
 
 
 Why are you not allowed to participate? 
(ENUMERATOR: LIST UP TO 3 ACTIVITIES) 
1. Poverty 
2. Occupation 
3. Lack of education 
4. Gender 
5. Age 
6. Religion 
7. Political affiliation 
8. Ethnicity or language spoken/race/caste/tribe 
9. Other (specify_____________________________) 
Sociability 
I am now going to ask a few questions about your everyday social interactions. 
 In the last one month, how many times have you met with people in a public place either to talk or 
to have food or drinks? 
 
In the last month, how many times have people visited you in your   home? 
 In the last month, how many times have you visited people in their home? 
  
 Were the people you met and visited with mostly…………….. 
 
A.   Of different ethnic or linguistic group/race/caste/tribe 
B.   Of different economic status 
C.   Of different social status 
D.   Of different religious group 
 
 
 
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In the last three months, how many times have you gotten together with people to play games, sports, 
or other recreational activities? 
 
How many times in the past 12 months did you participate in family/village/neighborhood festival or 
ceremony (wedding, funeral, religious festival, etc.)? 
 
Conflict and violence 
 In your opinion, is this village/neighborhood generally peaceful or marked by violence? 
1. Very peaceful 
2. Neither peaceful nor violent 
3. Moderately violent 
4. Very violent 
Compared to five years ago*, has the level of violence in this village/neighborhood increased, 
decreased, or stayed the same? 
1. Increased a lot 
2. Stayed about the same 
3. Deceased a little 
4. Decreased a lot 
 In general, how safe from crime and violence do you feel when you are alone at home? 
1. Very safe 
2. Neither safe nor unsafe 
3. Moderately unsafe 
4. Very unsafe 
 How safe do you feel when walking down your street alone after dark? 
1. Very safe 
2. Moderately safe 
3. Neither safe nor unsafe 
4. Very unsafe 
 In the past 12 months, have you or anyone in your household been the victim of a violent crime, 
such as assault or mugging? 
1. Yes  
2. No    go to question 5.22 
 How many times? 
 In the past 12 months, has your house been burglarized or vandalized? 
1. Yes 
2. No   go to question 6.1 
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6. Empowerment and Political Action 
 In general, how happy do you consider yourself to be? 
1. Very happy 
2. Neither happy nor unhappy 
3. Moderately unhappy 
4. Very unhappy 
How much control do you feel you have in making decisions that affect your everyday activities?  Do 
you have…… 
1. No control 
2. Control over some very few decisions 
3. Control over most decisions 
4. Control over all decisions 
 Do you feel that you have the power to make important decisions that change the course of your 
life?  Rate yourself on a 1 to 5 scale, where I means being totally unable to change your life, and five 
means having full control over your life. 
1. Totally unable to change life 
2. Mostly unable to change life 
3. Neither able nor unable 
4. Totally able to change life 
 Overall, how much impact do you think you have in making this village/neighborhood a better 
place to live? 
1. A small impact 
2. No impact 
 In the past 12 months, how often have people in this village/neighborhood gotten together to 
jointly petition government officials or political leaders for something benefiting the community? 
1. Never        skip to question 6.7 
2.  Once 
3. Many times (>5) 
 Were any of these petitions successfully? 
1. Yes, all were successful 
2. Most were unsuccessful 
3. None were successful 
 158 
 
 In the pat 12 months, have you done any of the following? 
 1    Yes 
2     No 
A. Attend a village/neighborhood council meeting, public hearing, or  
public discussion group 
 
B. Met with a politician, called him/her, or sent a letter  
C. Participated in a protest or demonstration 
D. Participated in an information or election campaign  
E. Alerted newspaper, radio or TV to a local problem  
F. Notified police or court about a local problem  
 
 Lots of people find it difficult to get out and vote.  Did you vote in the last local election? 
1. Yes/ No 
 
 Did you vote in the last state/national/presidential election? 
1. Yes/ No 
 Would you ever vote for a candidate who was not from you ethnic or linguistic 
group/race/caste/tribe? 
1. Yes/ No 
 To what extent do local government and local leaders take into account concerns voiced by you 
and people like you when they make decisions that affect you? 
1. A lot 
2. Not at all 
 In your opinion, how honest are the officials and staff of the following agencies?  Please rate them  
 on a 1 to 5 scale, where I is very dishonest and 5 is very honest? 
 1. Very dishonest 
2. Mostly dishonest 
3. Neither honest nor dishonest 
4. Mostly honest 
5. Very honest 
6. Not applicable (agency not in 
village/neighborhood) 
 7. Very dishonest 
8. Mostly dishonest 
9. Neither honest nor dishonest 
10. Mostly honest 
11. Very honest 
 159 
 
12. Not applicable (agency not in 
village/neighborhood) 
A.  Local government officials  
B   Traditional village leaders  
C.  Doctors and nurses in health clinic  
D.  Teachers and school officials  
E.  Staff of post office  
F.  Police  
G.  Judges and staff of courts  
H.  Staff of NGOs  
 In general, compared to five ago* has the honest of local government improved, 
deteriorated, or stayed about the same? 
(*ENUMERATOR: TIME PERIOD CAN BE CLARIFIED BY SITUATION IT 
BEFORE/AFTER MAJOR EVENT) 
 1. Improved  
 2. Stayed about the same 
 In the past 12 months, did your household have to pay some additional money to 
government officials to get things done? 
1. Yes, occasionally 
2. No    end interview 
 Are such payments effective in getting a service delivered or a problem solved? 
1. Yes, usually 
2. Yes, but only occasionally 
 
7.0 INCOME GENERATION ACTIVITIES 
7.1  Kindly indicate income generating activities you are into?  (You can  
               check more than one). 
(a) Crop farming 
(b) Livestock 
(c) Fish farming 
(d) Trading in manufactured goods 
(e) Artisans 
(f) Others please indicate; 
 160 
 
7.2 Which of the above is being considered as the primary livelihood? 
Please tick 
(a)  Crop farming 
(b)  Livestock 
(c)  Fish farming 
(d)   Trading in manufactured goods 
(e)   Artisans 
(f)    Others please indicate; 
7.3   Why do you consider the choice as your primary livelihood? 
(a)   Receive more income than the others 
(b)   Readily available 
©   Tradition 
(d)   Have no choice 
(e)   Others, please indicate 
------------------------------------------------------------ 
7.4   Kindly give the items used for production of the chosen income generating 
activities. 
7.5   Kindly give the production cost amount spend in the last twelve months on 
the items. 
 Amount N 
7.6 In the last twelve (12) months, how did you dispose off your harvested 
products? 
(a)  Farm gate  (b) Local markets  (c)  Major markets 
(d)  State markets  (e) Export  (f)   Others 
 (please indicate) 
7.7 How did you sell your products? 
(a)   In baskets (b) Kilogram  (c) Others please indicate. 
7.8 Give a rough estimate of basket or kilogram of your harvested products 
disposed off in the last twelve months. 
7.9 How much did you dispose a unit basket or kilogram__________N 
7.10 Can you give an estimate of the one you took home for consumption? 
________________ 
7.11 Did you give any to family, relatives, or friends? 
 161 
 
7.12 If yes, give the estimate of the one given to family, relatives or friends. 
7.13 Did you reserve any of this for future productivity?  ____________ 
Yes/No 
If yes! give an estimate  __________________ Yes/No  
Did you experience any waste? If yes, give an estimate of the waste.  N 
___________ 
7.14 What are the major sources of financing your enterprises or household‘s 
needs?(1) Banks /  / 
(ii) Cooperatives (iii) Professional Associations (iv) Local Lenders (v) Personal 
Savings (vi) Friends and Relatives (vii) Others (Specify)………        
 7.15 Rank the sources of credit in order of importance 
1st………2nd……..3rd……..4th……. 
7.16 Give information on the credit received from any of the sources in the last one year as 
shown below.   
Source of Need for Amount Amounted Interest Time lag Proportion Pay back Distance 
credit which requested Granted N charged % between of loan period between 
credit was from per year request & paid as at (year) place and 
sought credit (if any) granting due % the credit 
source N of loan source 
(week) (KM) 
         
         
         
         
         
         
         
 
 
 
 
 
 
 
 
 
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7.17 What is the mode of repayment of loan? Weekly /  / Monthly /  / Annually /  / 
7.18 Amount paid to penalty for loan repayment default in Naira ………. 
7.19 What type of housing unit is this? Room and parlour /  / Flat /  / Duplex /  / Single 
room /  / Hut /  / Other /  / 
7.20 What is the quality of construction of the house? Block+Zinc roof ?  / Mud+Zinc 
roof  /  / Mud+thatch room /  /others /  / 
7.21 Is the wall of the house plastered yes /  /No /  / 
7.22 What type of toilet facilities do you have in your house? Flush /  / Pt /  / 
Bucket/pail/  / Bush/ bare ground /  / others /  / 
7.23 What is the source of your drinking water? Tap /  / Bore hole /  /Well /  / 
Stream/River /  /Others /  / Specify…….. 
7.24 What is the source of your lighting in your house at night? Electricity /  / Kerosene 
Lantern /  / Candle/ wick lamp /  / Others (Specify)…… 
7.25 What do you use for cooking? Gas cooker /  / kerosene stove /  / Fire wood /  / Coal 
/  / Others (Specify)……… 
7.26 Which of the following assets does your household possess? Buildings /  / Farm 
Land /  / Vehicle(s) /  / Motor cycle /  / Radio /  / Television /  / Others specify…….  
 
7.27 How Much in Naira does your household spend on the following item? 
 
 Amount Spent in Naira (N) 
Items 
 Daily Weekly Monthly Total 
Food      
      
Clothing 
Medical      
Education      
Fuel and      
Light 
Transport      
Remittance      
Rent      
Toiletries      
Others      
Total      
 
 
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