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Item SPATIAL CONCENTRATION OF POVERTY AND ITS DETERMINANTS IN NIGERIA(2013-08) SOWUNMI, FATAI ABIOLAPoverty reduction programmes in Nigeria have not had significant intended effects. This can be attributed to the non-consideration of the heterogeneous nature of poverty and spatial contiguity of geographical units in their designs. There is scarce information on spatial decomposition and spillover of poverty across the Senatorial Districts (SD) in Nigeria. Therefore, the spatial concentration of poverty and its determinants were investigated. The study employed secondary data from Nigeria Living Standard Survey (NLSS) and Core Welfare Indicators Questionnaire (CWIQ) survey conducted by National Bureau of Statistics (NBS), Independent National Electoral Commission (INEC) and Food and Agriculture Organization (FAO). The NLSS and CWIQ were conducted in 2004 and 2006 respectively. The national sample sizes for NLSS and CWIQ were 22,200 and 77,400 household units respectively. Following the elimination of households with missing values, samples considered for the study were 18,760 and 54,536 households for NLSS and CWIQ respectively. The Poverty Rate (PR) per SD was obtained from household consumption expenditure data sourced from NLSS. Data on Household Size (HS), Household Membership of Association (HMA), Households’ Access to Health Facilities (AHF), People Employed in Agriculture (PEA), Access to Credit Facilities (ACF) and Literate Adult (LA) were obtained from CWIQ. Data on Number of Years Spent in the National Assembly by Senators (NYSNAS) (1999 – 2004) and soil fertility classification of Nigeria were sourced from INEC and FAO respectively. These variables and spatial dimension were hypothesized to influence PR. Data were analysed using descriptive statistics, Foster Greer and Thorbeck model, spatial regression, local indicator of spatial association and spatial probit at p = 0.05. Mean annual household per capita consumption expenditure was N28475.01 ± N11967.5. Percentage of PEA in the SD was 44.2 ± 18.4% while mean HS was 6.5 ± 1.5. Mean values of NYSNAS, ACF and AHF were 4.3 ± 0.5years, 10.5 ± 7.4% and 51.6 ± 18.2% respectively. Fifty-six percent of the SD had fertile soils. Average national PR of the SD was 56.03 ± 24.1%. Fifty three of the SD had PR below the national average. The Moran’s I value (3.4) indicated that spillover of poverty existed among SD. Ten percent increase in PR in one SD resulted in 3.1% increase in PR in the neighbouring SD ( = 0.3). Fifty-two percent of the SD with significant spatial association had low PR neighboured by low PR SD, 41.03% of the SD with high PR were neighboured by high PR SD. The PR in high-high SD was significantly reduced by HMA (-0.9), AHF (-0.3), ACF (-0.9), LA (-1.1), fertile soil (-5.2) and NYSNAS (-6.6). Poverty rate was significantly increased by PEA (0.4) UNIVERSITY OF IBADAN LIBRARY iv and HS (5.5). Mean PR in high-high and low-low SD was 82.6% and 31.8% respectively. Household’s probability of being poor was higher in high-high SD (0.8) compared to low-low (0.08). Poverty incidence in a senatorial district influenced the neighbouring senatorial district. Reduction in poverty incidence would be achieved through households’ membership of associations, improved access to health and credit facilities. Keywords: Spatial concentration, Poverty rate, Spatial probit, Senatorial district Word count: 491Item UNIVERSITY OF IBADAN LIBRARY COMPETITIVENESS OF COCOA VALUE CHAIN IN SOUTHERN NIGERIA(2016-10) OLUYOLE, KAYODE AKANNICocoa contributes immensely to Nigeria’s export earnings but it has low domestic value addition. In order to improve this, there is a need to ascertain the competitiveness along cocoa value chain. However, there’s a dearth of information on the competitiveness at each stage of cocoa value chain. The competitiveness of cocoa along the value chain in Southern Nigeria was therefore investigated. Using three-stage sampling procedure, six cocoa producing Local Government Areas (LGAs) were purposively selected from Oyo, Ondo and Cross River states in Southern Nigeria using two LGAs per state. In each LGA, two cocoa producing communities were randomly selected. A total of 250 cocoa farmers and 102 cocoa marketers were randomly selected from the twelve communities proportionate to the number of cocoa farmers and cocoa marketers in each community. Fifty-four cocoa processors were randomly selected from the study area. Structured questionnaire was used to collect data on the participants’ socio-economic characteristics, input and output prices at each stage (production, marketing and processing) of cocoa value chain. At production stage, there are Sharecropped Farmers (SF), Self-Owned Farmers (SOF) and Leased/Rented Farmers (LRF); at marketing stage, there are exporters, Licensed Buying Agents (LiBA) and Local Buying Agents (LoBA), while at processing stage there are Cocoa Butter Processors (CBP), Cocoa Powder Processors (CPP) and Black Soap Processors (BSP). Data were analysed using descriptive statistics, policy analysis matrix and partial equilibrium analysis at α0.05. The working experience of cocoa producers, cocoa marketers and cocoa processors were 23.5±14.1, 18.3±8.3 and 9.2±9.2 years, respectively. At the production stage, SF, SOF and LRF had Private Profit (PP) of ₦468 729.76/ha, ₦397 465.03/ha and ₦331 465.03/ha, respectively while Private Cost Ratio (PCR) were 0.22, 0.24 and 0.25, respectively. The SF, SOF and LRF had Social Profit (SP) of ₦792 038.37, ₦536 178.10 and ₦468 729.76, respectively. Also, SF, SOF and LRF had Nominal Protection Coefficient (NPC) of 0.75, 0.85 and 0.79, respectively. At the marketing stage, exporters, LiBA and LoBA had PP and PCR of ₦43 018.01/tonne, ₦36 104.98/tonne, ₦24 279.81/tonne and 0.18, 0.27, 0.40, respectively. Exporters had the highest SP of ₦51 159.04/tonne while exporters, LiBA and LoBA had NPC of 0.98, 0.94 and 0.90, respectively. At the processing stage, CBP, CPP and BSP had PP and PCR of ₦730 229.77/tonne, ₦309 708.13/tonne, ₦92 262.26/tonne and 0.02, 0.05 and 0.27, respectively. The CBP had the highest SP of ₦814 273.32/tonne and lowest Domestic Resource Cost of 0.02. The NPC of 0.95, 0.94 and 0.79 for CBP, UNIVERSITY OF IBADAN LIBRARY iv CPP and BSP, respectively showed lack of fiscal policies’ protection on cocoa processing. Welfare loss of producers was ₦429 432.36/tonne, while consumers’ gain was ₦123 492.22/tonne in the value chain. Competitiveness and comparative advantage along the stages of cocoa value chain exist in Southern Nigeria. The most competitive stage is cocoa processing. Cocoa production, marketing and processing were profitable to cocoa stakeholders in the study area. It is recommended that input use efficiency technologies should be introduced to maintain the competitiveness along the entire cocoa value chain. Keywords: Cocoa value chain, Social cost benefit, Comparative advantage, Effective protection coefficient. Word count: 497Item Multi-dimensional poverty estimates for fishing households in the south-western zone of Nigeria(2013) Ologbon' A. O. C.Using the traditional income-expenditure approach, coastal households have been adjudged to be poorer than their non-coastal counterparts. Poverty encompasses deprivation in other welfare dimensions such as education, health, housing, household assets, potable water and social participation. However, only few studies have conceptualised poverty with these various dimensions in focus. Hence, the nature and determinants of multi-dimensional poverty among fishing households in southwestern Nigeria were investigated. A multi-stage sampling procedure was adopted in collecting data from fishing households using structured questionnaire. Three coastal states (Ogun, Ondo and Lagos) were selected at the first stage. The three Local Government Areas (LGAs) with coastal characteristics were selected in Ogun and Ondo states while in Lagos state, three of such LGAs were randomly selected at the second stage. Subsequently, 100 coastal communities and 500 fishing households were selected based on probability proportionate to size. Data were obtained on socio-demographic characteristics and thirteen poverty dimensional variables including household expenditure, assets, housing quality, sources of drinking water and lighting, types of cooking fuel, waste disposal methods, and participation in grassroot politics and community development projects. Data were analysed using descriptive statistics, multiple correspondence analysis, Alkire-Foster counting and dimension-adjusted poverty measure and logit regression at p = 0.05. Mean age and year of schooling of household heads were 46.0 ± 10.9 and 9.0 ± 4.0 years respectively. Household size and dependency ratio were 5.0 ± 3.0 persons and 0.4 ± 0.4, respectively. Majority (72.1%) of the households were male-headed with 33.7% of houses built onshore. Thirty seven percent (37%) of the houses were built with planks and bamboo with 47.5% of the households defecating directly into the river. Daily mean per capita household income was N1237.20 ± 776.60. Most households (97.5%) had no access to potable water and 60.0% lacked essential household assets. A multi-dimensional poverty cut-off value of 8 was obtained out of a possible 13 welfare indicators that had direct effect on the welfare status of the households. Poverty headcount ratio was 0.6 while the dimension-adjusted poverty incidence, depth and severity were 34.2%, 16.0% and 7.6% respectively. Large-sized households (> 12 members) had higher Poverty Incidence (PI) (0.5938) than small-sized households (< 6 members) with PI of 0.3326, while households with tertiary education had lower PI (0.3351) than those without formal education (0.3781). Households with higher dependency ratio of 0.60 had higher PI of 0.4196 than those with lower dependency ratio of 0.10 having PI of 0.3326. Being fully engaged in onshore economic activities (0.13), using dugout canoes (0.11), and having house located onshores (3.13) increased the probability of households’ multi-dimensional poverty while high educational attainment (- 0.005), income (- 0.14) and land size (- 0.11) reduced it. Multi-dimensional poverty was high among the fishing households. Inadequate education, insufficient income, use of dugout canoes and living onshore increased multidimensional poverty incidence among the households. Reduction in the poverty incidence of households would be achieved through improved access to formal education and use of motorised canoes.Item Impact of Agricultural Production on Rural Welfare in Nigeria(2012) Olayide, O. EIncrease in agricultural production is essential for agricultural development since it enhances profitability and income which leads to welfare improvements. In Nigeria agricultural production and rural welfare have worsened over the years. Adequate information on the link between agricultural production and rural welfare in Nigeria is expected to better inform policy makers on implementation. Agricultural production and its impact on rural welfare in Nigeria were, therefore, investigated. Secondary data covering the military period (1970-1979 and 1984–1999) and democratic (1980–1983 and 1999-2007) periods were used for the study. The pre-Millennium Development Goals - MDGs (1970– 1999) and MDGs (2000–2007) periods also fall within the study period (1970 – 2007). The government regimes (military and democratic) as well as the pre-MDGs and MDGs periods captured the various policies implemented. Data were obtained from the National Bureau of Statistics (NBS), Central Bank of Nigeria and the Food and Agriculture Organization. Data were extracted on agricultural inputs and production, Agricultural Gross Domestic Product (AGDP), foreign private investments in agriculture, agricultural budgets as well as infrastructural and industrial development indices. These were analysed against extant policy regime at the periods of data collection. Rural welfare was proxied by real AGDP per capita. Data were analysed using descriptive statistics, stochastic frontier function and generalized method of moments at p = 0.05. Irrigated area as a percentage of arable land was highest in the MDGs period (0.90±0.03) and lowest during the pre-MDGs period (0.74±0.04). Use of tractors per ha of arable land was highest during the MDGs (9.74±0.64) and lowest at pre-MDGs era (5.78±3.08). Rate of fertilizer use was highest (15.51±3.47) during the democratic period and lowest during military rule (13.34±3.46) kg ha-1. Aggregate index of agricultural production peaked during the MDGs period (165.5814.85). Production indices for crop, livestock, and forestry were highest during the MDGs period (176.58±22.53, 225.91±36.54, and 129.42±11.89) but that of fishery peaked during the democratic period (158.62±29.79). The AGDP as a percentage of national GDP was highest during the MDGs period (41.76%) and lowest during the pre-MDGs period (38.72%). Agricultural budget as a percentage of total national budgets was highest during the military period (3.67±2.77) and lowest during the democratic period (3.21±2.87). Improvement on road was highest during the military era (63.00±26.51) while industrial development peaked during the democratic period (53.83±11.47). Percentage of foreign private investments in agriculture peaked during the pre-MDGs (1.77±1.03). A unit change in area under irrigation led to increase in agricultural productivity by 2.11%. Agricultural productivity index was highest during the MDGs period (0.87±0.09) and lowest during pre-MDGs era (0.84±0.11). Real AGDP per capita was also highest during the MDGs era (N2872.19±491.75) and ebbed during military era (N1950.75±398.76). Agricultural productivity and agricultural budgets significantly improved rural welfare by 0.28% and 0.29%. Also, industrial development and road infrastructure indices significantly improved rural welfare by 0.01% and 0.11%. The policies implemented during democratic period significantly improved rural welfare by 0.65%. Increase in agricultural production led to significant improvement in rural welfare in Nigeria. Increment in land area under irrigation would therefore, be recommended to sustain the agricultural productionItem Income Polarisation and Poverty Among Rural Households in Nigeria(2013) Ogunyemi, O. I. O.Poverty in Nigeria has been on the increase with consequence for Income Polarisation (IP). The IP which is the sum effect of alienation and identification between two groups at polar ends of the income distribution could worsen poverty. Studies on income distribution and poverty have mostly focused on income inequality to the total neglect of IP. Therefore, the extent and pattern of IP and its relationship with poverty among rural households in Nigeria were investigated. Data covering households’ socio-economic characteristics and consumption expenditure were obtained from secondary sources through the National Consumer Survey of 1980, 1985, 1992, 1996 and National Living Standards Survey of 2004 conducted by the National Bureau of Statistics. As a result of data collection and cleaning with elimination of households with some missing values considered important for the study, samples of 4,685, 4,044, 5,712, 11,358 and 22,152 households with relevant variables: household’s consumption expenditure, occupation, gender, education, age, household size and marital status were used for the survey periods. Analysis was done for the six geopolitical zones of rural Nigeria. Data were analysed using Duclos-Esteban-Ray (DER) polarisation index, Foster–Greer–Thorbecke poverty index and Tobit regression at p=0.05. Mean per capita household expenditure at 1980 prices was lowest (N89.75 ± N60.31) in 1996 and highest (N1,124.78 ± N1,072.00) in 2004. The IP decreased between 1980 (0.2389) and 1985 (0.2111), increased in 1992 (0.2371), then decreased in 1996 (0.2189) and 2004 (0.1874). The IP was highest in the southsouth in 1980 (0.2551), 1985 (0.1991) and 1996 (0.2147). In 1992, the southeast had the highest (0.2373) while the southwest was highest (0.1851) in 2004. The IP was lowest in the northcentral in 1980 (0.2019) and 1985 (0.1753). The southwest (0.2119) and northwest (0.1885) had the least values in 1992 and 1996 respectively. In 2004, the southsouth had the least IP of 0.1757. Among farming households, IP was highest (0.2169) in 1980 and lowest (0.1792) in 1985. Non-farming households had highest IP (0.2115) in 1980 and lowest IP (0.1806) in 2004. Male IP (0.2411) was higher than that of female (0.1792) in 1980. Also in 1996, IP was higher for male (0.1958) than female (0.1890). Except in 1992 when IP for educated households was higher (0.2140) than that of non-educated (0.2120), the other periods had non- educated being more polarised. Non-wage employed had higher IP over the periods with 0.1833 than wage employed 0.1799 in 2004. Polarisation increased with poverty level at N714.80 poverty line. A unit increase in age, household size and poverty significantly increased IP by 0.01%, 0.01% and 0.73% respectively. However, years of education and being married significantly decreased IP by 0.01% and 0.27% respectively. Income polarisation reduced among households over the periods but higher in the southern geopolitical zones as well as among farming households. Income redistribution policy should be based on poverty reduction.Item Economic Impact of Climate Change on Smallholder Crop Farms in Nigeria(2015) Odozi, J. CThe negative effect of Climate Change (CC) on agriculture across Africa has been well established. This underscores its global policy interest. In Nigeria, crop farming is climate dependent and farmholders often employ measures that are sub-optimal against climate risk. This raises the vulnerability of farming to CC uncertainty. For a long time, knowledge of CC perception by farmholders dominated the existing literature. However, information on economic estimates of damages and responses at the farm level is relatively scanty. Economic impact of CC on smallholder crop farms was therefore investigated. General household survey data on smallholder farms collected by the National Bureau of Statistics (NBS) in 2010 was used together with baseline climate observations from 1950-2000 and projections (2000-2050) of the World Climate Data Base (WCDB). Complementary data on population, soil and altitude for 774 Local Government Areas (LGA) were sourced from National Population Commission (NPC) and Food and Agriculture Organisation (FAO). Variables from NBS were farm value, farm revenue, crops cultivated, land size, area planted, household size and age. Variables from WCDB were Mean Temperature (MT) and Mean Precipitation (MP) for wet and dry seasons. Data was analysed using descriptive statistics, multivariate probit and Ricardian models at ∝0.05 Farm value and annual farm revenue were 156293.3 (10714.3-1619433.0) N/ha and 47837.1 (3966.2-2159244.3) N/ha respectively. Land size was 2.7±1.9 ha while area planted, household size and age were 2.3±18.2 ha, 5.2±1.6 and 51.3±15.3 years respectively. Baseline MT and MP were 26.3±2.9 ℃and 179.2±75.1 mm/month respectively for wet season and 25.9±3.0 ℃ and 22.3±24.7 mm/month for the dry season. Projected MT and MP were 27.61±3.0 ℃ and 192.3±61.6 mm/month for wet season and 27.5±3.0 ℃ and 25.6±29.3 mm/month for dry season respectively. Baseline MP increased the probability of cultivating sorghum (0.5%), cowpea (0.2%), and yam (0.1%) while it reduced the probability of cultivating millet (0.8%), rice (0.1%), cassava (0.1%) and maize (0.5%). Baseline MT increased the probability of cultivating millet (5.8%), rice (2.4%) and maize (51.5%) and reduced the probability of cultivating sorghum (0.7%), cowpea (2.1%), cassava (0.7%) and yam (36.7%). Projected MT reduced the probability of cultivating all crops with the highest probability on sorghum (10.5%). While the effect of projected MP on the probability of cultivation was mixed across crops, the highest probability of reduced cultivation was observed for rice (25.9%) and the least for maize (1.8%). Controlling for non-climate factors, climate change reduced farm value by 62.8% for the whole country and across agricultural zones by 8.2%, 41.9%, 7.2% and 41.0% for North central, North east, North west, and South west respectively except for South east that increased marginally by 3.4%. Climate change affected revenue and crop cultivation of smallholders and could affect food security in the near future. Impact was huge for the whole country and varies across agricultural zones. Use of stress tolerant technologies (irrigation, and drought tolerant seeds) and institutional support would enhance coping capacity against climate change riskItem Impact of Root and Tuber Expansion Programme Technology Adoption on Poverty and Food Security Status of Cassava- Farming Households in Southwestern Nigeria(2011) Obisesan, A. AAdoption of yield increasing technologies among farming households is one way of reducing poverty and food insecurity. In Nigeria, Root and Tuber Expansion Programme (RTEP) was implemented to develop improved technology of root and tuber crops. However, the impact of RTEP technology on poverty and food security has not been fully established. Therefore, the effect of RTEP technology on poverty and food security status of cassava-farming households in southwestern Nigeria was investigated. Ondo and Ogun states were randomly selected from the six states in southwestern Nigeria. Two RTEP participating and two Non-RTEP participating Local Government Areas (LGAs) were randomly chosen from each state. Three communities were randomly selected from each of the LGAs. In each RTEP community, 30 households were randomly selected (beneficiaries and non-beneficiaries) while 15 households were randomly selected from each Non-RTEP community making 540 respondents. Data were collected on age, gender, Household Size (HS), Land Area Cultivated (LAC), technology adoption, Credit Accessibility (CA), Educational Level (EL), Off-farm Activities Participation (OAP), Cassava Yield (CY), Distance to Input Market (DIM) and Household Consumption Expenditure (HCE) using structured questionnaire. The HCE was used to estimate Poverty Incidence (PI) and Food Insecurity Incidence (FII) while other variables were hypothesized to influence Adoption Level (AL) of RTEP technology. Data were analyzed using propensity score matching, descriptive statistics, Foster-Greer-Thorbecke and Tobit regression model at p = 0.05. There were 387 RTEP and Non-RTEP households with similar characteristics. Age (44.3 ± 10.1 years), HS (6.0 ± 2.0) and LAC (1.0 ± 0.4 hectares) of the beneficiaries were not significantly different from those of the non-beneficiaries. The AL of RTEP technology was 76.01%. Cassava yield of RTEP Beneficiaries (RTEPB) was 14.56 ± 1.27 tons/ha. Gender, OAP, CA and EL significantly increased AL by 13.8%, 15.8%, 4.7% and 17.6% respectively while DIM decreased AL by 1.8%. At poverty and food insecurity lines of ₦34,473.00 and ₦20,132.20 respectively per annum, 55.0% RTEPB were poor while 51.3% were food insecure. The RTEP technology adoption reduced PI of RTEPB by 11.2%. The PI of the male beneficiaries reduced by 12.6% compared with 5.6% for female. The PI of RTEPB with CA reduced by 11.8% compared with 5.2% for those without CA. The PI decreased by 14.1% for RTEPB with OAP while the reduction was 8.2% for those without off-farm activity. The FII decreased by 16.3% with male RTEPB having higher reduction of 17.8% compared with female of 8.0%. The FII of the beneficiaries with CA decreased by 20.9% while the reduction was 9.8% for those without CA. The decrease in FII was 17.45% for RTEPB with OAP compared to 9.4% for those not participating. Root and Tuber Expansion Programme technology alleviated both poverty and food insecurity status of beneficiaries especially among males, those with credit accessibility and off-farm activity participation in southwestern Nigeria.Item Effects of Rice Trade Policies on Household Welfare in Nigeria(2014) Obi-Egbedi, O.Inconsistent trade policies have characterised Nigeria’s rice importation, leading to planning and decision-making challenges for producers and consumers, and with fluctuating consequences on welfare status. However, studies on Rice Trade Policy (RTP) have been carried out within the partial equilibrium framework which do not reveal the welfare effects on all sectors and households in the economy. For effective RTP, an understanding of the economy-wide welfare effects is necessary which is possible within a general equilibrium framework. The economy-wide welfare effects of RTPs on households in Nigeria were therefore investigated. Value of domestic production, inputs and intermediate products were obtained from Nigerian Institute for Social and Economic Research’s Input-Output (I-O) table. From the I-O, the economy was grouped into rice, Other Agriculture (OA), Oil and Mining (OM) and Manufacturing and Services (MS) sectors. Household incomes were collected from National Bureau of Statistics’ Nigerian Living Standards Survey (NLSS). From NLSS, households were classified into Rural North Household (RNH), Rural South Household (RSH), Urban North Household (UNH) and Urban South Household (USH). Value of imports and import charges, as measures of Import Tax (IT), were gathered from the Central Bank of Nigeria’s trade summary. All data were for year 2004. Two trade protection policy instruments: Import Ban (IB) and Eighty Percent Tariff Increase (EPTI); and two trade liberalisation policy instruments: Five Percent Tariff Reduction (FPTR) and Tariff Elimination (TE) were identified for simulation. Data were analysed using computable general equilibrium model and Hicksian measures of equivalent variation. Total output valued at ₦11,065 billion comprised MS (42.9%), OM (28.9%), OA (27.5%) and rice (0.7%). Household Income (HI) totaled ₦8,260 billion comprising USH (43.1%), UNH (32.8%), RSH (13.5%) and RNH (10.6%). The IT contributed 77.5% of government revenue. Rice output increased most by 3.1% under TE followed by 1.1% under FPTR. Least increase in rice output of 0.1% occurred under EPTI. Output decreased most in OA (21.7%), OM (0.01%) and MS (0.1%) under TE. However, output increased by 0.5% in OA and decreased least in OM and MS with 0.1% and 0.6% respectively under FPTR. Rural north household had the highest increase in HI of 0.3% under IB but recorded the highest decrease of 17.9% under TE. Least decrease in HI was recorded for RNH (0.1%), RSH (0.01%) and USH (0.2%) under FPTR whereas, UNH income increased by 0.1%. Import ban improved RNH welfare most by ₦2.3 billion while TE decreased it most by ₦115.0 billion. Social welfare loss occurred under all RTPs but was lowest (₦8.0 billion) under FPTR. Highest loss in welfare of ₦694.1 billion occurred under TE. Rural households benefitted under protectionist rice trade policies but the social welfare effect on the economy was negative. However, mild rice trade liberalisation of 5% tariff reduction would minimise Nigeria’s welfare loss from rice trade policiesItem Effects of Social Capital and Microcredit on Profitability of Grain Traders in Southwestern Nigeria(2014) Durojaiye, A. M.Grain marketing requires considerable investment of fund but traders are often plagued with inadequate capital to run their enterprises. The inadequacy of fund prevents traders from expanding their businesses resulting in low profit margin. However, social capital is increasingly recognised as a bridge for the gap in credit availability which can help in business expansion and profitability. There is little empirical evidence on the extent of the effectiveness of social capital and microcredit delivery in profitability of traders. The study was designed to investigate the effects of social capital and microcredit on profitability of grain traders in southwestern Nigeria. Multistage sampling procedure was employed for the study with random selection of Oyo and Ogun states from the six states in southwestern Nigeria. Two Local Government Areas (LGAs) were then randomly selected from the states. Eleven rural and twelve urban markets were randomly chosen in each of the LGAs based on Probability Proportionate to Size (PPS). Finally, 500 grain traders were sampled using PPS, with 492 traders having detailed information used for the analysis. Data were collected on grain traders’ socio-economic characteristics, membership density, Meeting Attendance (MA), heterogeneity, Decision Making (DM), Cash Contribution (CC), Labour Contribution (LC), trust, social cohesion, Time Lag (TL), Payback Period (PP), credit distance as well as costs and returns. Data were analysed using descriptive statistics, multinomial logit, budgetary analysis, ordinary least square and two- stage least square regression models at α0.05. Age and household size were 43.3 ± 9.4 years and 6.0 ± 2.9 respectively. Density of membership in associations was 3.0 ± 0.1. Average MA by traders was four out of five. Membership of the association was diversified with heterogeneity index of 69.9%. Members participated in three out of five decisions made by the associations. The six microcredit sources identified were Traders’ Association (TA); community association; cooperative society; Rotating Savings and Credit Association (ROSCAS); Friends and Relatives (FR) and Microfinance Bank (MB). Total revenue was N496, 135.80 while net revenue was N12, 359.00. Average amount of credit granted from the six identified sources was N67, 480.13 ±6, 764.80 representing only 46.0% of the total credit needs of the traders. The TL for credit was 2.13 ± 2.00 weeks with a PP of 6.51 ±4.17 months. Payback period decreased the likelihood of access to credit in TA, ROSCAS, FR and MB ranging from 61.5% to 84.5%. Credit distance increased credit access in TA (2.81) and ROSCAS (1.93). Interest charged decreased credit access in TA (-2.40) and RF (-3.38). Trust and heterogeneity indices increased credit access in ROSCAS by 77.5% and 99.2% respectively. Increase in time lag reduced profitability of the grain traders (-0.0235) while social capital increased profitability by 12.1%. Social capital increased access to, and the amount of credit available, which improved profitability of grain traders. Therefore, social capital formation with its attendant implications for improved access to microcredit should be encouraged.Item Demand, Supply Response and Preference Switch for Rice in Nigeria(2014) Ayanwale, A. O. S.The phenomenon of increasing rice importation defying several policy interventions has been of great concern in Nigeria. This rising importation is however driven by increasing demand, shortage in domestic supply and consumers’ preference for imported rice. Yet, comprehensive national studies on determinants of demand, supply response and preference switch for rice are scarce. Thus, the determinants of demand, supply response and preference switch for rice were investigated. Secondary data from the Nigeria Living Standard Survey (NLSS) of 2004 conducted by the National Bureau of Statistics (NBS) and time series data from the official records of International Rice Research Institute (IRRI), 1960-2008 were used. Due to elimination of households with missing values on variables of interest, a total of 18,861 out of 21,900 households were used in the NLSS. Variables used in NLSS included Household Size (HS), Non-Food Total Expenditure (NFTE), Years of Education (YE), sector (urban/rural), occupation (farming/non-farming) and Membership of Association (MA) which were hypothesized to influence household expenditures on Imported Rice (IR), Improved Domestic Rice (IDR) and Local Rice (LR). Data on area cultivated, level of import, fertilizer consumption and prices were used in IRRI rice statistics and these variables were also hypothesized to influence supply (output) of rice. Data were analysed using descriptive statistics, Tobit regression model, vector error correction model and generalised least square regression at p= 0.05. The HS and YE were 4.9±2.9 and 6.8±6.3 years, respectively. Rural dwellers, farmers and members of association constituted 76.1%, 82.7% and 54.2%, respectively. Monthly rice expenditure was N2, 712.40, representing 25.0% of total monthly food expenditure. The expenditure share of IR (45.0%) was higher than IDR (30.0%) and LR (25.0%). Urban sector, YE, HS and NFTE increased the demand for IR by 4.0×10-03, 2.0×10-04, 1.0×10-03 and 1.0×10-09, respectively, while Farming Occupation (FO) reduced it by 9.0×10-03. Also, FO increased IDR demand by 8.0×10-03. Conversely, HS, NFTE, and MA reduced IDR demand by 9.0×10-04, 2.0×10-08 and 1.0×10-09, respectively. Also, NFTE and MA, respectively, increased LR demand by 6.0×10-09 and 4.0×10-03. Price elasticities of IR, IDR and LR which were -3.0×10-03, -7.0×10-04 and -2.0×10-03, respectively implied that rice was price inelastic. Also, income elasticities of IR, IDR and LR which were, respectively, 7.0×10-08, 2.0×10-07 and 1.0×10-07 classified rice as ‘necessities’ and ‘normal’ good. In the long-run, area cultivated and fertilizer consumption increased rice output by 2.8 and 2.3 respectively. Rural Sector (RS), HS, FO, and price of IR increased consumers’ switch from IR to IDR by 55.1, 6.6, 130.4, and 30.7, respectively, while price of IDR reduced it by 19.4. Price of IR and RS positively influenced switch from IR to LR by 2.0 and 70.2, respectively, while price of LR reduced it by 16.3. Education and urban livelihood increased demand for imported rice. Increasing rice area cultivated and usage of fertilizer may boost domestic rice supply. Price reduction will be a veritable tool in switching consumers’ preference from imported to improved domestic and local rice.