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Articles by F.Y. Okunmadewa
Total Records ( 3 ) for F.Y. Okunmadewa
  A.O. Adesanoye and F.Y. Okunmadewa
  A household`s observed poverty status is an ex-post measure of its well-being (or lack thereof). But in thinking about forward-looking anti-poverty interventions that aim to prevent rather than alleviate poverty, what really matters is the vulnerability of households to poverty that is the ex-ante risk that a household will, if currently non-poor, fall below the poverty line, or if currently poor will remain in poverty. This study empirically assessed vulnerability to poverty at household level using a two-period panel data set obtained from 150 households, sampled from two local government areas within Ibadan Metropolis. The study also examined the socio-economic characteristics of the respondents that affect a household`s vulnerability to poverty. Data were analysed using descriptive statistics, poverty indices and probit regression analysis. Analysis of the socio-economic characteristics and their relationship with vulnerability to poverty revealed that large-sized households headed by men who were old, widowed, self-employed, uneducated or who had only primary school education and who had no access to any form of credit, were more vulnerable than other households. The estimated probit regression equation showed that marital status and tertiary education status of respondents reduced vulnerability to poverty while primary education status and household size enhanced households vulnerability to poverty.
  F.Y. Okunmadewa , S.A. Yusuf and B.T. Omonona
  Against the backdrop of increasing focus on the use of Local Level Institutions (LLIs) in addressing poverty and the growing literature on impact of social capital on welfare and poverty, this study provides empirical evidence for Nigeria. The study focuses on households’ memberships in LLIs using primary data from 587 households in 6 participating pilot states under the World Bank’s assisted Community-based Poverty Reduction Project (CPRP). Six measures of social capital were identified. These are density of membership, internal heterogeneity of associations, meeting attendance, payment of membership due, labour contribution and decision making. The study reveals that an average household size of 9 participates in at least 3 LLIs. Further, internal heterogeneity reveals some level of diversity in each group while meeting attendance index averaged about 60% for all participating members of households. An average of N4, 254.90 membership due and 43 days of labour are contributed by households to LLIs. The basic data from the study indicate that households with higher social capital are less poor using different dimensions of poverty. The study shows that while a unit increase in household size tend to aggravate poverty by 3.1%, one extra year of educational attainment reduces the extent of poverty by 1.6%. The level of heterogeneity of the associations, meeting attendance index, cash contribution score and the labour contribution score are the key social capital dimensions with dampening effect on poverty, in the order listed, a unit change in each of these dimensions of social capital leads to 0.85, 1.2, 0.82 and 0.3%, respectively.The findings of this study support recent emphasis on investing in social capital. In addition it has been shown that investments in LLIs need to be part of poverty alleviation programmes.
  A.S. Oyekale and F.Y. Okunmadewa
  Poverty measurement has recently shifted from the income/expenditure unidimensional approach to multidimensional all inclusive poverty indicators. This study constructs some composite indicators of multidimensional poverty and determines some socio-economic factors influencing them. Data collected in 2002 from 1686 households in Abia State, Nigeria, were used. Fuzzy set was used to compute poverty indices while Tobit regression was carried out. The multidimensional poverty index is 27.76% for the population and rural areas have higher poverty intensity than the urban areas. Poverty simulation shows drastic reduction if almost everybody has access to electricity, good toilet, water and food. Tobit regression shows that households’ male headship, literacy and urbanization significantly reduce multidimensional poverty. It was recommended that increased literacy will reduce poverty with special focus on rural dwellers.
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