This study examined the socioeconomic characteristics of household in Ekiti State Nigeria, it identified and measured the relative importance of factors affecting poverty in both the rural and urban area of the state. The study also looked at the poverty profile in the area. Data collected from 432 heads of households through a random sampling technique from Ekiti Central, Ekiti North and Ekiti South were analysed using Foster, Greer and Thorbecke (FGT) indices, Gini coefficient index (GI), and ordinary least square (OLS). Result shows that for the urban part of Ekiti State, the poverty headcount ([P.sub.o]) indicates that 48%, 71% and 62% share of the population are poor in Ekiti Central, Ekiti North and Ekiti South while for the rural area it was 61%, 55% and 67% in that order respectively. The Gini coefficient shows that there is high welfare inequality in both Ekiti Central and Ekiti North as the Gini coefficient was 0.57 and 0.63 respectively. However welfare inequality was low in Ekiti South as the Gini coefficient was 0.31. Result of the ordinary least square identified some of the factors affecting poverty in Ekiti State Nigeria. The value of [R.sup.2] for rural area are 0.75, 0.61 and 0.53 for Ekiti Central, Ekiti North and Ekiti South respectively, while for urban it is 0.68, 0.57 and 0.51 in that order. The value of the regression sum of square shows that the model accounts for most of variation in the welfare status in the Ekiti for the period. Other dagonistic tests show that some of the estimates are statistically significant. Out of poverty determinant factors fitted in the model education and household size stand as the most important determinant of poverty in Ekiti State Nigeria.
Keywords: Poverty Analysis, Household, Poverty Line, Welfare Inequality Poverty Determinant
Poverty is a complex human phenomenon associated with unacceptably low standard of living. It has multiple dimensions, manifestations and causes (World Bank 2000).
Poverty analysts from a variety of disciplines have been constantly asking questions about this phenomenon, sometimes out of curiosity, but often with the aim of providing information that can be used to overcome it.
Poverty debate and analyst is understood to incorporate various dimensions.
According to OECD (2001), for example, poverty is multidimensional in that it encompasses deprivations that relate to human capabilities, including consumption and food security, health, education, rights, voice, security, dignity and decent work.
Persistent poverty has plagued Africa for generations and, by some accounts, is becoming more widespread and entrenched. As a consequence, governments and donors have renewed and intensified their commitment to poverty reduction. This is reflected around the continent in poverty reduction strategy, efforts at decentralizing public goods and service delivery and the rise of participatory poverty appraisals intended to empower the poor, and a range of other policy changes.
In some cases, one can legitimately wonder about the extent to which these reforms are heartfelt, rather than merely rhetorical and political, and the extent to which national and international elites are prepared to make sacrifices to advance an authentic poverty reduction agenda. Nigeria has not fair well in poverty.
According to Soludo (2006), Nigeria has been a country of paradoxes. It is a country abundantly blessed with natural and human resources, but the potential remained largely untapped and even mismanaged. With a population estimated at about 140 million, Nigeria is the largest country in Africa and one-sixth of the black population in the world. It is the 8th largest oil producer and has the 6th largest deposit of natural gas in the world. Soludo (2006) asserted that the growth in per capita income in the 1990s was zero while the incidence of poverty in 1999 was 70 percent. As a result of different economic policies...
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[SD.sub.n-1] 58.48 6.94 49.06 6.41 48.19 7.28
Source: Computed from data obtained from Field Survey, 2006.
Source: Computed from data obtained from Field Survey, 2006
TABLE 3: DISTRIBUTION OF RESPONDENT BY MONTHLY INCOME
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