Inequality in income according to Kopp (2019) is “an extreme disparity of income distribution with a high concentration in the hands of a small percentage of a population”. In the presence of income inequality, large gap exists between the wealth of one segment of the population relative to another. Income inequality can be investigated through a variety of segmentations, such as gender (male vs female), occupation, geographic location and ethnicity (Ibrahim & Taiga, 2020). Segmentations of income distribution on the basis of demographic features forms the basis for our studying income inequality and income disparity.
The concept of poverty is defined by Haughton and Khandker (2009) as a “pronounced deprivation in well-being”. Well-being in this respect can be measured broadly or narrowly. Well-being in the broad sense consists of physical and mental health conditions, competence and self-worth and social connections among others (Wellbeing & poverty Pathways, 2013). Well-being in a narrow definition is linked to commodities, that is, whether individuals or households have adequate resources to take care of their needs. In this instance, poverty is related to monetary terms, that is, household income or consumption expenditure. The theories of poverty are divergent and required difference approach in tackling issues of poverty. Theories reviewed are geographical disparity theory individual deficiency theory, and social exclusion theory.
Geographical Disparities Theory
The theory of geographical disparities relates poverty with geographical features, like rural poverty, ghetto poverty, third world poverty among others. The theory calls attention to the fact that individual, institutions and cultures in certain areas lack access to opportunities for wealth creation. This theory can also be likened to the agglomeration theory which reveals how heavy domicile of similar industries and firms attracts supportive services and market links which attract more industries and firms, while impoverished communities generates more poverty (Danaan, 2018).
Individual Deficiency Theory
The individual deficiency theory was built on the premise of the neo-classical dictum that reinforced individualistic sources of poverty with the assumption that relates poverty to lack of hard work and bad choices of individuals. This theory assumes the poor to be responsible for creating their problems due to individual deficiencies. Other variants of this theory attributes poverty to a lack of generic attributes, IQ level and even punishment from God for sins committed (Danaan, 2018). This theory likens the poor to moral hazard with claim that poverty and inequality exist due to the poor are engaging in activities that counterproductive (Gwartney & McCaleb,1985 cited in Danaan, 2018). Thus, poverty reduction and tightening inequality gap requires hard work, skill acquisition and resilience.
Social Exclusion Theory
The social exclusion theory focuses on the lack or denial of resources, right, goods and services and inability to partake in normal activities and relationship available to the majority of the people in the community. The theory was popularized in the 1960’s and stems from the fact that income inequality could be as result of social exclusion which exacerbates poverty (Ibrahim & Taiga, 2020; Levitas et al., 2007). The basis of this theory is that poverty is due to cumulative disadvantage where a comfortable minority co-exist with a disadvantaged majority who are collectively excluded from socio-economic opportunities in the community. Social exclusion is associated to unemployment and level of income (Gallie et al., 2003).
A good number of empirical studies have been conducted on inequality and poverty incidence, depth and severity in Nigeria for both rural and urban areas. For instance, Asogwa et al. (2012) investigated the determinants of poverty depth among farmers in the peri-urban area of Benue State, Nigeria. Result of the study revealed that household income, farm total economic efficiency, farm size, education, household size, age, credit access, membership of farmer association, extension contact and valuable farm asset significantly impact on poverty depth/incidence among respondents. In the like manner, Ogbonna et al. (2012) carried out an empirical investigation on the factors that influence poverty incidence among rural yam farmers in the south eastern Nigeria. The study result revealed that social group membership, education, participation in agricultural workshops, level of education, farming experience as negative drivers of poverty. Perhaps household dependency ratio indicates a positive relationship with rural poverty in the study.
Similar studies were carried out in the South-West region of Nigeria, in the likes of Olawuyi and Adetunji (2013), Igbalajobi et al. (2013), Akinbode (2013), Adetayo (2014) and Awotide et al. (2015). Olawuyi and Adetunji (2013) evaluated the severity, incidence and determinants of poverty among households in Ogbomoso Agricultural Zone of Oyo State, Nigeria. The study identified household size, gender, years spent in school, non-farm job and farm size as essential significant determinants of poverty in the study area. Igbalajobi et al. (2013) in the vein analysed the determinants of poverty among rural farm households in Ondo State, Nigeria. The logit regression result revealed that gender, age, marital status, household size, credit access, education level and farm income as core determinants of poverty among farm households. In another study, Akinbode (2013) used FGT index to assess poverty incidence, depth and severity and its determinants among urban households in the south west region in Nigeria. The result revealed that 34% of households were poor with a poverty severity and gap indices of 0.06 and 0.11 respectively. The study further revealed household size, gender of household head, dependency ratio, educational level, assess to credit as significant determinants of household poverty in the study area. Similarly, Adetayo (2014) assessed poverty status of rural farm household in Ogun State, Nigeria. The study revealed that poverty incidence was higher among male headed household (60%) and household with over five members (66.1%). The Logit regression result further revealed that there is high tendency of falling into poverty for large households, non-educated farm household head and household with no access to credit and non-farm income. The finding is consistent with the study by Awotide et al. (2015) in Akinyele local government area of Oyo State, Nigeria. The study found that number of dependent ratio and household size significantly increases the tendency of falling below poverty line among respondent. While access to credit and access to extension services significantly reduces probability of falling below poverty line. Similar finding was found a study conducted in the northern region by Duniya and Rekwot (2015). They carried investigation on the determinants of poverty among groundnut farm households in Jigawa State. Result of their study revealed that age of household head, education, marital status of household head and membership of cooperative were negatively related to poverty incidence, while farming experience and access to extension services had positive significant relationship with poverty incidence in the study area.
Related studies have also been conducted in the south-south region of Nigeria. For instance, Edoumiekumo et al. (2014) examined the incidence, depth and severity of poverty in Bayelsa state. The study used 2009-10 NLSS data. Result of the FGT model revealed that 25% of households are income poor. Result from the logit model revealed that agriculture and household size rise the probability of household falling below poverty line while dwelling in the urban area. Whereas the male headed household, a naira increase in household per capita expenditure on health, education, number of years spent in school by household head reduces the probability of household falling below poverty line. In another study in region, Akpan, Patrick & Amama (2016) analysed poverty and inequality as well as its determinants among youth in the rural areas of Akwa Ibom State, Nigeria. Data used in the study were collected from 300 youth spread across rural areas of Akwa Ibom State. The logit regression result revealed that level of formal education, age of youths, amount of non-farm income, farm size and access to agricultural extension services reduces the probability of poverty incidence among youth farmers in the State. While household size and dependent ratio were positive drivers of poverty in the State.
Using a nationally representative data from NBS 2010 survey, Lucky and Achebelema (2018) examined poverty and inequality in Nigeria. Dollar per day poverty line, subjective poverty measure, food poverty line and absolute poverty line were used to measure poverty and Gini coefficient was used to measure income inequality. Result of the study revealed that significant number of the Nigerian population are living below the poverty line and there is wide income gap between the rich and the poor in Nigeria.
Other studies in Nigeria used time series data with different economic approaches. For instance, Brown and Ogbonna (2018) investigated the relationship between income inequality and poverty in Nigeria using data from 1980 to 2017. The study adopted Error Correction Model (ECM) and the following variables inequality, poverty, unemployment and life expectancy at birth. The result revealed that national poverty index increased inequality though was statistical insignificant. In the same vein, Ibrahim & Taiga (2020) examined the impact of income inequality on poverty using Nigerian data from 1986 to 2018. The study employed Autoregressive Distributed Lag (ARDL) model and found that income inequality significantly contributes to the incidence of poverty in Nigeria by 75%. Also, inflation and rising unemployment were found to exacerbate the poverty situation in Nigeria.
From the empirical literature reviewed, it is observed that most studies on income inequality and poverty in Nigeria focused on a particular region or State in Nigeria. To the best of our knowledge none of the existing studies have used the recent Nigeria living standard survey to conduct income inequality and regional poverty analysis. Hence, this study shall use the recent NGLSS to evaluate income inequality and regional poverty using FGT model.