INEQUALITY, POLARIZATION AND POVERTY IN NIGERIA. Awoyemi Taiwo Timothy Oluwatayo Isaac Busayo Oluwakemi Adewusi

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1 INEQUALITY, POLARIZATION AND POVERTY IN NIGERIA Awoyemi Taiwo Timothy Oluwatayo Isaac Busayo Oluwakemi Adewusi

2 BACKGROUND Nigeria: A country with large territory FRN: 36 States plus FCT, Abuja 12 Northern states, 12 Middle belts States, and 12 Southern states The states are subdivided into 774 (LGAs). Grouped into six geo - political zones on ethnic identity (ethno-linguistic fractionalization) 374 identifiable ethnic groups

3 Political rivalry Ethno-regional clusters: the Hausa-Fulani (39.1%), Yorubas (21.4%), Ibos (11.7%) (Total=72.7%) Effects: Civil War (1970) tension, civil unrest competitive rent-seeking activities, corruption, institutional failures, inefficiency polarization and social conflict

4 Poverty High between 1980s - 90s (Canagarajah, et al., (1997) Head count ratio: Higher in the northern parts North east zone: Highest poverty incidence (67.3%)(NBS, 2006) South east zone: The least poverty incidence (34.2%) (NBS, 2006) Drop in relative poverty 65.6 per cent in 1996 to 54.4 per cent in 2004 (NBS, 2006). Further, urban sector declined by 15%, rural sector declined by 6.5%

5 Inequalities Inequality increased from 38.1 per cent in 1985 to 44.9 per cent in (Canagarajah et al, 1997). Top 10% of the income bracket accounts for 60% of total consumption (Okunmadewa, 1998) North West zone contributes (5.2 per cent) South East zone contributes the least (1.2 per cent) to the national inequality (Araar and Awoyemi, 2006)

6 Polarization High regional differences in social and economic conditions (Ogoni case in oil producing Niger delta) Sectarian tensions and violence Tendencies for socially embedded inequality Vestiges of colonial administration Dual economies: rural and urban Gender inequalities Susceptibility of the country to disintegration Motivation: to detect and predict possibilities of social conflict and revolutionary tendencies Furthering our under standing of the nature of distributive changes

7 Concept definitions Inequalities Dispersion of the distribution of the attributes of the welfare indicators Inversely linked with equalizing meanpreserving spreads Emphasizes the deviation from the global mean, ignoring clustering around local means (Zhang and Kanbur, 2001)

8 Polarization the clustering of incomes around local poles building homogeneous clusters that oppose each other Involves disappearance of the middle class Fails to satisfy the principle of transfers between polar group Bi-polarization: Considers only two poles

9 Research Questions Sufficient evidences of double process of regional convergence National question: how to structure the state so that every ethnic or religious group and every Nigerian as an individual becomes a stakeholder? How do we detect inequality and polarization and empirically document the differences and their contribution to poverty in Nigeria? What are the reasons underlying the evolution of these phenomena? How bipolar is Nigeria society? How much do disparities in average living standards between zones, regions, urban and rural sectors contribute to the level of polarization or inequality in Nigeria?

10 General Research objective To empirically document the evolution of inequality, polarization, bipolarization, and the driving force behind them as well as how these have contributed to the level of poverty in Nigeria

11 Specific objectives empirically estimate the trends and levels in regional polarization, bipolarization, poverty and inequality of per capita expenditure distribution between in Nigeria. identify and estimate the explanatory power of key dimensions along which polarization occurs in Nigeria assuming that income proximity determines the group to which one belongs. examine the origin of polarization in the regional distribution of per capita expenditure for the special case of two poles (bipolarization) and its link to poverty in Nigeria. estimate the contribution of within and between regional variations to total inequality, polarization, bipolarization and poverty in Nigeria.

12 Scientific Contribution of the Research Review and employ value-added measures to perform the decomposition of polarization indices into their component groups Investigate the link between polarization and poverty in Nigeria

13 Policy relevance Weak democracy in Nigeria- low level of trust, tension, bitterness, violence Strong correlation of economic status and social categories like ethnic and religion - polarization along these dimensions Importance of the middle class as an engine of development and sustenance of democracy Egalitarian enhancing information, shed light on factors associated with conflicts Help targeting of programmes education, health, infrastructure Identifying and locating the poor and lagging regions Guide decisions of private initiatives and LGAs reform The need to judge the tax reform policies Assessment of the present government policies The need to nurture specific programmes FEAP, NAPEP Size of Nigeria in Africa economy

14 Theoretical framework Significant economic dualism in Africa Broadly backwash effect circular and cumulative causation thesis (Myrdal, 1957) unequal natural resource endowments (Williamson, 1965) limited availability of arable land, distance from the sea and the prevalence of disease The need to locate the poor and understand the dynamics of their distribution

15 Literature Review and Knowledge Gaps Esteban and Ray (1994), Wolfson (1994) Duclos, Esteban and Ray (2004) Duclos and Echevin 2004 Fedorov, 2002 Rodriquez and Rafael Salas, 2006 Dearth of information in these areas Aighokhan 2000, Nigeria The use of rigorous axiomatic decomposition method of polarization

16 Methodology Data requirements and sources The 1996 National Consumer Survey (NCS) 1998/99 General Household Survey data sets 2004 World Bank assisted National Living Standard Survey (NLSS) data. A two-stage cluster design was employed cluster of 120 housing units called enumeration area (EA) were randomly selected from each of the 36 states including FCT second stage: random selection of 5 housing units from the selected EAs 600 households were randomly chosen in each state and the FCT, summing up to 22,200 households in all For GHS in each state a sample of 120 EAs were selected for the survey 10 housing units were randomly selected in each of the sample we choose consumption as our indicator of well-being.

17 Analytical methods Gini Coefficient: that could be used for individual data. For instance Lerman and Yitzhaki (1984) 2cov ar( y, r y ) G= Ny 1 σ y G = ρ ( y, r y ) 3 y Milanovic (1997): Gini coefficient is the product of a constant, coefficient of variation of income and correlation coefficient between income and rank

18 Gini: Shapley decomposition approach It is based on the ethical values that allows exact algebraic decomposition of Gini index (Araar 2004) I( μ1..., μ g ) I( y ( μ μ )) i g ( ) I= C + C int er Cint er = 0.5 I I yi ( μ μg ) I( μ1,..., μ + G ( μ μ ) ( μ μ ) Cint ra = 0.5 I I 1,..., G + I( yi g ) int ra

19 Polarization Axoms IS That is a greater distancing between two groups below and above the median increases polarization IB A rank-preserving equalizing transfer between two individuals on the same side of the median increases polarization Symmetry means that a reordering of incomes does not change the level of polarization Principle of population: if an income distribution is pooled several times, then the degrees of polarization of the pooled and the original distributions are the same Normalization attaches zero polarization to a perfectly equal income distribution. Continuity means that P will not take an abrupt jump for small changes in its argument

20 DER (2004) Polarization Estimation for Continuous Distributions Avoid conceptual and practical problems of population distributed over a discrete and distinct number of points measurement theory of polarization for the case in which asset distributions can be described using density functions appropriate for the case of continuous distributions of our income variable Identification-alienation framework DER take polarization to be proportional to the sum of all effective antagonisms DER re-define the axioms for continuous variables based on a density with finite support (kernel) symmetric reductions in dispersion that concentrate the density around its mean (squeezes) Determine the area of identification influence by nonparametric kernel techniques Estimation of the polarization indices is done by substituting the distribution function by the empirical distribution function Duclos et al method, Horenstein and Olivieri (2004) method

21 Estimation method P f f x f y y xdydx 1+ α α ( ) ( ) ( ), whereα [.25,1] G * P F = f x y j x x y dfj j= 1 k j x dfk y ( ) ( ) ( ) ( )

22 Bootstrap Method to ascertain statistical inference for polarization measures It will allow us to build 95% confidence intervals, thereby enabling us to test for the existence of a significant change e.g Biewen (2002), Mills and Zandvakili (1997).

23 The index of polarization of Reynal-Querol Л is the proportion of each group i denotes a group N is the number of groups N 2 1 (0.5 i) i 0.25 i= 1 IRCI = π π RQ index of polarization has the usual properties of other indices properties This index provides a ranking order of the different distributions of the population similar to those in the measure proposed by ER (1994) The major difference between these two indices is in the form of the function; whereas IRC1 has a convex and concave part as explained in the proposal ER is strictly convex for α > 1 (Reynal-Querol, 2002).

24 The Wolfson indexbipolarization W= 2(2 T Gini) ( m μ) where T = L(0.5) L(0.5) = the value of the Lorenz curve at the 50th percentile m and µ are the median and mean respectively

25 Rodríguez and Salas's (2003) approach where m is the median, µ is the mean F is the distribution function 2μ B W P( F) = G ( F) G ( F) m Subtract B W within-groups from G B the between-groups Gini coefficient computed for groups separated by the median value conceptually, inequality and polarization can be viewed within the same framework, with addition and subtraction of the within-groups component corresponding to inequality and polarization, respectively a connection between Wolfson s concept of polarization and the polarization model of ER has been established

26 Bipolarization-Poverty Link bipolarization and poverty measures are closely related when the income value used to separate income groups represents the poverty line (Rodríguez, 2006) the normalized poverty deficit index is equal to the ER polarization measure, whether the poverty line is the mean income and the identification sensitivity parameter is unity. Wolfson polarization measures is a function of the normalized poverty deficit index, which belongs to the Foster Greer Thorbecke family of poverty measures (Foster et al., 1984).

27 Tsui and Wang (1998) Measure k θ TW = f ( y j ) N j = 1 f(yi) is the population share of group i k is the number of groups, yi, is the mean value in group m is the median income. θ is a positive constant scalar and rє(0,1) we shall set r = 0.5 y j m m r

28 Zhang and Kanbur (2001) require an a priori specification of clusters (groups of regions), measures the extent of inequality between these clusters derived from the GE index by decomposing it by population into within-group and between-group inequality and, then, taking a ratio of between and within components

29 k GE = w I + I( μ l... l ) g g 1 1 k g= 1 KZ between groupinequality I( μ1l1,..., μklk) = = k within groupinequality wi g= 1 g g

30 Marginal contributions of the within and between group G PYzL (,, ) ϕ P( Y, zl, ) * * = g= 1 G = g= 1 g g g P Y z L ϕ P μ z L (,, ) (,, ) g g g G ( **,, ) (,, ) ** P Y z L = μ ϕgpg z L μ g= 1 g

31 S 1 CW = 2 P W B P B + P W P z L S 1 CB= 2 P W B P W + P B P z L where P( W, B) = P( Y, z, L) and [ (, ) ( ) ( ) ( μ,, )] [ (, ) ( ) ( ) ( μ,, )] PB ( ) = ϕ P( μ, zl, ) g g g μ PW ( ) = ϕgpg( zy, g, L) μ g

32 THANK YOU ALL

Stochastic Dominance in Polarization Work in progress. Please do not quote

Stochastic Dominance in Polarization Work in progress. Please do not quote Andre-Marie TAPTUE 17 juillet 2013 Departement D Économique and CIRPÉE, Université Laval, Canada. email: andre-marie.taptue.1@ulaval.ca