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Explaining Polarization and its Dimensions in Nigeria - African ...

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<strong>in</strong>dex, <strong>and</strong> largely the work of Pyatt, (1976), Lambert <strong>and</strong> Aronso, (1993) <strong>and</strong> Araar (2006) on<br />

the decomposition of <strong>in</strong>equality <strong>in</strong>dex by sub-population groups. The idea is that between-group<br />

<strong>in</strong>equality represents the <strong>in</strong>equality of the group when each household has the average <strong>in</strong>come of<br />

<strong>its</strong> group. Then the algebraic decomposition of the G<strong>in</strong>i <strong>in</strong>dex takes the follow<strong>in</strong>g form:<br />

w<br />

A = ∑ϕ<br />

g<br />

ψ<br />

g<br />

Ag<br />

+ A + R<br />

g<br />

Where<br />

ϕ<br />

g<br />

<strong>and</strong><br />

ψ<br />

g<br />

are the population <strong>and</strong> <strong>in</strong>come shares of the group g respectively. A w is the<br />

between group <strong>in</strong>equality <strong>and</strong> equals to the G<strong>in</strong>i <strong>in</strong>dex when each member of the group has the<br />

average <strong>in</strong>come of <strong>its</strong> group. It is good to note that if <strong>in</strong>comes do not overlap, the residual part<br />

(R) of this decomposition vanishes (Araar, 2008). It follows that group with low residual of<br />

relative contribution will have high explanatory power of the polarization. This decomposition of<br />

G<strong>in</strong>i <strong>in</strong>dex helps to shed light on the decomposition of polarization as we can use the <strong>in</strong>dicator<br />

R/A to assess the explanatory power of the <strong>in</strong>terest group to polarization. This we applied to the<br />

decomposition of the DER <strong>in</strong>dex by population groups follow<strong>in</strong>g Araar (2008). Here our groups<br />

comprise of zone, sector, educational groups, occupational groups <strong>and</strong> sex.<br />

From (2), DER could <strong>in</strong> a way be written as:<br />

[ ]<br />

P= AI( α) 1+ ρ<br />

(9)<br />

(8)<br />

where<br />

1+<br />

α<br />

I( α ) f( y)<br />

dy<br />

= ∫ is the average identification component, A the G<strong>in</strong>i coefficient <strong>and</strong> the<br />

parameter ρ is the normalized covariance between alienation <strong>and</strong> identification which is equals<br />

to<br />

x<br />

α<br />

( [ ])( ⎡ ⎤)<br />

∫ ax ( ) = Ea f( x) −E ⎣<br />

f ⎦<br />

f( xdx )<br />

ρ = (10)<br />

AI<br />

12

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