Income Growth and Mobility of Rural Households in Kenya: Role of Education and Historical Patterns in Poverty Reduction

Empirical Findings and Discussions

Table 2a presents the parameter estimates of the first difference model given by equation
(8) in the methods section. For comparison purposes, five different models are estimated
representing different treatments of the lagged dependent variable. Only model (5)
involves IV estimation. Model (1) represents the most basic type of estimation possible
with a two-year panel though it ignores the role of historical patterns in income
determination.

Model (2) shows the results when we include lagged income as a level variable in
a differenced model. Three things are particularly noteworthy here. One is that the
inclusion of the lagged income variable is not in built in the original formulation of the
model and thus does not in itself go through the differencing procedure. Secondly, there
is a significant increase in the coefficient of determination from the first model, thus
indicating the importance of accounting for income persistence in an income model.
Thirdly, the results show evidence of convergence of income towards the mean, a result
that is consistent with earlier studies in Africa that followed a similar econometric
approach, namely Grootaert et al. (1997) and Fields et al. (2003a). The reliability of
these results may however be in question as the estimation fails to account for the
endogeneity of the lagged income variable. Fields et al. (2003b) and Woolard and Klasen
(2005) use a similar procedure but also instrument for the endogenous lagged income
variable. Fields et al. (2003b) find mixed results with the IV method and alludes to the
sensitivity of results to the treatment of the income variable. On the other hand, Woolard
and Klasen (2005) indicate that convergence is maintained with the IV estimation but the
coefficient is greatly reduced for the rural areas.

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