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Macro policy reform, labour market, poverty & inequality in Urban Ethiopia:
A Micro-simulation approach

Alemayehu Geda1, Alem Abereha

September 2006

SARPN acknowledges the African Economic Research Consortium (AERC) as the source of this document:
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Despite the liberalization program that Ethiopia embarked upon since 1992 aggregate indicators of poverty and inequality largely remained unchanged. This paper addresses why incomes and inequality largely remained stable at a time of fundamental changes in macroeconomic policy environment. We have used both data exploratory analysis as well as earning and occupational choice modelling, together with counterfactual simulation, to investigate this issue. The study showed that the absence of change in aggregate measure of poverty and inequality hides an enormous change that occurred across different income categories. This shows the importance of understanding the labour market to understand the policy propagation mechanism through which macro policy is expected to affect poverty.. The study has show that although there seem to be limited change in poverty and inequality at aggregate level, there is significant change within and across categories of households. Thus different household are affected differently by the reform. The level and distribution of household incomes is found to depend on the structure of returns to labour and on the occupational choice the households made. Thus, policy effectiveness of poverty reduction policies could be achieved if we understand the workings of the labour market and how it affects both level and distribution of income across different categories of income & sector.


Governments in Africa and their development partners such as the Worland Bank and IMF are concerned with the issue of reducing poverty. Thus, since the 1980 they have deployed macro policy packages that are believed to help in addressing the challenge of reducing poverty. This took the form of Structural Adjustment Packages (SAP) in the 1980s and 1990s and now taking a ‘new’ form called Poverty Reductions Strategy Programs/Papers (PRSPs) or its new (or competitive version) ‘the Millennium Development Goals’ (MDGs). At the heart of these policy packages lie a set of macro polices, which can loosely be termed as ‘liberalization and conservative monetary and fiscal policies’ – or reform in short, that are believed to help the fight against poverty. One important analytical shortcoming of these efforts is lack of a link between macro policies employed and indicators of issues of poverty and inequality. In other words, we do not precisely know through which channels the deployed macro policies are supposed to affect poverty (perhaps the only exception being the presumption that stable macro environment is good for growth and hence for reducing poverty). One obvious channels through which macro polices may affect poverty is through its effect on the labour market and hence earnings form that market. Thus, characterization of the labour market in general and modelling how incomes are generated in this market in particular are key to understand the propagation mechanisms through which macro polices may affect poverty and inequality. This paper is aimed at exploring this issue using the Ethiopian household data and a micro simulation technique.

The rest of the study is organized as follows. In the next section, we present a brief review of the macroeconomic performance in post-reform Ethiopia. In section three, we will analyze the structure of employment and household income in urban Ethiopia. This section provides a description of the state of affairs and evolution of key labour market indicators using two rounds of a household survey undertaken in 1994 and 2004. In section four we will specify the models employed in the study and estimate their parameters. Using these models we have made a microsimulation analysis of the impact of the reform on poverty and inequality in the same section. Section five will conclude the paper.

  1. Assoc. Prof., Dept of Economics, Addis Ababa University (corresponding author ). We thank the African Economic Research Consortium for financing this study. Any errors are ours.

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