Decomposition of Changes in Poverty Measures: Sectoral and Institutional Considerations for the Poverty Reduction Strategy Paper of Pakistan

Two extremely significant empirical questions on the relationship between growth, distribution and poverty have remained the focus of attention for researchers and academicians. First, how does a change in aggregate poverty reflect intrasectoral gains/losses versus intersectoral shifts in population? Second, how much of an observed change in poverty can be attributed to the changes in the distribution of income, as distinct from growth in average incomes? Standard inequality measures like the Gini coefficient can be misleading in this context. At any rate, the change in an inequality measure can be a poor guide to its quantitative impact on poverty. Ravallion and Huppi (1991) proposed decomposition formulae to throw light on the contributions of sectoral gains and population shifts (on the one hand) and economic growth and changes in inequality (on the other) to aggregate changes in poverty. They found that both population shifts and gains to the urban and rural sectors alleviated aggregate poverty in Indonesia over the 1984–87 period. In addition, they obtained estimates of the relative contributions of growth and greater equity to poverty alleviation in Indonesia. Datt and Ravallion (1992) extended the analysis to study poverty in Brazil and India during the 1980s. Kakwani (1993) explored the relation between economic growth and poverty for Cote d’Ivoire from 1980–85. He developed his own methodology to measure separately the impact of changes in average income and income inequality on poverty. Kakwani (2000) applied the same methodology to analyse changes in poverty in Thailand covering the period from 1988–94. Recently, Contreas (2003) examined the evolution of poverty and inequality in Chile between 1990 and 1996. Using the “Datt-Ravallion decomposition”, he computed that economic growth accounted for over 85 percent of the poverty reduction in Chile.