Understanding Changes in Welfare
June 19, 2013
- To what extent does labor income drive poverty reduction, and how can it be measured? Economists use decomposition methods to find out. Learn more on this page.
- The latest reports on decomposition methods: Find them here.
- Are you an economist looking for decomposition tools and research? Look for the links below.
What is Decomposition?
Decomposition methods help us determine what role employment, earnings, transfers, demographics and other factors play in the reduction of poverty and inequality. The research can guide the World Bank's activities as we seek to meet our poverty and inequality reduction goals.
Jobs and Wage Increases Drive Poverty Reduction
Changes in labor earnings were the largest contributor to poverty reduction in a sample of 21 countries, a recent report shows. In 13 of these countries, greater employment or higher earnings explained more than half of the change in poverty.
- Understanding Changes in Poverty (2014)
- Decomposing the Recent Inequality Decline in Latin America (2013)
- Is Labor Income Responsible for Poverty Reduction? A Decomposition Approach (2013)
- Fifteen Years of Inequality in Latin America: How Have Labor Markets Helped? (2013)
- What is Behind the Decline in Poverty since 2000? Evidence from Bangladesh, Peru and Thailand (2012)
- Identification of Sources of Variation in Poverty Outcomes (2012)
- Distributions in Motion: Economic Growth, Inequality and Poverty Dynamics (2010)
- The Microecomomics of Income Distribution Dynamics in East Asia and Latin America.
- Beyond the Oaxaca-Blinder: Accounting for Differences in Household Income Distribution
Using Stata for your decomposition analysis? Go here to learn more about Stata. Below are some Stata commands for decomposition analysis to help your research:
1) Azevedo et. al. Decompositions
Methodology for Azevedo et. al (2013) decomposition gives you a first approximation of the relative weight of labor and non-labor income, as opposed to demographic effects, in explaining the observed changes in poverty and inequality. Within Stata type:
ssc install adecomp
2) BFL Decompositions
Methodology follows Bourguignon, Ferreira and Lustig (2005) to distinguish between distributional changes caused by changes in endowments, returns to endowments, changes in occupational choice; and changes in the geographical, age and gender structure of the population. A beta version of a Stata ado file is available. Please contact Sergio Olivieri or Gabriela Inchauste for more information.
Decomposes changes in poverty into growth and distribution effects. Uses Shapley values. Within Stata type:
a. With standard errors
ssc install dfgtgr
b. Without standard errors
ssc install drdecomp
Decomposes changes in poverty over time into intrasectoral effects, a component due to population shifts and an interaction term between sectoral changes and population shifts. Within Stata type:
ssc install sedecomposition
Decomposes changes in poverty into growth, distribution and price effects. Within Stata type:
ssc install skdecomp
Decomposes changes of inequality over time by income sources. See Table 8 of Poverty & Inequality Module of ADePT: