October 26, 2012 | Contribution by
GLADYS LOPEZ ACEVEDO AND JAVIER ARIAS By Gladys Lopez Acevedo (Senior Economist, Poverty Reduction Group (PRMPR), The World Bank) and Javier Arias (Consultant, PRMPR, The World Bank)
In light of growing evidence that much of the poverty reduction observed in the past decades has been facilitated by the dynamics of labor markets in developing countries, it is more important than ever to understand the links between labor markets and poverty and income inequality. In an effort to do just that, on October 18, 2012, World Bank researchers launched a revamped labor module for labor market diagnostics as part of its free software program – called ADePT (Automated DEC Poverty Tables) - that offers policy makers globally a helping hand in evidence-based decision making.
Maize seed quality control at small seed company Bidasem, by CIMMYT, 2012
What is ADePT-labor?
ADePT-labor is a user-friendly software, part of the ADePT program, which facilitates using micro-data to monitor progress in reducing poverty by making the statistical analysis less resource-intensive. ADePT-labor uses household surveys to provide diagnostics of labor markets outcomes and trends. With the recent upgrade, it now produces indicators around four pillars: (i) labor market performance; (ii) inequality in the labor market; (iii) poverty and labor markets; and (iv) disadvantaged groups.
Labor markets in developing countries have long been recognized for having certain features that differentiate them from those in developed countries. For example, in low-income countries, the majority of workers is self-employed or works in family enterprises, with a relatively small fraction employed in salaried jobs. ADePT-labor was specifically designed to construct, quickly and with minimum error, indicators that help assess current labor market conditions in low- and middle-income countries. It also allows users to assess how labor markets evolve over time. ADePT-labor, through an exhaustive list of tables and figures, highlights the way that jobs and employment transmit the benefits of growth to the poor.
How does it work?
Example 1. In Mexico, where low earnings are prevalent, let's say we want to know whether poverty is highest among households led by an unemployed person versus an employed person, and if so, by how much? To answer that, we would use the sub-module on poverty, which produces poverty rates by labor force status of the head of the household. As Figure 1 shows, we find that the differences in poverty between employed and unemployed individuals are substantial, but poverty among employed is large (about 38 percent), with the prevalence of poverty among labor force status staying about the same between 2009 and 2011. This would send a message to policy makers that poverty reduction strategies also need to target people with jobs. The next step might be examining why people with jobs should have such a high level of poverty.
Figure 1 Mexico’s employed - not just the jobless - suffer high rates of poverty
(Poverty rates by individual employment status of the household head, in percent)
Example 2. Another question might be which economic sectors in Mexico have the highest poverty rates. Using the same poverty sub-module, we can generate Table 1, which shows that poverty is substantially higher in agriculture relative to other sectors. It also shows that the largest increase in poverty rates between 2009 and 2011 occurred in financial and business services.
The revamped ADePT labor is targeted at experienced, and less-experienced, analysts alike. The users' guide provides step by step instructions on processing and loading the datasets, with examples on running the software. It also includes an analytical framework and guides for readers on interpreting tables and figures for each sub-module. For more advanced readers, it contains an analytical appendix with detailed formulas and explanations on constructing indicators. In the past four years, the ADePT team has trained analysts in government, academia, and think tanks from about 30 countries (including Indonesia, Russia, Mexico, and South Africa) on using the program.
For further information contact Javier Arias (firstname.lastname@example.org)
Contributors: Gladys Lopez Acevedo and Javier Arias