Growth, its Sectoral Composition, and Poverty Alleviation

1. Growth, its Sectoral Composition, and Poverty Alleviation

2. The UN Millennium Declaration sparked new interest on understanding how the poor fare in the development process. Do the poor share in economic growth? Strong ideological positions, but at the end of the day this is an empirical question Review some of the recent evidence Emphasis on how the sectoral composition of growth affects the relation between growth and poverty alleviation. The MD and the discussions previous to its formal release increased the interest among the development community on the question on… There are strong ideological positions At the end this is an empirical question which had been hard to address until the mid 90’s by the lack of data Availability of data generated two strands of literature In today’s presentation I will focus on the second strand of literatureThe MD and the discussions previous to its formal release increased the interest among the development community on the question on… There are strong ideological positions At the end this is an empirical question which had been hard to address until the mid 90’s by the lack of data Availability of data generated two strands of literature In today’s presentation I will focus on the second strand of literature

3. Outline Growth and Poverty Heterogeneity and its possible causes Initial conditions The composition of growth Where do we stand?

4. Growth and Poverty Preliminary issues: Who are the poor? Poor are those who cannot afford certain consumption needs: those below some “poverty line” Poverty lines: absolute vs. relative Absolute PL defined in terms of the cost of a bundle of goods (PPP) Relative PL takes into account level of income of the country How do we measure poverty? In general, we use a weighed sum of the number of people below the PL (%) Equal weights (counting the number of poor (%)): Headcount index (H) More weight to the poorest: Poverty Gap, Squared PG, Watts. Everything seems intuitive but in principle the definitions can make a lot of difference If not the consensus, probably most of the literature has focused on the first definition This does not mean that the question is already solved…Everything seems intuitive but in principle the definitions can make a lot of difference If not the consensus, probably most of the literature has focused on the first definition This does not mean that the question is already solved…

5. Growth and Poverty

6. This empirical relation seems a robust pattern of the data: Cross country: Chen and Ravallion (1997): Headcount Dollar and Kraay (2002): Income of 1st quintile Within country, time series Chen and Ravallion (2004) for China Within country, across provinces Datt and Ravallion (1996, 1999, 2002) for India. World Evolution of poverty Chen and Ravallion (1997, 2001): survey data only, common poverty line. Sala-i-Martin (2000): Inequality, DS data + NA Growth and Poverty Perhaps I should also mention the growth and inequality relationship: Most evidence suggest that growth is not associated with changes in inequality (different from the inequality and growth literature): Deninger and Squire (1996), Chen and Ravallion (1997), Easterly (1999), Dollar and Kraay (2002) Evidence is also that most pro-growth policies have little impact on inequality (Dollar and Kraay (2002), Lopez (2004)) exceptions are Barro (2000) and Lundberg and Squire (2003) who show that openness increases inequality. Perhaps I should also mention the growth and inequality relationship: Most evidence suggest that growth is not associated with changes in inequality (different from the inequality and growth literature): Deninger and Squire (1996), Chen and Ravallion (1997), Easterly (1999), Dollar and Kraay (2002) Evidence is also that most pro-growth policies have little impact on inequality (Dollar and Kraay (2002), Lopez (2004)) exceptions are Barro (2000) and Lundberg and Squire (2003) who show that openness increases inequality.

7. Caveats: Data: Measurement error, comparability Econometrics: Mainly reverse causality. Not so obvious Existing evidence from using internal instruments suggests OLS bias is small (Dollar and Kraay, 2002; Lopez, 2004) Unlikely first order issues

8. Heterogeneity On average growth has been associated with poverty declines… but there is important unexplained variation

9. Heterogeneity Cites for this: Ravallion (1997, 2004), Bourguignon (2002), Son and Kakwani (2003)Cites for this: Ravallion (1997, 2004), Bourguignon (2002), Son and Kakwani (2003)

11. Geographic composition (rural-urban) Geographic composition relates to the idea that growth matters more if it occurs where the poor areGeographic composition relates to the idea that growth matters more if it occurs where the poor are

12. Sectoral composition of growth Relation with relative prices (goods and factors) Location also results in focus on agriculture But evidence suggests the link is complex Social accounting: Indonesia: agriculture and services (Thorbecke and Jung, 1996) South Africa: agriculture, services, and some manufacturing (Kahn, 1999) Reduced form relation (Agriculture, industry and services) India: Agriculture and Services (Datt and Ravallion, 1996) Also for India: Industry (Besley et al. 2004) China: Only Agriculture (Chen and Ravallion, 2004) Taiwan: Industry (Warr and Wang, 1999) Only partial support for agriculture

13. Some remaining questions: How general are these results? Why does agriculture matter? What can explain the heterogeneous results among countries? What is the impact of aggregation? “The composition of growth matters for poverty alleviation” (Loayza and Raddatz, 2005) Cross-country analysis of the relation between the composition of growth and poverty alleviation Deal with aggregation issues (disentangle what is inside Industry) Focus on a specific mechanism: composition of growth and changes on real unskilled labor wages. Sectoral composition of growth

14. Sectoral composition of growth

15. Six sectors dissagregation Sectoral composition of growth

16. Why would some sector’s growth be more poverty reducing? Model: Sectoral Growth ? increases in real unskilled wages ? poverty reduction Two technologically different sectors used to produce a final good (GDP) Poor abundant in unskilled labor Standard neo-classical framework. No dualism, perfectly mobile labor

17. Simplest way to link wage growth and poverty consistent with earlier literature

19. More formal test of predicted relation:

21. Sectoral composition matters: Growth in sectors that are more intensive in the use of unskilled labor in a given country has a larger impact in poverty alleviation (e.g. 4.4 vs -1.26) It’s not agriculture itself: Agriculture matters to the extent that it is labor intensive Other results: How you measure labor intensity matters Results hold for more bottom sensitive measures (PG, SPG) Robust to including interaction with initial inequality Poverty change decomposition:

22. Where do we stand? Strong empirical regularity that growth is associated with poverty declines and has explained the bulk of the decline in last 20 years This does not mean that distributional changes do not matter There is heterogeneity in the response of poverty to growth Initial conditions can explain part of it But the composition of growth also has an important role Growth in sectors that are more intensive in unskilled labor is more poverty reducing No basis for distortionary industrial policy (the level effect is still there and all sectors contribute) But removing some distortions may yield important results Neglect of basic infrastructure for agricultural sectors Impediments to labor mobility Results also shed light on expected poverty reductions resulting from particular types of growth that may require counter-balancing distributive policies