Finance, Inequality and Poverty: Cross-Country Evidence

1. Finance, Inequality and Poverty: Cross-Country Evidence Thorsten Beck, Asli Demirguc-Kunt and Ross Levine

2. Motivation • High levels of income inequality and poverty around the world • In 2001, 1.1 billion lived on less than one dollar a day • In Thailand, poverty dropped by 90% from 1981 to 2000, while it doubled in Venezuela • While growth helps reduce poverty, it is not enough! • Growth-enhancing policies can have distributional effects: • Raise everyone’s income • Raise primarily incomes of the rich • Raise primarily incomes of the poor

3. Motivation • Negative relationship between inequality and growth often explained with financial market constraints; suggesting redistributive policies • Alternative: financial sector reform that reduces market frictions, lowers income inequality and boosts growth without incentive problems of redistributive policies

4. Our Contribution • Finance is pro-(average) growth … • … but is it also pro-poor? ... Does it boost the growth of the poor more than growth of the average person? • Using a cross-country regressions, we analyze the effect of financial development on: • Income growth of the poor • Changes in income inequality • Changes in Headcount

5. Finance – pro-rich or pro-poor? • Pro-poor • Credit constraints are particularly binding for the poor (Banerjee and Newman,1993; Galor and Zeira, 1993; Aghion and Bolton, 1997) • Finance helps overcome barriers of indivisible investment (McKinnon, 1973) • Finance foster economy-wide openness and competition by facilitating entry (Rajan and Zingales, 2003) • Pro-rich: • Credit is channeled to incumbent and connected and not to entrepreneurs with best opportunities (Lamoreaux, 1986; Haber, 1991)

6. Data – Financial development • Private Credit • Value of credit by financial intermediaries to the private sector divided by GDP • Data averaged over 1960-99 (1980-2000) • Countries with higher levels of Private Credit grow faster • Beck, Levine and Loayza (2000)

7. Data – Dependent variables • Average annual growth rate of the real income of lowest income quintile over 1960-99 for 52 countries • Average annual growth rate of Gini coefficient over 1960-99 for 52 countries • Average annual growth rate in Headcount (share of population with less than $1 a day) over 1980-2000 for 58 countries

8. Methodology Finance and income growth of the poor Finance and changes in income inequality Finance and poverty alleviation

9. Finance and income growth of the poor

10. Finance and the Poor – the economic effect • Income of the poor in Brazil would have grown 4% instead of 0% per year over the period 1960-99, had Brazil had the same level of Private Credit as Korea

11. Finance and changes in Gini

12. Finance and changes in Headcount

13. Finance and Poverty Alleviation – the economic effect • Headcount in Peru would have increased only by 5% instead of the actual 19% per year, had it had the level of financial development of Chile; this would have resulted in a Headcount of 2% in 2000 rather than the actual 15%.

14. Robustness tests Results hold controlling for: • Trade Openness • Inflation • Schooling 1960 • Age dependency ratio • Population growth

15. Simultaneity Bias • Control for reverse causation and simultaneity bias by instrumenting for Private Credit • Legal origin • Latitude • Religion • Tests: • Test of overidentifying restrictions • F-test and adjusted R-squared for first stage

16. Conclusions • Finance is pro-growth and pro-poor! • In countries with better developed financial intermediaries, • income of the poor grows faster • income inequality decreases at faster rate • poverty falls at faster rate • How to foster financial intermediary development? • How to broaden access to financial services?