1. Openness, growth, and inequality: It’s (partly) how you look at it
Mattias Lundberg
18 June 2002

2. Openness, growth, and inequality
No robust universal trends
No fixed relationships
No Kuznet’s law
Sometimes up, sometimes down
Sometimes concave, sometimes convex
What you see depends on WHERE and HOW you look
No fixed relationships –
No Kuznets law – what my mother-in-law would call a “pie-crust” law: easily made, easily broken.
L&S tried to find Kuznets curves for 47 countries: 8 Kuznets, 11 inverse Kuznets, and 30 with no relationship.

3. Trends in inequality, 85 countries
This shows the initial and final (5-year average) Gini coefficients for 85 countries. There is no obvious trend. The numbers towards the bottom are the mean overall trends among those countries for which we have data beginning in each 5-year period. For those countries for which we have data beginning in the period , the Gini has decreased on average four one-hundredths of one point each year. For those countries that only join the sample in , the Gini has increased on average 1.2 points per year.

4. Openness and growth (dependent variable – across-period growth in per capita GDP)
This is a regression of income on openness, in differences. The openness measure is instrumented by the twice-lagged level. When the regression is population-weighted, as in Dollar and Kraay, greater openness leads to faster growth.

5. Openness and growth (dependent variable – across-period growth in per capita GDP)
When the regression is re-run on unweighted data, the relationship disappears. Also when we choose (arbitrarily) to weight the data by Gini coefficient.

6. Openness and growth (dependent variable – across-period growth in per capita GDP)
Most importantly, even the population-weighted regressions are heavily influenced by China. Without China, there is no relationship.

7. Openness and inequality (dependent variable – across-period change in Gini coefficient)
Similar story with regard to inequality (again in first differences, with openness instrumented by the twice-lagged level). Population-weighted regressions find that openness is bad for distribution, but not the unweughted regressions.

8. Openness, growth, and inequality (dependent variable – across-period change in Gini coefficient)
Here we try to find an aggregate Kuznets curve, again in differences. Surprisingly, what we get is an inverse Kuznets curve, but it’s not robust.

9. Openness, growth, and inequality (results from Lundberg and Squire, 2001)
In Lundberg and Squire (2001), we try to find the policies that get influence BOTH outcomes. We find that the Sachs-Warner measure of trade openness leads to faster growth and greater inequality, but this result is not robust to other measures of openness.

10. Openness, growth, and inequality
Growth and distribution both driven by policies (such as openness) and environment
Empirical results are not often robust
Inequality changes very little over time
Hard to find significance in cross-country regressions
The Kuznets curve is missing the point. The growth of income, and its distribution are at least in part the results of the same process.

11. Openness, growth, and inequality (results from Lundberg and Squire, 2001)
The point the Lundberg and Squire paper was trying to make is that these two are simultaneously determined. We couldn’t find any variable that was uniquely significant only to one outcome.

12. Openness, growth, and inequality
The search for causality between growth and inequality is futile:
A mechanistic relationship that ignores the role of policy
The two outcomes are clearly jointly determined
Policies designed to advance one will affect the other

13. Openness, growth, and inequality
More important to understand:
The conditions under which openness leads to growth
The conditions under which openness leads to inequality-reducing growth
How more people can profit from the benefits of increased openness

14. Openness, growth, and inequality
Case studies offer alternative (possibly superior?) research technique, eg:
Take 10 countries that have opened to trade,
What has happened to growth?
What has happened to distribution?
What intermediating policies/factors drive the difference?
Finally, a suggestion (or plea):