Inequality and Growth: From Micro Theory to Macro Empirics
To establish the nature of the link between income distribution and economic growth by means of a standard growth regression, one needs to collapse an entire income distribution into a scalar measure of inequality. Due to data shortages macro-economic research has typically been forced to use the gini coefficient for this purpose. Using a simulation set up we check how well different measures of inequality or poverty succeed in detecting the correct relationship. We find that the gini coefficient might not be the worst of choices, but the comparison of the explanatory power of different inequality measures can help to identify the theoretical mechanism through which inequality affects growth.
|Date of creation:||Sep 2004|
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- Anthony B. Atkinson & Andrea Brandolini, 2000.
"Promise and Pitfalls in the Use of 'Secondary' Data-Sets: Income Inequality in OECD Countries,"
Temi di discussione (Economic working papers)
379, Bank of Italy, Economic Research and International Relations Area.
- Atkinson, A.B. & Brandolini, A., 2000. "Promise and Pitfalls in the Use of 'Secondary' Data -Sets: Income Inequality in OECD Countries," Papers 379, Banca Italia - Servizio di Studi.
- Niko Gobbin & Glenn Rayp, 2004.
"Inequality and Growth: Does Time Change Anything,"
Development and Comp Systems
- N. Gobbin & G. Rayp, 2004. "Inequality and Growth: Does Time Change Anything?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/230, Ghent University, Faculty of Economics and Business Administration.
- Robert J. Barro, 1999. "Inequality, Growth, and Investment," NBER Working Papers 7038, National Bureau of Economic Research, Inc.
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