Inequality and Instability What we learned and why it matters James - PowerPoint PPT Presentation

Inequality and Instability What we learned and why it matters James K. Galbraith and Béatrice Halbach with Aleksandra Malinowska, Amin Shams and Wenjie Zhang UNU-WIDER Conference on Inequality— Measurement, trends, impacts and policies Helsinki, Finland September 5-6, 2014

A Brief Summary The EHII data set is a panel of estimated Gini coefficients for gross household income, derived from measures of cross-sector industrial pay inequality, known as UTIP- UNIDO, which are computed using the between-groups component of Theil's T- statistic.

Extending EHII EHII is calculated by regressing the original Deininger Squire “High Qualitÿ” data set against UTIP-UNIDO, with controls for the share of manufacturing in total employment and dummies for the various income/expenditure concepts present in the DS data set. The coefficient estimates are then used to generate the EHII values. Here is the new regression underlying EHII 2013.

The new EHII panel has 3871 estimates for 149 countries, over the years 1963-2008

Coverage and Estimates By Decade Averages

The charts following compare EHII with other measures for various countries. They were compiled by ransacking the literature for Gini coefficients, and color- coding the results.

Color Coding Black : EHII Green: Market Income Blue: Gross Income Red: Net Income Yellow: Consumption Purple: Not clearly distinguished in the source documents * Light dotted entries represent the Solt SWIID estimates

Estimates Consistent with the Literature

Problematic Estimates

1 5 2 0 2 5 3 0 3 5 4 0 4 5 5 0 5 5 6 0 6 5 D D R S W E T W N D E U P O L H K G A U S R O U M L T F R A S V K I R L I T A L V A D Z A K O R U K R A F G M D A E H I I M i n i m u m , M e a n a n d M a x i m u m Y U G U R Y I R Q A L B I R N B G D Z W E M D G b y C o u n t r y T U R T O N S U R B F A C H L E R I S O M Z M B G T M S D N T U N C O G Y E M U G A N P L K E N B D I T Z A S W Z L S O C M R K H M Q A T M a x i m u m M i n i m u m M e a n

Maximum, Mean, Minimum E H I I G i n i C o e f f i c i e n t s 1 9 6 3 - 2 0 0 8 M i n i m u m , 1 0 t h , 2 5 t h , M e a n , 7 5 t h , 9 0 t h , M a x i m u m 6 5 6 0 5 5 5 0 4 5 4 0 3 5 3 0 M e a n 2 5 M i n i m u m M a x i m u m 2 0 L o w e r U p p e r P e r c e n t i le 1 5 P e r c e n t i le 1 9 6 3 1 9 6 7 1 9 7 1 1 9 7 5 1 9 7 9 1 9 8 3 1 9 8 7 1 9 9 1 1 9 9 5 1 9 9 9 2 0 0 3 2 0 0 7

Global Mean Values EHII Gini Coefficients ` E H I I M e a n V a lu e s 1 9 6 3 - 2 0 0 8 4 4 . 0 4 3 . 5 4 3 . 0 4 2 . 5 e a n 4 2 . 0 M 4 1 . 5 4 1 . 0 4 0 . 5 4 0 . 0 1 9 6 3 1 9 6 7 1 9 7 1 1 9 7 5 1 9 7 9 1 9 8 3 1 9 8 7 1 9 9 1 1 9 9 5 1 9 9 9 2 0 0 3 2 0 0 7

Brief Conclusions The literature on inequality measurement is very messy . In advanced countries the difference between market, gross and net income inequality is typically very large. EHII appears to provide reasonable estimates for gross household income inequality, and a basis for comparisons. It does not capture capital-based incomes well, but this is a problem in only a few countries.

http://utip.gov.utexas.edu Calculations and Charts by Beatrice Halbach Aleksandra Malinowska Amin Shams Wenjie Zhang Support from INET gratefully acknowledged.