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Measuring Inequality. A practical workshop On theory and technique. San Jose, Costa Rica August 4 -5, 2004. Panel Session on: Introduction and Overview. by James K. Galbraith and Enrique Garcilazo. The University of Texas Inequality Project. http://utip.gov.utexas.edu. Session 1.

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Measuring Inequality

A practical workshop

On theory and technique

San Jose, Costa Rica

August 4 -5, 2004


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Panel Session on:

Introduction

and

Overview


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by

James K. Galbraith and Enrique Garcilazo

The University of Texas Inequality Project

http://utip.gov.utexas.edu

Session 1


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The Classical Kuznets Hypothesis

Kuznets’ hypothesis of a relationship between income levels and inequality. If this hypothesis holds, either case in the previous figure may be observed from time to time, but neither will hold generally. Conceiçao’s idea of an “augmented Kuznets hypothesis is sketched with a dashed curve.



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Basic Question: Has Inequality been Rising or Falling? Three ways to measure it, per Milanovic, 2002

  • Un-weighted Between-Country

    (has been rising in all studies)

  • Weighted Between-Country

    (has fallen because of China)

  • Within-country “True”(disputed territory)

?


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The Economist compares inequality types 1 and 2,

1980-2000.

(from Stanley Fischer, 2003 Ely Lecture)


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Existing studies of “true” world income inequality give conflicting results, recently surveyed by B. Milanovic

Including Sala-i-Martin’s claim that inequality has been steadily declining…based on Deininger and Squire.

Figure borrowed from Milanovic


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Comparing Coverage: Deininger and Squire conflicting results, recently surveyed by B. Milanovic

Version of D&S used by Dollar and Kraay, “Growth is good for the poor.”


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The D&S data are heterogeneous for North America and Europe, but homogeneous for Asia

Note the low inequality registered for Indonesia and India, comparable to Europe and Canada.

The fact that South Asia uses expenditure surveys while Europe uses income surveys is clearly

relevant, but how to make an adjustment?


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Elementary economics suggests these differences in inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility.


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Indonesia and India have highly inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility. unequal manufacturing pay. So how do they arrive at highly equal D&S measures – more equal than Australia or Japan? Through strong redistributive welfare states? Probably not. Or, if low Ginis in those countries reflect egalitarian but impoverished agriculture – as many who use these data believe -- then why are the D&S Ginis so high in agrarian Africa?


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Inequality in Spain, as reported by D&S inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility.

HGI: Household Gross Income

HNE: Household Net Expenditure


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Rank and Distribution of D&S Gini for 20 OECD countries inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility.


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The U.T. Inequality Project inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility.

  • Measures Global Pay Inequality

  • Uses Simple Techniques that Permit Up-to-Date Measurement at Low Cost

  • Uses International Data Sets for Global Comparisons, especially UNIDO’s Industrial Statistics

  • Has Many Regional and National Data Sets as well, including for Europe, Russia, China, India, and the U.S.


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General Technique inequality are implausible. Europe has an integrated economy with free trade, free capital flow, nearly equal average incomes (between, say, France and Germany) and factor mobility.

We use Theil’s T statistic, measured across sectorswithin each country, to show the evolution of economic inequality. You can do this with many different data sets, including at the regional or provincial level. International comparisons are facilitated by standardized categories, for which sources include UNIDO and Eurostat. Our global pay inequality data set is calculated from UNIDO’s Industrial Statistics, and gives us ~3,200 country-year

Observations.



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Comparing Coverage II ….

UTIP coverage count for this table is based on UNIDO ISIC 2001 edition only, where matching data for GDP per capita also available; total UTIP coverage is about 3200 observations. All UTIP calculations presented here are by Hyunsub Kum.


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These maps rank countries by comparative measures of inequality over a long historical period, with red and orange indicating relatively low inequality, yellow and green in the middle, and light and dark blue indicating the highest values.


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Note that the UTIP-UNIDO measures are homogeneous for Europe, North America, and South America, but highly heterogeneous for Asia.


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Inequality and Economic Growth…. Europe, North America, and South America, but highly heterogeneous for Asia.


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6. Manufacturing Wage Inequality in Mexico Europe, North America, and South America, but highly heterogeneous for Asia.Jan. 1968-Oct.1999

Using the between group Theil Index of dispersion for 9 manufacturing sectors in Mexico, we can compute the evolution of inequality for over 30 years for this country.


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7. Inequality and the Presidents in Mexico Europe, North America, and South America, but highly heterogeneous for Asia.


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8. Wage Inequality and Five External Events Europe, North America, and South America, but highly heterogeneous for Asia.


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9. Wage Inequality and Peso Devaluations Europe, North America, and South America, but highly heterogeneous for Asia.


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Type “Inequality” into Google to find us on the Web Europe, North America, and South America, but highly heterogeneous for Asia.


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