Galbraith inequality and instability; a study of the world economy just before the great crisis (2012)

Inequality and Instability This page intentionally left blank Inequality and Instability A Study of the World Economy Just Before the Great Crisis JAMES K GALBRAITH Oxford University Press, Inc., publishes works that further Oxford University’s objective of excellence in research, scholarship, and education Oxford New York Auckland Cape Town Dar es Salaam Hong Kong Karachi Kuala Lumpur Madrid Melbourne Mexico City Nairobi New Delhi Shanghai Taipei Toronto With offices in Argentina Austria Brazil Chile Czech Republic France Greece Guatemala Hungary Italy Japan Poland Portugal Singapore South Korea Switzerland Thailand Turkey Ukraine Vietnam Copyright © 2012 by James K Galbraith Published by Oxford University Press, Inc 198 Madison Avenue, New York, New York 10016 www.oup.com Oxford is a registered trademark of Oxford University Press All rights reserved No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Oxford University Press Library of Congress Cataloging-in-Publication Data Galbraith, James K Inequality and instability : a study of the world economy just before the Great Crisis / James K Galbraith.—1st ed p cm Includes bibliographical references ISBN 978-0-19-985565-0 Income distribution Economic policy Globalization—Social aspects Power (Social sciences) Economic development—Research Global Financial Crisis, 2008–2009 I Title HC79.I5.G35 2012 339.2—dc23 2011026835 Printed in the United States of America on acid-free paper for Luigi Pasinetti inspiration and friend This page intentionally left blank Kepler undertook to draw a curve through the places of Mars, and his greatest service to science was in impressing on men’s minds that this was the thing to be done if they wished to improve astronomy; that they were not to content themselves with inquiring whether one system of epicycles was better than another, but that they were to sit down to the figures and find out what the curve in truth was —Charles Sanders Peirce (1877) This page intentionally left blank CONTENTS Acknowledgments CHAPTER xiii The Physics and Ethics of Inequality THE SIMPLE PHYSICS OF INEQUALITY MEASUREMENT THE ETHICAL IMPLICATIONS OF INEQUALITY MEASURES PLAN OF THE BOOK CHAPTER 13 14 The Need for New Inequality Measures THE DATA PROBLEM IN INEQUALITY STUDIES 20 20 OBTAINING DENSE AND CONSISTENT INEQUALITY MEASURES GROUPING UP AND GROUPING DOWN CONCLUSION CHAPTER 29 36 43 Pay Inequality and World Development WHAT KUZNETS MEANT 47 47 NEW DATA FOR A NEW LOOK AT KUZNETS’S HYPOTHESIS 50 PAY INEQUALITY AND NATIONAL INCOME: WHAT’S THE SHAPE OF THE CURVE? 62 GLOBAL RISING INEQUALITY: THE SOROS SUPERBUBBLE AS A PATTERN IN THE DATA 69 CONCLUSION APPENDIX: CHAPTER 73 ON A PRESUMED LINK FROM INEQUALITY TO GROWTH Estimating the Inequality of Household Incomes ESTIMATING THE RELATIONSHIP BETWEEN INEQUALITIES OF PAY AND INCOME 82 FINDING THE PROBLEM CASES: A STUDY OF RESIDUALS 87 74 81 310 Index between-household inequality, betweencounty inequality compared to, 141, 142f between-industry earnings inequality, 128 between-county inequality compared to, in US, 140–41 high-growth sectors contributing to, 135–37, 136t for high-growth sectors in United States 1991–2001, 136–37, 137f Lorenz curves for United States, 131–32, 131f politics and, 139–40 Theil statistic measuring , 129–30, 130f, 133–34, 133f United States 1990–2007 rising , 134–35, 134f in United States 2000–2007, 138–39, 139f between-state inequality, 141–43, 143f Blanchard, Olivier, 201–2 Bluestone, Barry, 125 Bound, John, 125 Brady, Henry E., 152 Brandolini, Andrea, 23 Brazil, 17, 88f, 89, 291 datasets for, 256 finance sector in, 263–64, 263f, 264f, 266–67 as global power, 254 income inequality in Argentina compared to, 254–55, 265–67 inequality across regions, 1996–2007 in, 264–65, 266f, 267f inequality across sectors, 1996–2007 in, 262–64, 263f, 264f, 267f inequality decline, mid-90s in, 252, 263 pay inequality from 1996–2007 in, 261–65, 263f, 264f, 266f, 267f Plan Real in, 253 politics in, 253–54 poverty in, 262–63 Brazilian Industry Classification (CNAE), 256 Brazilian Institute of Geography and Statistics (IBGE), 256 Bretton Woods fixed exchange rate system, breakdown of, 71 Bureau of Economic Analysis (BEA), 128–29 coding regimen shifts of, 130 income definition of, 141 state-level income inequality datasets from, 159 Bush, George W., 134, 139–40 on income inequality, 147 inequality measures of, 292–93 Bush boom sectors, inequality among , 138–39, 139f Bush-Gore election, 155–58, 156t, 157t, 158t Canada, income inequality in manufacturing pay for Finland and, 60t, 61 canonical root, 204 canonical score and pseudoscore correlations for Austria GDP, 228t for Austria investments, 229t for Belgium, 230t for Denmark, 229t, 232t for European wage flexibility dataset, 225t–233t for Finland, 231t for France, 229t for Greece, 231t for Luxembourg , 230t for Netherlands, 229t for Norway, 231t, 233t for oil price rate of change, 233t for Portugal, 226t for Sweden, 231t, 233t for Switzerland, 229t, 232t for UK , 227t canonical scores, 205–7 capital flow Chinese speculative sectors and, 247–49 Chinese trade and, 244–46 capital markets, income inequality driven by, 13 Cardoso, Fernando Henrique, 253–54, 261–62, 291 Castro, Raul, 287 Census Bureau, 126, 132, 141 CPS, 132, 158 household income inequality measures of, 128–29 methods of, 158 urbanization quantified by, 155 Chavez, Hugo, 269 Cheibub-Gandhi index , 105, 111 for UTIP-UNIDO dataset, democracy compared to dictatorship, 118, 118t China, 17 Beijing Olympics, 248 capital flow and trade in, 244–46 capital flow into speculative sectors in, 247–49 economic growth in, 235–36 exports to GDP of, 240, 242 Index exports upgraded in, 242–43 finance and trade rise of 2002–2006 in, 240–44, 242t foreign exchange transactions within, 245–46, 246t GDP overstatements in, 248 Great Crisis of 2008 shocking , 249 gross capital formation in, 247–48, 247t harmonious society object of, 235, 249 “hot money” inflows in, 245–46, 250n10 income inequality in, 8–9 Kuznets curve shape for, 73–74 Kuznets’ inequality and industrialization argument for, 51–52 manufacturing employment in, 239–40, 239t manufacturing pay in, 236 market socialism in, 243–244 PPP in, 18n5, 250n8 real estate sector in, 248–49, 248t stock market boom in, 245 VAT rebates in, 246 wage rates in, 244 Chinese inequality causes of, 235 contribution between sectors to, 240, 241f economic growth slowing , 249 evolution through 2007 of, 236–40, 237f export boom and, 236, 240–44, 242t interprovincial, 237–38, 238f manufacturing employment and, 240 Theil statistic for provinces and, 237, 237f civil war periods, countries with, 117 Clinton, Bill, 134, 139 cluster analysis discriminant function analysis for, 203–4, 206–8, 207f for European wage flexibility dataset, 203, 206–11, 207f, 208f, 209f, 215–223 Ward’s method for, 203 CMEA See Council of Mutual Economic Aid CNAE See Brazilian Industry Classification coarse disaggregation, 31 Commodity Futures Modernization Act of 2000, 293 communism, 16, 104 classification of, 107 countries classified as, 116 Cuba’s government of, 269 inequality in, 108, 109t, 110t, 112t Convertibility Plan, in Argentina, 253, 260 Council of Mutual Economic Aid (CMEA) Cuban dependence on, 273–74, 283 311 Soviet Union fall and disintegration of, 272 CPA See Agricultural Production Cooperatives CPS See Current Population Survey Created Unequal (Galbraith), 13, 16, 19n10, 56, 130, 200 gradual success of, 126 credit financial crisis and, global, 18, 74 instability and, 18 in Ireland, 177 lack of study on, UK boom in 1990s due to, 213 United States and bubbles in, 148 Cuba, 18 agriculture as percentage of GDP in, 283–84, 284t CMEA dependence of, 273–74, 283 communism in government of, 269 CPA in, 284 economic evolution 1991–2005 of, 272–78 economic restructuring by 1996 in, 276–77, 277f economy and external shock effects on, 273–74, 273f exports by groups of products from 1985–2004 in, 282–83, 283f exports from 1990–2004 in, 277–78, 278t manufacturing employment in, 271 manufacturing sector as percentage of GDP in, 282, 283t mining industry harmed by crisis in, 282, 283f social services sector within total public spending in 2004 in, 281–82, 282t “Special Period in Times of Peace”, 274, 275t–276t, 276, 281, 287 sugar industry impact of crisis in, 277, 282–83, 283f tourism boom in, 270, 276, 284 UBPC in, 284 wage rate across sectors in, 270–71 Cuban pay inequality dataset calculations for, 270–72 government economic policy and, 286–87 by region, 285–86, 285f, 286f by sector, 279–85, 280f Soviet Union collapse and, 279 Current Population Survey (CPS), 132 limitations of, 158 312 Index da Silva, Luiz Ignácio (Lula), 254, 261–62, 267, 291 datasets See also DS datasets; European wage flexibility dataset; grouped data; Luxembourg Income Studies; political regime data; sector datasets; semi-aggregated economic datasets; survey data; UTIP Estimated Household Income Inequality dataset; UTIP-UNIDO dataset for Argentina, 256 Barro-Lee, 75 bias in, 88 for Brazil, 256 clarity of, 51 combining , 81–83 comparative, 11 consistency of, 23 hierarchical, 10 inequality measurement problems with, 20–29 intercountry comparability of, 32–33 Kuznets’ inequality and industrialization argument with manufacturing pay, 53, 59t–60t limitations of, 14 national compared to transnational, 69–70 noisy, 6, 51, 79n7 old questions reexamined with new, 100 Penn World Tables, 58, 75 REGIO, 173, 183 running mean smoother applied to, 65, 65f scope and restrictions of, 12 for state-level income inequality from BEA , 159 WIDER , 21, 29 debt, income inequality and, Deininger, Klaus, 20 See also DS datasets democracy, 15 authoritarian regime compared to, 104 Cheibub-Gandhi index for UTIP-UNIDO dataset comparing dictatorship to, 118, 118t classification of, 114 dummy variables for, 106–7 Hadenius regime classification for UTIP-UNIDO dataset comparing dictatorship to, 119–20, 121t inequality in various types of, 109–11, 109t, 110t, 112t labor market regulation in, 101 median-voter mechanism for, 101 political competition for public support in, 101 political science on inequality and, 101–5 Polity/Freedom House index for UTIP-UNIDO dataset comparing dictatorship to, 119, 119t pseudo-, 107, 109t, 110t, 112t recent, 106, 109–11, 109t, 110t, 112t transitions to, 103 World Bank index for UTIP-UNIDO dataset comparing dictatorship to, 119, 120t Democratic Party, 16–17 election characteristics favoring , 155 inequality influencing voter choice for, 164 regional data and, 40 Republican Party ideals and interests compared to, 153–54, 162 Denmark, 36 canonical score and pseudoscore correlations for, 229t, 232t developing countries DS datasets for, 22–23 pay inequality gaps for, 61 development See economic development dictatorship, 15–16 Cheibub-Gandhi index for UTIP-UNIDO dataset comparing democracy to, 118, 118t classification of, 107 countries classified as, 115–16 Hadenius regime classification for UTIP-UNIDO dataset comparing democracy to, 119–20, 121t inequality in, 108, 109t, 110t, 112t Polity/Freedom House index for UTIP-UNIDO dataset comparing democracy to, 119, 119t World Bank index for UTIP-UNIDO dataset comparing democracy to, 119, 120t disaggregation coarse compared to fine, 31 in inequality measurement, 10–11 discriminant function analysis for cluster analysis, 203–4, 206–8, 207f eigenvalue from, 204, 224t eigenvalues and canonical correlations for, 224t discriminating variable, 204 dispositional properties of, political regimes, 105 distribution of income, econophysics for, 41 Index DS datasets accuracy pitfalls of, 94 consistency problems with, 23–24 for developing countries, 22–23 expenditure surveys compared to income surveys in, 24, 24t–26t high-quality criteria for, 44n1 Hong Kong Gini coefficient measures in, 88f, 89–90 household income inequality trends in UTIP-EHII compared to, 94–95, 94f, 95f household-size adjustments in, 44n4 impact of, 21 inequality trends for OECD and nonOECD countries in, 93, 93f LIS compared to, 29 for OECD inequality measurement, 21–23, 22f regional differences influencing , 29 regression analysis with dummy variables for, 27–29, 28t regression analysis with dummy variables for political regimes using , 111–12, 112t South Africa Gini coefficient measures in, 88f, 89 UNIDO Industrial Statistics predicting , 33 UTIP-EHII advantages over, 92, 94–95 UTIP-EHII compared with Gini coefficients of, 87–88, 88f, 92 UTIP-UNIDO datasets combining with, 81–87, 85t, 86t UTIP-UNIDO datasets diverging from, 60t, 61, 62f WIDER dataset compared to, 21 Duesenberry, James, 18n4 economic boundaries, globalization changing , 179 economic development Gini coefficient advantages and, 45n22 inequality and, 49–51, 62, 69, 74–76, 77t, 78t pay inequality relationship with, 51–52 economic growth in China, 235–36 Chinese inequality slowed by, 249 inequality influencing , 5–6 pay inequality increases improving , 76 United States and war driving , 140, 149 economic inequality See income inequality economy See also global economy 313 Cuba and external shock effects on, 273–74, 273f Cuba from 1991–2005 evolution of, 272–78 Cuban pay inequality and government policy for, 286–87 Cuba restructuring by 1996 of, 276–77, 277f government type impact on, 15–16 income inequality and structure of, 50–51 inequality and complexity of, 49–50 interdependence of, 11–12 intersectoral transitions in, 48 econophysics, 19n9 for distribution of income, 41 education, for employment, 140 EHII See UTIP Estimated Household Income Inequality dataset eigenvalue, 204, 224t elections Bush-Gore, 155–58, 156t, 157t, 158t countries classified with free multiparty, 114–15 Democratic Party favorable characteristics for, 155 factors influencing outcomes of, 152 income influence on, 16–17 inequality suppressing turnout for, 39–40, 155 in pseudo-democracy countries, 115 state-level income inequality influencing presidential, 162 subverting , 103 voter choice in, 153 voter repression in, 153 Electoral College (United States), 16, 39 employment See also manufacturing employment; unemployment between-county inequality and, 148f education for, 140 income inequality relationship with, 147–48, 148f without inflation, 146 under-, 168 ethics, inequality measurement and, 13–14 Euro, 171, 177 Europe cost-of-living across, 197n18 dependent variables within, 200 inequality and unemployment in United States compared to, 179–81 inequality in, post-1974, 168–70 inequality measurement of, with Theil statistic, 38 314 Index Europe (continued) integration of, 168–69 labor markets in, 17, 199 MNC investment in, 202 pay inequality reduced in, 181 pay rate rigidity in, 17 regional and sector data needed for, 37 unemployment in, 39, 42–43 unemployment in United States compared to, 165 United States income inequality compared to, 37–38 wage flexibility and, 166, 182 wage rate summary statistics for, 192t youth enabled in, 182 European Central Bank, 178 European colonies countries classified as, 117 government of, 107 European multinational corporations, 199 European region-based unemployment and inequality fixed-effects model negative effects for small countries in, 176–77, 177f population components in, 174, 175t by region and date, 195t region list, 185t–189t sensitivity analysis for, 191t time effects in, 177–78, 178f variables for, 173 variance in, 174, 176t European unemployment See also regionbased unemployment demand policies for, 181–82 European wage rigidity causing , 201 European wages rising and falling with, 213 inequality-based theory of, 167–70 labor market policy affecting , 165–66, 199 LMF hypothesis of, 201–2, 213 Meidner-Rehn argument for, 169–70 monetary policy affecting , 166–67 MP hypothesis on, 202 national fixed-effects for, 183t oil crises causing , 168, 198 place and, 166 policy implications for, 181–83 sensitivity analysis for, 191t supply policies for, 182 time fixed-effects for, 184t European wage flexibility dataset accessing , 203–6 canonical score and pseudoscore correlations for, 225t–233t cluster analysis for, 203, 206–11, 207f, 208f, 209f, 215–223 country codes for, 214t discriminant function analysis for, 224t forces influencing , 211–12, 212t pseudoscores clarifying , 206–7, 207f, 208f, 209f sector codes for, 215t variations in, 213 European wages co-movement of changing , 203 currency adjustments and, 199–200 European unemployment from rigidity of, 201 European unemployment rising and falling with, 213 forces affecting , 211–12, 212t rigidities of, 198–99 variability of, 200 Eurostat, 170 REGIO dataset, 173, 183 Eurozone, 17 expenditure surveys conversion issues for, 23 income surveys compared to, 24, 24t–26t in South Asian countries, 88 exports China upgrading , 242–43 Chinese GDP to, 240, 242 Chinese inequality and boom of, 236, 240–44, 242t in Cuba 1990–2004, 277–78, 278t in Cuba by groups of products from 1985–2004, 282–83, 283f market socialism and, 243–44 principles of, 241 fascism, 104 Faure, Felix , 289 Fed See Federal Reserve Board Federal Administration of Public Revenues, Argentina (AFIP), 256 Federal Reserve Board (Fed), 4–5 on monetary policy affecting inequality, 42 finance sector, 134f, 135 in Brazil, 263–64, 263f, 264f, 266–67 China rise of 2002–2006 in trade and, 240–44, 242t financial crisis credit and, inequality linked to, 3–4 United States combating , 292–93 fine disaggregation, 31 Finland, 210 Index canonical score and pseudoscore correlations for, 231t income inequality in manufacturing pay for Canada and, 60t, 61 fixed-effects modeling , 66–67, 66t, 68f See also European region-based unemployment and inequality fixed-effects model European unemployment, national, 183t European unemployment, time, 184t for global inequality, 70–71, 71f, 71t heteroscedasticity of, 80n23 for voter choice, 160–61, 161t for voter turnout, 160–61, 161t Forbes, Kristin J., 74–76 foreign exchange transactions, within China, 245–46, 246t France, 174 canonical score and pseudoscore correlations for, 229t Freedom House index , 104, 111 for UTIP-UNIDO dataset, democracy compared to dictatorship, 119, 119t free multiparty elections, 114–15 Friedman, Milton, G20, 254 Garcilazo, Enrique, 173 GDP See gross domestic product GDPPC See gross domestic product per capita geographic stratification of incomes, 154–55 for state-level income inequality, 163–64 Germany, 123n18, 176 Austrian wage rate compared to, 193t, 196 Gini coefficient, 15 between-region, 38 comparability of, 150n13 economic development and advantages of, 45n22 Hong Kong DS dataset measures with, 88f, 89–90 income inequality and, 35 in integer units, 98n7 South Africa measures in DS dataset with, 88f, 89 for state-level income inequality and voter turnout, 160 Theil statistic compared to, 82 UTIP-EHII compared with DS datasets and, 87–88, 88f, 92 Glass-Steagall Act, repeal of, 293 global credit, 18, 74 315 global economy intersectoral transitions in, 50 Kuznets’ inequality and industrialization argument and, 51 Soros on post-1980, 73 super bubble from 1980–2000 in, 290 global finance, pay inequality and, 73 global inequality factors affecting , 289–90 fixed-effects modeling for, 70–71, 71f, 71t government willingness to affect, 290–91 Kuznets curve and, 74 as macroeconomic, 73–74 national studies confirming statistics for, 290 rising , 69–73, 292 time effects on, 70–72, 71f, 71t 2001 factors halting rise in, 72 unemployment and, 291 globalization economic boundaries changing with, 179 inequality rising with, 97 Gonzales, Elian, 288n9 Gore-Bush election, 155–58, 156t, 157t, 158t government See also political regimes Cuban pay inequality and economic policy of, 286–87 Cuba’s communism, 269 economy relationship to type of, 15–16 of European colonies, 107 global inequality measures and willingness of, 290–91 income inequality influence of type of, 100 Gradstein, Mark, 102–3, 122n6 Great Crisis (2008), 140, 149, 182 China shocked by, 249 housing boom prior to, 135 Great Depression, The Great U-Turn (Bluestone & Harrison), 125 Greece, 190 canonical score and pseudoscore correlations for, 231t Greenspan, Alan, 147 gross capital formation, in China, 247–48, 247t gross domestic product (GDP), 58 canonical score and pseudoscore correlations for Austria, 228t Chinese exports to, 240, 242 Chinese overstatements with, 248 Cuban agriculture as percentage of, 283–84, 284t 316 Index gross domestic product (continued) Cuban manufacturing sector as percentage of, 282, 283t inequality measurement with, 63–69, 65f, 65t, 66t, 68t gross domestic product per capita (GDPPC), 63, 65t, 79n20 grouped data inequality measurements with, 8–9 MECE, 30 regional changes between, 31–32 for semi-aggregated economic datasets, 30–31 for state-level income inequality, 158–59 survey data compared to, 14 Guonan Ma, 245 Hadenius regime classification, 111 for UTIP-UNIDO dataset, democracy compared to dictatorship, 119–20, 121t Hale, Travis, 39 Harris, John, 167–68 Harrison, Bennett, 125 HGI See household gross income hierarchical datasets, for inequality measurement, 10 high-growth sectors between-industry earnings inequality from, 135–37, 136t between-industry earnings inequality in United States 1991–2001 for, 136–37, 137f Bush boom sectors, 138–39, 139f wage rate in United States from 2003– 2007 in, 137–38, 138t HNE See household net expenditure HNI See household net income Hong Kong, DS dataset Gini coefficient measures for, 88f, 89–90 “hot money,” in China, 245–46, 250n10 household gross income (HGI), 24 in Spain, 27, 27f household income inequality Census Bureau measure for, 128–29 global, 96–97 missing information with, 82 1990s rise in, 126 OECD and non-OECD countries and rise of, 93–96 UTIP-EHII trends compared to DS dataset for, 94–95, 94f, 95f UTIP-UNIDO dataset measuring , 87 household net expenditure (HNE), 27, 27f household net income (HNI), 24 IBGE See Brazilian Institute of Geography and Statistics identity by industry, in United States, 132 income See also distribution of income BEA definition of, 141 between-county inequality by selected years and, 145–46, 145t elections based on, 16–17 geographic stratification of, 154–55 income inequality’s relationship with rise in, 49–51, 62, 69 personal, 150n16 property, 46n30 region-based unemployment affected by relative, 174 UTIP-EHII for non-OECD countries by level of, 96, 96f income inequality See also between-industry earnings inequality; household income inequality; inequality in Argentina compared to Brazil, 254–55, 265–67 Bernanke on, 147 Bush on, 147 capital markets impact on, 13 in China, 8–9 debt and, determinants of, 83–84 economic structure and, 50–51 employment relationship with, 147–48, 148f Gini coefficient format for, 35 global measurement of, government type influencing , 100 gross-net variables for, 84, 85t income rises relationship with, 49–51, 62, 69 macroeconomic dimensions of, in manufacturing pay for Canada and Finland, 60t, 61 in manufacturing pay for United States and UK , 58, 59t, 61 MFGPOP and, 84–85, 85t, 86t, 87 most probable distribution of, 135 Paulson on, 146 pay inequality relationship to, 82–87, 85t, 86t, 127 POPGROWTH and, 83–85, 85t, 86t power law for, 135 regional data discrepancies for, 91 regional data under- and over-estimation of, 90, 90f research methods for, 7–8 Index “skill-bias” hypothesis for United States and, 19n10 stock market influence on, 127 study of, 6–7 sustainability of, 13 technological changes and, 126 in United States, manufacturing pay compared to unemployment, 41–42, 42f in United States compared to Europe, 37–38 United States components of, 52, 146–48 urbanization and, 84–85, 85t, 86t income paradox in voting inequality and, 162–64 multilevel model for, 162 state-level income inequality and, 162–63, 163f income surveys conversion issues for, 23 expenditure surveys compared to, 24, 24t–26t industrialization See also Kuznets’ inequality and industrialization argument of agriculture, 47 United States inequality in, 56 inequality See also between-county inequality; Chinese inequality; European region-based unemployment and inequality fixed-effects model; global inequality; income inequality; Kuznets’ inequality and industrialization argument advanced technology and, 49–50 of Argentina boom and nonboom sectors 1994–2007, 258, 259f in Argentina by regions, 1994–2007, 260, 261f Argentina post-2001 decline in, 252 authoritarian regime associated with, 102 of Brazil across regions from 1996–2007, 264–65, 266f, 267f of Brazil across sectors from 1996–2007, 262–64, 263f, 264f, 267f Brazil mid-90s decline in, 252, 263 in “Bush boom” sectors, 138–39, 139f Bush’s measures to combat, 292–93 in communism, 108, 109t, 110t, 112t in democracy types, 109–11, 109t, 110t, 112t Democratic Party voter choice and, 164 in dictatorships, 108, 109t, 110t, 112t in DS datasets for OECD and non-OECD countries, 93, 93f economic development and, 49–51, 62, 69 317 economic growth influenced by, 5–6, 74–76, 77t, 78t economic theory neglect of, election turnout suppression and, 39–40, 155 European unemployment theory based on, 167–70 Europe compared to United States with unemployment and, 179–81 in Europe post-1974, 168–70 Fed on monetary policy and, 42 financial crisis linked to, 3–4 global concern for rising , 13 globalization and rising , 97 income paradox in voting and, 162–64 of industrialization in United States, 56 intersectoral transitions and, 74 in Islamic Republics, 108, 109t, 110t, 112t in IT sector, 136–37, 137f, 139f Kuznets’ inequality and industrialization argument sources of, 128–29 LIS showing OECD rise in, 61, 62f in manufacturing pay, 52–53 political regime type effect on, 108–13, 109t, 110t, 112t political science on democracy and, 101–5 region-based unemployment and, 170–71 skill-biased technological change and, 125 in social democracy, 16 social welfare and problematic indicator of, 140 unemployment correlated to, 38–39, 197n6 United States historical perceptions of, 124–25 voter choice and, 153 in voter choice and turnout in Bush-Gore election, 155–58, 156t, 157t, 158t voter choice influenced by cycle-to-cycle changes in, 161 vote repression and, 153 wage rank and changes in, 55 inequality measurement data problem in, 20–29 detail needed in, disaggregation in, 10–11 ethics and, 13–14 of Europe with Theil statistic, 38 GDP and, 63–69, 65f, 65t, 66t, 68t grouped data for, 8–9 hierarchical datasets for, 10 in OECD DS datasets, 21–23, 22f political interpretations of, 13–14, 16 problems inherent to, 20 318 Index inequality measurement (continued) purpose of, 14 regional data differences influencing , 29 regional data for unemployment and, 39 regional data in United States with NASDAQ index and, 40–41, 40f regional data of, 6–7 reliability of, 12 scope and restrictions of, 11–12 by sector, 33–34, 35f simple physics of, 9–12 Theil’s formula for, 9–10 time scale for, 11 UNIDO Industrial Statistics categories for, 98n9 of UTIP-UNIDO dataset by region and time, 57t in UTIP-UNIDO dataset distribution with Theil statistic, 58, 58f inflation, employment without, 146 information technology sector (IT sector), 134f, 135 between-county inequality impact of boom/bust in, 145–46 end of boom for, 137 geographic distribution of, 143–44 inequality among , 136–37, 137f, 139f Shapiro on bubble in, 146 instability credit and, 18 managing , 4–5 insurance sector, 134f, 135 Integrated Retirement and Pension System (SIJP), 256 International Standard Industrial Classification (ISIC), 56 intersectoral transitions in economy, 48 in global economy, 50 inequality and, 74 pay inequality and, 48 United States and, 49–50 inverted U See Kuznets curve Ireland credit bubble in, 177 UK wage rates by sector compared to, 194t, 196 unemployment in, 190, 192 ISIC See International Standard Industrial Classification Islamic Republics, 107, 290 countries classified as, 116 inequality in, 108, 109t, 110t, 112t IT sector See information technology sector Jobs Study (OECD), 202 Johnson, George, 125 Johnson, Lyndon, 124 Joint Economic Committee, 149n2 Journal of Economic Literature, Kennedy, Joseph P., Kirchner, Nestor, 253 Kum, Hyunsub, 33, 36 Kuznets, Simon, 5–6, 15, 74, 77n2, 101, 167 modern application of analysis from, 291–92 on urbanization, 98n14 Kuznets curve, 48 augmented, 52, 53f China’s shape of, 73–74 cross-sectional approach to, 65–66 obsolescence of traditional, 63 global inequality and, 74 panel estimation for, 66–67, 66t testing for, 64–65 turning points in, 64, 64f Kuznets’ hypothesis Augmented, 68–69 basic mechanism of, 47–48 as between-sector model, 55–56 change in proportions and differentials as key to, 48 China and, 51–52 global economy and, 51 inequality sources in, 128–29 longevity and validity of, 69 manufacturing pay datasets for, 53, 59t–60t policy choices blurring , 48–49 technology accounted for in, 63 time and, 49 UTIP-UNIDO dataset and, 51–52 labor market flexibility hypothesis (LMF hypothesis), 201–2, 213 labor markets democracy regulation of, 101 in Europe, 17, 199 European unemployment affected by policy with, 165–66, 199 flexibility of, 38–39, 46n27 latent variable, 204 Leone, Richard, 125 LIS See Luxembourg Income Studies LMF hypothesis See labor market flexibility hypothesis Lorenz curve, 82, 98n6 Index for between-industry earnings inequality in United States, 131–32, 131f Luxembourg , 209–10 canonical score and pseudoscore correlations for, 230t Luxembourg Income Studies (LIS) DS and WIDER compared to, 29 OECD inequality rise shown in, 61, 62f Maastricht Treaty of 1993, 42, 171 austerity of, 202 failure of, 182–83 Macroeconomic Policy hypothesis (MP hypothesis), 202 macroeconomics global inequality as, 73–74 trade principles in, 241 manufacturing employment in China, 239–40, 239t Chinese inequality and, 240 in Cuba, 271 manufacturing pay See also pay inequality agriculture wage rate observations based on, 53–54, 82 in China, 236 income inequality in Canada and Finland with, 60t, 61 income inequality in United States and UK with, 58, 59t, 61 inequality in, 52–53 Kuznets’ inequality and industrialization argument with datasets from, 53 in Mexico, 88f, 89 United States unemployment compared to income inequality in, 41–42, 42f wage rank differentials within, 54–55, 55f manufacturing sector, Cuba as percentage of GDP, 282, 283t market socialism, 243–44 McCaulet, Robert, 245 MECE See mutually exclusive and collectively exhaustive grouped data median-voter mechanism, in democracy, 101 Meidner-Rehn argument, 169–70 Menem, Carlos, 253 Mexico, manufacturing pay in, 88f, 89 MFGPOP See ratio of manufacturing employment to population migration, region-based unemployment and, 172 Milanovic, Branko, 7, 102–3, 122n6 research methods of, 23 mining industry, Cuba crisis harming , 282, 283f 319 MNC See multinational corporation monetary policy European unemployment affected by, 166–67 Fed on inequality and, 42 most probable distribution, of income inequality, 135 MP hypothesis See Macroeconomic Policy hypothesis multinational corporation (MNC), 202 mutually exclusive and collectively exhaustive grouped data (MECE), 30 NAICS See North American Industry Classification System NASDAQ composite index , 40f between-counties Theil statistic compared to, 144, 144f national datasets, transnational datasets compared to, 69–70 “national labor supply” concept, 45n24 national-level interindustrial pay inequality, state-level income inequality affected by, 159–60 National Statistical Institute, Cuba (ONE), 271 NDF See nondeliverable forward neoliberalism, in Argentina, 252, 265 Netherlands, 182 canonical score and pseudoscore correlations for, 229t New Deal, 124 New Zealand, 123n18 nondeliverable forward (NDF), 245 North American Industry Classification System (NAICS), 129, 130f SIC change to, 130 Norway, 210–11 canonical score and pseudoscore correlations for, 231t, 233t NUTS level and 2, region list, 185t–189t OECD See Organization for Economic Co-Operation and Development ONE See National Statistical Institute Organization for Economic Co-Operation and Development (OECD) DS datasets for inequality measurement in, 21–23, 22f household income inequality rise in non-OECD countries and, 93–96 inequality in DS datasets for non-OECD countries compared to, 93, 93f Jobs Study of, 202 320 Index Organization for Economic (continued) LIS showing inequality rise for, 61, 62f pay inequality in, 61–62 panel estimation See also fixed-effects modeling ; random-effects modeling autoregressive specification for, 67, 68t for Kuznets curve, 66–67, 66t Paulson, Henry, 146 pay inequality See also between-industry earnings inequality; Cuban pay inequality; manufacturing pay in Argentina from 1994–2007, 256–61, 257f, 259f, 261f, 262f in Brazil from 1996–2007, 261–65, 263f, 264f, 266f, 267f in Cuba 1991–2004, 270–72 economic development relationship with, 51–52 economic growth improving with increase in, 76 Europe reducing , 181 developed and developing countries differences in, 61 global finance and, 73 income inequality relationship to, 82–87, 85t, 86t, 127 intersectoral transitions and, 48 national-level interindustrial, 159–60 in OECD, 61–62 per capita national income and, 62–63, 69 region-based unemployment and, 172–73 technological change influencing , 56 unemployment and, 38–39, 43, 127 United States history of, 124 in United States using alternative category structures, 132–33, 132f Penn World Tables dataset, 58, 75 per capita national income, pay inequality and, 62–63, 69 personal income, 150n16 Piketty, Thomas, 126, 149n5 Plan Real, in Brazil, 253 Poland, 179 political competition for public support, in democracy, 101 political regimes See also specific regimes attributes of, 106 Cheibub-Gandhi index for, 105, 111, 118, 118t countries classified by, 113–17 dispositional properties of, 105 empirical classification of, 104 Freedom House index on, 104, 111, 119, 119t Hadenius regime classification for, 111, 119–20, 121t inequality effects by type of, 108–13, 109t, 110t, 112t Polity index on, 104, 111, 119, 119t regression analysis with dummy variables using DS datasets, 111–12, 112t regression analysis with dummy variables using UTIP-UNIDO dataset for, 107–11, 109t, 110t relational properties of, 105 typology of, 105–6 Vanhanen database on, 104–5 World Bank index for, 105, 111, 119, 120t political regime data control variables in, 117 country classification in, 113–17 political science, democracy and inequality in, 101–5 politics in Argentina, 253–54 between-industry earnings inequality and, 139–40 in Brazil, 253–54 inequality measurement and, 13–14, 16 regional data for analyzing , 39–40 state-level income inequality consequences for, 152–53 Polity index , 104, 111 for UTIP-UNIDO dataset, democracy compared to dictatorship, 119, 119t POPGROWTH See population growth rate population growth rate (POPGROWTH), 83–85, 85t, 86t Portugal, 190 canonical score and pseudoscore correlations for, 226t power law, of income inequality, 135 PPP See purchasing power parity property income, 46n30 pseudo-democracy, 107 elections in countries with, 115 inequality in, 109t, 110t, 112t pseudoscores See also canonical score and pseudoscore correlations calculating , 205–6 for European wage flexibility dataset, 206–7, 207f, 208f, 209f purchasing power parity (PPP), in China, 18n5, 250n8 Index race, voter suppression and, 154 random-effects modeling , 66 tests for, 79n22 ratio of manufacturing employment to population (MFGPOP), 83, 84–85, 85t, 86t, 87 Rawls, John, 101 real estate sector, 134f, 135 in China, 248–49, 248t recent democracy, 106 inequality in, 109–11, 109t, 110t, 112t regimes See political regimes REGIO dataset, 173, 183 regional data for Democratic and Republican Party, 40 DS datasets influenced by differences in, 29 Europe need for, 37 grouped data changes by, 31–32 income inequality discrepancies with, 91 of inequality measurement, 6–7 inequality measurement influenced by differences in, 29 inequality measurement of UTIP-UNIDO dataset by time and, 57t for inequality measurement with unemployment, 39 political analysis with, 39–40 with Theil statistic, 43 in United States for inequality measurement with NASDAQ index , 40–41, 40f region-based unemployment See also European region-based unemployment and inequality fixed-effects model factors governing , 170, 172 global and national policies taken into account for, 171 inequality and, 170–71 migration and, 172 pay inequality and, 172–73 population differentials for, 172, 172t relative income affecting , 174 sectorization used for, 190t sensitivity analysis for, 191t youth and, 171 regression analysis with dummy variables for DS datasets, 27–29, 28t for political regimes with DS datasets, 111–12, 112t for political regimes with UTIP-UNIDO dataset, 107–11, 109t, 110t relational properties of, political regimes, 105 321 Republican Party, 16–17 Democratic Party ideals and interests compared to, 153–54, 162 regional data and, 40 rigidity European unemployment caused by European wages and, 201 of European wages, 198–99 of Europe pay rates, 17 Rousseff, Dilma, 291 RoyChowdhury, Deepshikha, 200, 205 Rumsfeld, Donald, 79n7 running mean smoother, 65, 65f Saez, Emmanuel, 126, 149n5 Sala-i-Martin, Xavier, 23, 44n3 sector datasets See also between-industry earnings inequality; regional data Europe need for, 37 inequality measurement with, 33–34, 35f semi-aggregated economic datasets advantages of, 32–33 basis of, 29–30 grouped data for, 30–31 survey data valued over, 30 services sector, 168 Shannon, Claude, Shapiro, Robert, 146 SIC See Standard Industrial Classification SIJP See Integrated Retirement and Pension System Single European Act of 1987, 171 skill-biased argument, 19n10 evidence against, 127 fall of, 126 inequality and, 125 social democracy, 100, 290–91 end of, 123n18 inequality in, 16, 109t, 110t, 112t stability and endurance of, 113 socialism, market, 243–44 social welfare, inequality as problematic indicator of, 140 Soros, George, 73 South Africa, DS dataset Gini coefficient measures for, 88f, 89 Soviet Union, 269 CMEA disintegration with fall of, 272 Cuban pay inequality after collapse of, 279 Spain, 174, 176, 182 HGI and HNE in, 27, 27f “Special Period in Times of Peace”, of Cuba, 274, 275t–276t, 276, 281, 287 322 Index Squire, Lyn, 20 See also DS datasets Standard Industrial Classification (SIC), 129, 130f NAICS change from, 130 state-level income inequalityBEA data for, 159 dataset generation for, 158 geographic stratification of incomes for, 163–64 Gini coefficient for voter turnout and, 160 grouped data for, 158–59 income paradox in voting and, 162–63, 163f national-level interindustrial pay inequality affecting , 159–60 political consequences of, 152–53 presidential elections influenced by, 162 stock market See also NASDAQ composite index Chinese boom in, 245 income inequality influenced by, 127 studies See inequality measurement sugar industry, Cuban crisis impact on, 277, 282–83, 283f supply-side economics, 95 survey data See also expenditure surveys; income surveys combining , 37 grouped data compared to, 14 incompleteness of, 15 scope limitations of, 36–37 semi-aggregated economic datasets valued less than, 30 time and irregularity of, 22–23 Sweden, 210 canonical score and pseudoscore correlations for, 231t, 233t Switzerland, 208–9 canonical score and pseudoscore correlations for, 229t, 232t Tax Reform Act of 1986, 149n5 technology income inequality and, 126 Kuznets’ inequality and industrialization argument accounting for, 63 pay inequality influenced by changes in, 56 Theil, Henri, 30–31 inequality measurement formula of, 9–10 Theil statistic for between-county inequality and between-state inequality (US), 141–43, 143f “between-groups component” in, 30–31 between-groups component of, 193–94, 196 between-industry earnings inequality measured with, 129–30, 130f, 133–34, 133f for Chinese inequality between and within provinces, 237, 237f Europe inequality measurement with, 38 formula for, 9–10 Gini coefficient compared to, 82 regional data with, 43 skewness of, 79n13 as statistical fractal, 32 UTIP-UNIDO dataset inequality measurement distribution with, 58, 58f time European region-based unemployment and inequality fixed-effects model and effects of, 177–78, 178f European unemployment fixed-effects with, 184t global inequality and effects of, 70–72, 71f, 71t inequality measurement and, 11 inequality measurement of UTIP-UNIDO dataset by region and, 57t Kuznets’ inequality and industrialization argument and, 49 survey data irregularity and, 22–23 Todaro, Michael, 167–68 top-coding , 129, 150n10 tourism, in Cuba, 270, 276, 284 trade China rise of 2002–2006 in finance sector and, 240–44, 242t Chinese capital inflow and, 244–46 macroeconomic principles of, 241 transnational datasets, national datasets compared to, 69–70 “trickle-down economy,” 148 UBPC See Basic Cooperative Production Units UK See United Kingdom underemployment, 168 unemployment, 17 See also employment; European unemployment; region-based unemployment in Europe, 39, 42–43 Europe compared to United States in, 165 Europe compared to United States with inequality and, 179–81 Index global inequality and, 291 inequality correlated to, 38–39, 197n6 in Ireland, 190, 192 pay inequality and, 38–39, 43, 127 rate, 166 regional data for inequality measurement with, 39 United States income inequality in manufacturing pay compared to, 41–42, 42f UNIDO Industrial Statistics See United Nations Industrial Development Organization Industrial Statistics United Kingdom (UK), 123n18, 174, 182 canonical score and pseudoscore correlations for, 227t credit conditions creating 1990s boom in, 213 income inequality in manufacturing pay for United States and, 58, 59t, 61 Ireland wage rates by sector compared to, 194t, 196 sterling overinflation in, 208, 212 United Nations Industrial Development Organization Industrial Statistics (UNIDO Industrial Statistics), 33, 56, 81 comparability and accuracy of, 79n10 inequality measurements reported in, 98n9 updating , 97n1 United States between-industry earnings inequality for high-growth sectors from 1991–2001 in, 136–37, 137f between-industry earnings inequality in 1990–2007 in, 134–35, 134f between-industry earnings inequality in 2000–2007, 138–39, 139f credit bubbles and, 148 economic growth driven by war in, 140, 149 Electoral College in, 16, 39 European income inequality compared to, 37–38 financial crisis measures of, 292–93 identity by industry in, 132 income inequality components in, 52, 146–48 income inequality in manufacturing pay for UK and, 58, 59t, 61 industrialization inequality in, 56 inequality and unemployment in Europe compared to, 179–81 323 inequality perceptions in history of, 124–25 intersectoral transitions in, 49–50 Lorenz curves for between-industry earnings inequality in, 131–32, 131f manufacturing pay income inequality compared to unemployment in, 41–42, 42f “national labor supply” concept in, 45n24 pay inequality history in, 124 pay inequality using alternative category structures in, 132–33, 132f regional data for inequality measurement with NASDAQ index in, 40–41, 40f “skill-bias” hypothesis for income inequality in, 19n10 unemployment in Europe compared to, 165 wage rate in high-growth sectors from 2003–2007 in, 137–38, 138t University of Texas Inequality Project (UTIP), 29, 81 EHII dataset, 35–36, 36f UNIDO dataset, 33 urbanization Census Bureau quantifying , 155 inequality and, 84–85, 85t, 86t Kuznets on, 98n14 UTIP See University of Texas Inequality Project UTIP Estimated Household Income Inequality dataset (UTIP-EHII), 35–36, 36f calculating , 91–92 DS dataset and advantages of, 92, 94–95 DS dataset Gini coefficients compared with, 87–88, 88f, 92 household income inequality trends in DS dataset compared to, 94–95, 94f, 95f for non-OECD countries by income level, 96, 96f variables for basis of, 91 UTIP-UNIDO dataset, 33 Cheibub-Gandhi index for democracy compared to dictatorship in, 118, 118t coverage of, 81 credibility of, 58–59 cross-country advantage of, 73 DS datasets combining with, 81–87, 85t, 86t DS datasets diverging from, 60t, 61, 62f 324 Index UTIP-UNIDO dataset (continued) Hadenius regime classification for democracy compared to dictatorship in, 119–20, 121t household income inequality measured with, 87 inequality measurement by region and time, 57t Kuznets’ inequality and industrialization argument and, 51–52 modern interpretation of, 63 Polity/Freedom House index for democracy compared to dictatorship in, 119, 119t regression analysis with dummy variables for political regimes using , 107–11, 109t, 110t Theil statistic inequality measurements in distribution of, 58, 58f uses of, 81 World Bank index for democracy compared to dictatorship in, 119, 120t value-added tax (VAT), 246 Vanhanen database, 104–5 VAT See value-added tax Vector Error Correction Model, 250n10 Venezuela, 269 voter choice fixed-effects modeling for, 160–61, 161t inequality and, 153 inequality and, in Bush-Gore election, 155–58, 156t, 157t, 158t inequality cycle-to-cycle changes influencing , 161 inequality influencing Democratic Party voter as, 164 voter repression inequality and, 153 race and, 154 voter turnout fixed-effects modeling for, 160–61, 161t Gini coefficient for state-level income inequality and, 160 inequality and, in Bush-Gore election, 155–58, 156t, 157t, 158t voting See elections; income paradox in voting Voting Rights Act, 154 wage flexibility, Europe and, 166, 182 See also European wages wage rank inequality changes impact on, 55 manufacturing pay differentials in, 54–55, 55f wage rate, 41 in Austria, 176–77 in Austria compared to Germany, 193t, 196 in China, 244 in Cuba across sectors, 270–71 Europe summary statistics for average, 192t of Ireland compared to UK by sector, 194t, 196 manufacturing pay observations used for agriculture and, 53–54, 82 in United States high-growth sectors from 2003–2007, 137–38, 138t Ward’s method, for cluster analysis, 203 WIDER See World Institute for Development Economics Research Widestrom, Amy, 153 WIID See World Income Inequality Database Wood, Adrian, 125 World Bank, 20, 97 See also DS datasets World Bank index , 105, 111 for UTIP-UNIDO dataset, democracy compared to dictatorship, 119, 120t World Income Inequality Database (WIID), 44n8 World Institute for Development Economics Research (WIDER), 21 LIS compared to, 29 youth European region-based unemployment and, 171 Zola, Emile, 289 ... such as the rise of wealthy Guangdong, Shanghai, and Beijing, and intersectoral forces such as the rise of banking and transport and the relative decline of farming and (retail) trade.8 It stands... in any particular data point The Physics and Ethics of Inequality 13 The Ethical Implications of Inequality Measures Most of those att racted to the study of inequality are motivated, at least... Theil statistic Thus readily available archives available from practically any country and many multinational agencies can be mined to generate a large archive of inequality measures, each of which