Appendix to final report WP3. Francesco Bogliacino, Virginia Maestri INTERMEDIATE WORK PACKAGE 3 APPENDIX JULY 2012 GROWING INEQUALITIES IMPACTS

Transcription

1 Appendix to final report WP3 Francesco Bogliacino, Virginia Maestri INTERMEDIATE WORK PACKAGE 3 APPENDIX JULY 2012 GROWING INEQUALITIES IMPACTS

2 July 2012 Francesco Bogliacino, Virginia Maestri, Amsterdam. Correspondence address: General contact: Bibliograhic Information Bogliacino, F., Maestri, V., (2012). Appendix to final report WP3. AIAS, GINI Intermediate Work Package 3 Appendix. Information may be quoted provided the source is stated accurately and clearly. Reproduction for own/internal use is permitted. This paper can be downloaded from our website

3 Appendix to final report WP3 Francesco Bogliacino Virginia Maestri GINI seventh framework programme Cooperation, theme 8 Socio-economic sciences and humanities SSH Social inequalities, their implications and policy options July 2012 Intermediate Work Package 3 Appendix

4 Francesco Bogliacino, Virginia Maestri Page 4

5 Intermediate Work Package 3 Report-Appendix Table of contents Drivers of Growing Inequalities APPENDIX A. STYLIZED FACTS ON THE EVOLUTION OF INEQUALITY FOR GINI PROJECT COUNTRIES...7 A.1 Inequality according to different data sources....7 A.2 Inequality according to different indicators A.3. Different patterns of Inequality...26 A.4. Top Income Shares and their evolution...29 APPENDIX B. INTER-LINKAGES AMONG DIFFERENT SOURCES OF INEQUALITY...35 APPENDIX C. ESTIMATED COEFFICIENTS FROM MINCERIAN REGRESSIONS FOR WAGES...41 INFORMATION ON THE GINI PROJECT...53 Page 5

6 Francesco Bogliacino, Virginia Maestri Page 6

7 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix A. Stylized facts on the evolution of inequality for GINI Project countries A.1 Inequality according to different data sources. In the following series of graphs, we report the GINI for net disposable income using the OECD equivalence scale, but calculated from different data sources. The sources are OECD, LIS, RED, SWIID and Eurostat (ECHP and then EU-SILC). Figure A. 1 Australia SWIID OECD LIS Page 7

8 Francesco Bogliacino, Virginia Maestri Figure A. 2 Austria SWIID OECD EUSILC LIS ECHP Figure A. 3 Belgium SWIID OECD EUSILC LIS ECHP Page 8

9 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 4 Canada SWIID OECD LIS RED Figure A. 5 Czech republic SWIID OECD EUSILC LIS ECHP Page 9

10 Francesco Bogliacino, Virginia Maestri Figure A. 6 Denmark SWIID OECD EUSILC LIS ECHP Figure A. 7 Finland SWIID OECD EUSILC LIS ECHP Page 10

11 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 8 France SWIID OECD EUSILC LIS ECHP Figure A. 9 Germany SWIID OECD EUSILC LIS ECHP RED Page 11

12 Francesco Bogliacino, Virginia Maestri Figure A. 10 Greece SWIID OECD EUSILC LIS ECHP Figure A. 11 Hungary SWIID OECD EUSILC LIS ECHP F Page 12

13 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities igure A. 12 Ireland SWIID OECD EUSILC LIS ECHP Figure A. 13 Italy SWIID OECD EUSILC LIS ECHP RED Page 13

14 Francesco Bogliacino, Virginia Maestri Figure A. 14 Luxembourg SWIID OECD EUSILC LIS ECHP Figure A. 15 Netherlands SWIID OECD EUSILC LIS ECHP CBS Page 14

15 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 16 Poland SWIID OECD EUSILC LIS ECHP Figure A. 17 Portugal SWIID ECHP OECD EUSILC Page 15

16 Francesco Bogliacino, Virginia Maestri Figure A. 18 Slovak Republic SWIID OECD LIS Eurostat Figure A. 19 Spain SWIID OECD EUSILC LIS ECHP RED Page 16

17 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 20 Sweden SWIID OECD EUSILC LIS ECHP RED Figure A. 21 United Kingdom SWIID OECD EUSILC LIS ECHP RED Page 17

18 Francesco Bogliacino, Virginia Maestri Figure A. 22 United States SWIID OECD LIS RED Page 18

19 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities A.2 Inequality according to different indicators. In the following set of graphs we show a set of indicators (Gini, Varlog, P90-50 and P50-10 ratios) for earnings. The datasource is RED. Figure A. 23 Canada: P-Ratios Canada - p50/p10 & p90/p50 ratio p50/p10 p90/p Figure A. 24 Canada. Var-Log and Gini Canada - Gini coeff. & var(log(w)) varlog Gini Page 19

20 Francesco Bogliacino, Virginia Maestri Figure A. 25 Great Britain: P-Ratios United Kingdom - p50/p10 & p90/p50 ratio p50/p10 p90/p Figure A. 26 Great Britain: Var-Log and GINI United Kingdom - Gini coeff. & var(log(w)) varlog Gini Page 20

21 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 27 Italy: P-Ratios Italy - p50/p10 & p90/p50 ratio p90/p50 p50/p Figure A. 28 Italy: Var-Log and Gini Italy - Gini coeff. & var(log(w)) Gini varlog Page 21

22 Francesco Bogliacino, Virginia Maestri Figure A. 29 Spain: P-Rations Spain - p50/p25 & p90/p50 ratio p90/p50 p50/p Figure A. 30 Spain: Var-Log and GINI Spain - Gini coeff. & var(log(w)) varlog Gini Page 22

23 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 31 Germany: P-Ratios Germany - p50/p10 & p90/p50 ratio p50/p10 p90/p d Figure A. 32 Germany: Var-Log and GINI Germany - p50/p10 & p90/p50 ratio p50/p10 p90/p d Page 23

24 Francesco Bogliacino, Virginia Maestri Figure A. 33 Sweden: P-Ratios p Sweden- p50/p10 & p90/p50 ratio p90/p50 p50/p p9050 Figure A. 34 Sweden: Var-Log and Gini Sweden - Gini coeff. & var(log(w)) varlog Gini Page 24

25 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 35 US: P-Ratios USA - p50/p10 & p90/p50 ratio p50/p10 p90/p Figure A. 36 US: Var-Log and Gini USA - Gini coeff. & var(log(w)) varlog Gini Page 25

26 Francesco Bogliacino, Virginia Maestri A.3. Different patterns of Inequality Figure A. 37 Canada: Var-log of different series g g Hourly wage (male) Earnings Disp. income Hours of work (male) Pre.-gov. income Figure A. 38 Germany: Var-log of different series Hourly wage (male) Earnings Hours of work (male) Disp. income Page 26

27 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 39 Sweden: Var-log of different series Earnings Disp. income Figure A. 40 Italy: Var-log of different series Earnings Hours of work (male) Disp. Income Hourly wage (male) Consumption Page 27

28 Francesco Bogliacino, Virginia Maestri Figure A. 41 United Kingdom: Var-log of different series Hourly wage (male) Earnings Hours of work (male) Consumption Figure A. 42 USA: Var-log of different series Hourly wage (male) Earnings Disp. income Hours of work (male) Pre.-gov. income Consumption Page 28

29 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities A.4. Top Income Shares and their evolution The following table illustrates the income definition used for the calculation of top income shares in each country. Definitions are taken from the World Top Income Database. Table A. 1 Income definition for the top share COUNTRY INCOME DEFINITION AUSTRALIA Actual gross income; adjustment made to taxable income prior to 1957 CANADA Gross income, adjusted for the grossing up of dividend income DENMARK Gross taxable income FRANCE Gross income, net of employee social security contributions FINLAND : taxable income/ : gross income JAPAN Gross income (significant capital income base erosion after 1946) ITALY Gross income but excluding interest income PORTUGAL Gross income SPAIN Gross income SWEDEN Gross income including transfers UNITED KINGDOM Prior to 1975 income net of certain deductions; from 1975 total income UNITED STATES Gross income, adjusted for net income deductions Figure A. 43 Top 0.1% country group 1 absolute difference FIN SWE AUS GBR USA JAP FRA top 0,1% income share Page 29

30 Francesco Bogliacino, Virginia Maestri Figure A. 44 Top 0.1% country group 2 absolute difference SWE AUS GBR USA FRA top 0,1% income share Figure A. 45 Top 0.1% country group 3 absolute difference PRT top 0,1% income share ITA ESP CAN Page 30

31 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 46 Top 1% country group 1 USA absolute difference AUS SWE GBR JAP FRA FIN top 1% income share Figure A. 47 Top 1% country group 2 absolute difference SWE AUS GBR USA FRA top 1% income share Page 31

32 Francesco Bogliacino, Virginia Maestri Figure A. 48 Top 1% country group 3 absolute difference DNK PRT ITA ESP CAN top 1% income share Figure A. 49 Top 5% country group 1 USA absolute difference AUS SWE GBR JAP FRA FIN top 5% income share Page 32

33 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure A. 50 Top 5% country group 2 absolute difference AUS SWE GBR USA FRA top 5% income share Figure A. 51 Top 5% country group 3 absolute difference DNK PRT ITA CAN ESP top 5% income share Page 33

34 Francesco Bogliacino, Virginia Maestri Page 34

35 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix B. Inter-linkages among different sources of inequality There is a generalized impression that inequality is somehow related with problem such as poverty and the material deprivation. Our understanding of the relationship among these measures is rather limited. The same holds for the relationship between income and wealth inequality. In this section we limit ourselves to the presentation of the statistical correlation. We start by plotting the association between income and wealth inequality. Both measures are affected by some biases: 1) income inequality does not keep into account in-kind benefits and imputed rents; 2) wealth inequality does not keep into account public pensions and human capital stocks. OECD (2008) shows that the inclusion of the in kind benefits has a progressive effect, while the effect of the inclusion of the items mentioned sub 2) are difficult to estimate, especially given that the institutional differences affect the incentives to accumulate wealth. One possible way to arrive to a less biased estimate of both and, also, to a potential association between the two variables (wealth and income) is the use of income net-worth as discussed by Weisbrod and Hansen (1968): it consists of transforming the net worth into a constant flow of income, using both an interest rate and life expectancy to discount. Unfortunately no data are available. In the figures below we plot Gini of Wealth taken from OECD (2008) for a selection of countries against Gini of Income taken from LIS. Whenever the s of the survey do not match we correct for the trend of Income Gini using data from SWIID (Slot, 2009). Besides the US, which stands as a deeply unequal society; the evidence for Europe shows a negative correlation. In Chapter 3 we will provide also some analytical discussion of the possible causes. In the same Appendix B we also plot the main associations between a set of common indicators: a) GDP per capita measured in purchasing power parity; b) poverty rate, measured as the share of persons with less than 60% of median equivalized income; c) GINI index of disposable income; d) measures of material deprivation and severe material deprivation, expressed as having at most four (respectively three) items of a bundle of fundamental goods (for a detailed definition see Eurostat). The source for the data is Eurostat. GDP per capita is strongly and negatively associated with indicators of poverty and material deprivation, supporting the fundamental statement that growth is a necessary condition for poverty reduction. Inequality is positively associated with material deprivation, severe and not severe, and poverty. The association is weak for the first Page 35

36 Francesco Bogliacino, Virginia Maestri measure and strong for the poverty rate, but in both cases data tend to be clustered, suggesting the possibility of multiple equilibria, namely the potential coexistence of different distribution of incomes for a given growth rate. Figure B. 1 Income Inequality versus Wealth Inequality GINI of Wealth vs GINI of Income Income GINI (SWIID) ITA GBR FIN CAN GER USA USA SWE Wealth GINI Source: GINI of Wealth is taken from OECD (2008), GINI of Income is taken SWIID data (Solt, 2009). Figure B. 2Gini of Wealth for selected countries in Source: UNU WIDER (2009) Page 36

37 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure B. 3Gini of Wealth for selected countries in Source: Global Wealth Report Credit Suisse 2011 (Shorrocks et al., 2011). Figure B. 4 GDP per capita versus material deprivation for a selection of countries in Source: Eurostat GDP p.c. PPP NLD DNK AUT SWE IRL GBR BEL GER FIN FRA ITA ESP PRTCZE GRC HUN SVK POL Deprivation Page 37

38 Francesco Bogliacino, Virginia Maestri Figure B. 5 GDP per capita versus severe material deprivation for a selection of countries in Source: Eurostat GDP p.c. PPP IRL NLD AUT SWE DNK GBR BEL FIN GER FRA ITA ESP PRT CZE GRC HUN SVK POL Severe Deprivation Figure B. 6Gini versus material deprivation for a selection of countries in Source: Eurostat Gini GBR ITA ESP IRL FRA BEL NLD AUT GER FIN DNK SWE PRT CZE GRC HUN SVK POL Deprivation Page 38

39 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure B. 7Gini versus severe material deprivation for a selection of countries in Source: Eurostat Gini ESP FRA BEL NLD AUT FIN GER DNK SWE GBR ITA IRL PRT GRC CZE HUN SVK POL Severe Deprivation Figure B. 8Gini versus poverty rate for a selection of countries in Source: Eurostat Gini FRA NLD AUT FINGER CZE DNK SWE BEL GBR PRT ITA ESP IRL GRC HUN SVK POL Poverty Rate Page 39

40 Francesco Bogliacino, Virginia Maestri Figure B. 9 GDP per capita versus poverty rate for a selection of countries in Source: Eurostat GDP p.c. PPP NLD AUT SWE DNK FINGER FRA CZE IRL GBR BEL ITA ESP PRT GRC HUN SVK POL Poverty Rate Page 40

41 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Appendix C. Estimated coefficients from Mincerian regressions for wages Figure C. 1Australia: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF TERTIARY Figure C. 2Australia: Estimated coefficients from a Mincerian regression. Source: LIS MANUF FINANCE Page 41

42 Francesco Bogliacino, Virginia Maestri Figure C. 3 Austria: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY Figure C. 4 Belgium: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF TERTIARY Page 42

43 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 5 Belgium: Estimated coefficients from a Mincerian regression. Source: LIS MANUF FINANCE Figure C. 6 Canada: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 43

44 Francesco Bogliacino, Virginia Maestri Figure C. 7 Denmark: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 8 Finland: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 44

45 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 9 France: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF TERTIARY Figure C. 10 France: Estimated coefficients from a Mincerian regression. Source: LIS MANUF FINANCE Page 45

46 Francesco Bogliacino, Virginia Maestri Figure C. 11 Germany: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 12 Hungary: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 46

47 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 13 Ireland: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 14 Italy: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 47

48 Francesco Bogliacino, Virginia Maestri Figure C. 15 Luxembourg: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 16 The Netherlands: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 48

49 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 17 Poland: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 18 Slovenia: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Page 49

50 Francesco Bogliacino, Virginia Maestri Figure C. 19 Spain: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF MANUF TERTIARY FINANCE Figure C. 20 United Kingdom: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF FINANCE MANUF Page 50

51 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Figure C. 21 USA: Estimated coefficients from a Mincerian regression. Source: LIS MAN/PROF TERTIARY Figure C. 22 USA: Estimated coefficients from a Mincerian regression. Source: LIS MANUF FINANCE Page 51

52 Francesco Bogliacino, Virginia Maestri Page 52

53 Intermediate Work Package 3 Report-Appendix Drivers of Growing Inequalities Information on the GINI project Aims The core objective of GINI is to deliver important new answers to questions of great interest to European societies: What are the social, cultural and political impacts that increasing inequalities in income, wealth and education may have? For the answers, GINI combines an interdisciplinary analysis that draws on economics, sociology, political science and health studies, with improved methodologies, uniform measurement, wide country coverage, a clear policy dimension and broad dissemination. Methodologically, GINI aims to: exploit differences between and within 29 countries in inequality levels and trends for understanding the impacts and teasing out implications for policy and institutions, elaborate on the effects of both individual distributional positions and aggregate inequalities, and allow for feedback from impacts to inequality in a two-way causality approach. The project operates in a framework of policy-oriented debate and international comparisons across all EU countries (except Cyprus and Malta), the USA, Japan, Canada and Australia. Inequality Impacts and Analysis Social impacts of inequality include educational access and achievement, individual employment opportunities and labour market behaviour, household joblessness, living standards and deprivation, family and household formation/breakdown, housing and intergenerational social mobility, individual health and life expectancy, and social cohesion versus polarisation. Underlying long-term trends, the economic cycle and the current financial and economic crisis will be incorporated. Politico-cultural impacts investigated are: Do increasing income/educational inequalities widen cultural and political distances, alienating people from politics, globalisation and European integration? Do they affect individuals participation and general social trust? Is acceptance of inequality and policies of redistribution affected by inequality itself? What effects do political systems (coalitions/winner-takes-all) have? Finally, it focuses on costs and benefi ts of policies limiting income inequality and its effi ciency for mitigating other inequalities (health, housing, education and opportunity), and addresses the question what contributions policy making itself may have made to the growth of inequalities. Support and Activities The project receives EU research support to the amount of Euro 2.7 million. The work will result in four main reports and a final report, some 70 discussion papers and 29 country reports. The start of the project is 1 February 2010 for a three- period. Detailed information can be found on the website. Page 53

54 Amsterdam Institute for Advanced labour Studies University of Amsterdam Plantage Muidergracht TV Amsterdam The Netherlands Tel Fax Project funded under the Socio-Economic sciences and Humanities theme.