1. István György Tóth / toth@tarki.hu / http://www.tarki.hu István György Tóth (with contributions by Márton Medgyesi and Tamás Keller) Kickoff conference at LSE, 19-20 March 2010 Income inequality measured and perceived: European comparisons

2. István György Tóth / toth@tarki.hu / http://www.tarki.hu 1)Part I: describe and assess the level and background factors of inequality in European countries as measured by EU- SILC 2)Part II: describe and assess the level of tolerance towards inequality in European countries as measured by EU-SILC 3)Part III. conclude Research question

3. István György Tóth / toth@tarki.hu / http://www.tarki.hu In Part I we … - examine the distribution of incomes in EU member states (new and old), with standard methods and assumptions - test if alternative measures and concepts affect the broad picture - analyse determining factors of income inequality Base: and SSO 2009 Annual Report

4. István György Tóth / toth@tarki.hu / http://www.tarki.hu In Part II we … - examine the distribution of inequality perceptions in EU member states - try finding alternative measures for a better fit between measured and perceived (tolerated) inequality levels - analyse determining factors of inequality tolerance

5. István György Tóth / toth@tarki.hu / http://www.tarki.hu For measured income inequalities: –Eurostat EU-SILC UDB 2007 released XXXXXXX –reference year: 2006 –income concept: yearly net household monetary income –country coverage: EU27 – (RO, BG and MT) –Bottom and top coding at 0.1 and at 99.95 percentiles –Research background: SSO, OECD ineq paper, Tarki international comparisons For inequality tolerance Special Eurobarometer 72xxxx ISSP ESS xxx Data and definitions

6. István György Tóth / toth@tarki.hu / http://www.tarki.hu Measured Income Inequality

7. István György Tóth / toth@tarki.hu / http://www.tarki.hu Source: Based on data from the Eurostat New Cronos database. http://epp.eurostat.ec.europa.eu/ Note: Bootstrap confi dence intervals were obtained by 1,000 replications. - Statistical margin of error: (overlapping) groups of countries can be identified - „Unequal”: PT, LV, GR, LT - „Equal”: SI, SE, DK - NMS: in the whole spectrum Gini indices of income inequality and 95% confidence intervals

8. István György Tóth / toth@tarki.hu / http://www.tarki.hu Alternative Equivalence scales: „”OECD II” (1 st adult=1, other 14+ members=0.5, all members <14=0.3), which is the default in this paper (e=0.7, approx) per capita adjustment (adjust for hh size, each member receives a weight of 1) Results: Gini (OECD2) < Gini (Per capita) - The effect of switching is large in countries where initial measured Gini (OECD2) is lower - Consequence: based on per capita incomes, country differences are larger - NMS in both groups Note: more restrictive scales (e=sqr2) to be investigated INEQUALITY SENSITIVITY: ALTERNATIVE EQ SCALES

9. István György Tóth / toth@tarki.hu / http://www.tarki.hu Sensitivity of Gini estimates to the choice of equivalence scale (1.)

10. István György Tóth / toth@tarki.hu / http://www.tarki.hu Sensitivity of Gini estimates to the choice of equivalence scale (2.)

11. István György Tóth / toth@tarki.hu / http://www.tarki.hu Source: EU-SILC (2006) Note: The bottom of the data bars represents the first decile, the top represents the tenth decile and the marks in between show the average incomes of the individual deciles. - Methods: - Bars connect (Euro, PPP) avg incomes of deciles - Not shown: variance at ends of distributions!! Conclusion: Ranked by country avg incomes, NMS-s cluster at the bottom (presumably, roughly corresponding to GDP ranking) - Care be taken with PPP (CY vs SE) The income distributions of the countries of the European Union (Euros, PPP)

12. István György Tóth / toth@tarki.hu / http://www.tarki.hu The distribution of the population among the different categories of the overall European income distribution, by country Source: Own calculations based on EU-SILC 2006 Findings: -The majority of the population in LT, LV, PL, EE SK, HU belong to the <50%med EU bracket -This ratio in CZ and SI is lower

13. István György Tóth / toth@tarki.hu / http://www.tarki.hu Note: Percentages are simple country averages. Age (>5%): North (and CY) Education (>15%): Mediterranean countries (PT, CY, GR), Former socialist countries (HU, LT, SI, PL), + LU, + IE Employment (>10%): Baltics and Anglo-Saxon countries plus FI, DK, BE, CZ Percentage of inequalities explained by different factors in the country groups, 2005

14. István György Tóth / toth@tarki.hu / http://www.tarki.hu Perceptions and tolerance

15. István György Tóth / toth@tarki.hu / http://www.tarki.hu European societies differ very much in their general attitudes towards inequalities. The share of people most dissatisfied with the overall level of inequality is over 70% in LT, HU, SI, EE, BG GR and LV while it is below 40% in DK, NL, AT, IT and MT. Inequality tolerance: are income differences too large? The share of population who “totally agree” with the question: “Nowadays income differences between people are fir too large”. Source of date: Special EuroBarometer, 2009.

16. István György Tóth / toth@tarki.hu / http://www.tarki.hu Preference for redistribution – Government should reduce income levels The “preference for (vertical) redistribution” is strongest in some Eastern European countries, including HU and LV and Latvia, while in some other former transition countries (CZ, SK) this share shows among the lowest in Europe The share of population who “totally agree” with the question: “Government should ensure that the wealth of country is redistributed in a fair way”. Source of date: Special EuroBarometer, 2009.

17. István György Tóth / toth@tarki.hu / http://www.tarki.hu Inequality intolerance and redistributive preference correlates, with some exceptions. In GR, HU and CY, the frustration with inequality levels is coupled with a high strain on government, while in PL, SK and CZ the relatively lower level of inequality intolerance is coupled with some of the lowest level of popular redistributive preferences. The relationship between inequality tolerance and redistributive preference Y axis: The share of population who “totally agree” with the question: “Government should ensure that the wealth of country is redistributed in a fair way”. Source of date: Special EuroBarometer, 2009. X axis: The share of population who “totally agree” with the question: “Nowadays income differences between people are fir too large”. Source of date: Special EuroBarometer, 2009.

18. István György Tóth / toth@tarki.hu / http://www.tarki.hu Inequality attitudes correspond only loosely to actual inequality levels. The level (and severity) of poverty seems to be a closer proxy to what people associate with “inequality” as the correlation for poverty rate and poverty gap is higher with inequality (in)tolerance. Inequality tolerance (2009) and Gini coefficient (2008) Y axis: The share of population who “totally agree” with the question: “Nowadays income differences between people are fir too large”. Source of date: Special EuroBarometer, 2009. X axis Gini coefficient 2008. Source of data: Eurostat New Cronos Database.

19. István György Tóth / toth@tarki.hu / http://www.tarki.hu Tests for … Alternative measures S80/S20 relative poverty rate and gap employment and wage differentials by education Averageing over years Spell (quasi panel) analysis

20. István György Tóth / toth@tarki.hu / http://www.tarki.hu Results  inequality attitudes correspond only loosely to actual inequality levels  the level (and severity) of poverty seems to be a closer proxy to what people associate with “inequality” (the correlation for poverty rate and poverty gap is higher with inequality (in)tolerance  people make their judgements about levels of inequalities based on perceived poverty levels, rather than on the basis of some abstract inequality concepts  using period averages may help sorting out distortions caused by measurement error  a change in poverty levels may provoke higher redistributive preferences but much depends on national contexts

21. István György Tóth / toth@tarki.hu / http://www.tarki.hu Poverty rate and redistributive preference Y axis: Redistributive preference is the share of population who “agree strongly” or “agree” to the question whether “Government should reduce differences in income levels”. Source of data: ESS 1st wave, ESS 2nd wave, ESS 3rd wave(2002- 2006). X axis: At risk of poverty rate (cut-off point: 60% of median equivalised income after social transfers) between 2002 and 2006. Source of data: Eurostat New Cronos Database.

22. István György Tóth / toth@tarki.hu / http://www.tarki.hu Poverty gap and redistributive preference Y axis: Redistributive preference is the share of population who “agree strongly” or “agree” to the question whether “Government should reduce differences in income levels”. Source of data: ESS 1st wave, ESS 2nd wave, ESS 3rd wave(2002- 2006). X axis: Relative median at-risk-of-poverty gap. The difference (in %) between the income of persons below the at-risk-of-poverty line and the at-risk-of- poverty line (cut-off point: 60% of median equivalised income after social transfers) between 2002 and 2006. Source of data: Eurostat New Cronos Database.

23. István György Tóth / toth@tarki.hu / http://www.tarki.hu There are significant cross country differences tolerance for inequalities It is not only country averages but also the internal distribution of preferences vary across countries In addition to objective income position, subjective mobility experiences and prospects, reference roups (comparison incomes) all matter Tolerance for inequality also contributes to demand for redistribution: in addition to self interest motives (income position, POUM, risk aversion) and to exogenous values (over individualism in society and over altruistic and reciprocity motives) This is a growing and interesting area research area. Conclusion

24. István György Tóth / toth@tarki.hu / http://www.tarki.hu Table 1.1 Trends in poverty in countries with low, medium and high levels of poverty Period: 1995–2001 Poverty trend DeclineNo significant change or unclear trend Increase Level of poverty Low Denmark, Luxembourg, Netherlands, Sweden Finland MediumAustria, Belgium, Germany France HighItaly, Greece, Portugal Spain, UK Ireland Notes: (1) Low poverty level: poverty rate 18. (2) Increasing/declining trend: poverty rates increased (declined) in minimum two consecutive years or by minimum 2%.

25. István György Tóth / toth@tarki.hu / http://www.tarki.hu Table 6.1 Magnitude and direction of change in the variables examined between 2000 and 2005 CountryGini coefficient 00/05 Poverty rate 00/05 GDP PPS 00/05 AT0+0 BE0++0 BG---+++ CY.. 0 CZ0+++++ DE+++0 DK+++0 EE-0+++ ES-++ FI0++0 FR000 GR00++ HU++ IE++--+

26. István György Tóth / toth@tarki.hu / http://www.tarki.hu CountryGini coefficient 00/05 Poverty rate 00/05 GDP PPS 00/05 IT+++-- LT++ +++ LU0+++ LV+++++ MT.. - NL0-0 PL++++ PT0-0 RO++++++ SE++++ SI++++ SK.. +++ UK-+0 Table 6.1 Magnitude and direction of change in the variables examined between 2000 and 2005

27. István György Tóth / toth@tarki.hu / http://www.tarki.hu Figure 6.6 The change in the Gini coefficient and the change in GDP PPS per capita, 2000-05

28. István György Tóth / toth@tarki.hu / http://www.tarki.hu Figure 6.7 The change in the poverty rate and the change in GDP PPS per capita, 2000-05

29. István György Tóth / toth@tarki.hu / http://www.tarki.hu www.tarki.hu Thank you!