Economic strain over the life course in Europe

Transcription

1 Economic strain over the life course in Europe (towards assessing prospects of ing) Tadas Leoncikas, Joanna Napierala Presentation for the conference Social monitoring and reporting in Europe 7 October 05

2 Key ims about the quality of life over a life course: U curve Intergenerational in-justice How true, where (un)true? In this presentation, we share a work in progress please provide feedback directly to the authors

3 EQLS 0: Economic strain : data sources will be examined A household may have different sources of income and more than one household member may contribute to it. Thinking of your household's total income, is your household able to make ends meet, namely, to pay for its usual necessary expenses? EU SILC: Values with great difficulty with difficulty with some difficulty 4 fairly easily 5 easily 6 very easily

4 Difficulties+great difficulties making ends meet by groups (EQLS 0) 50% 45% % 5% 0% 5% 0% 5% 50% 45% % 5% 0% 5% 0% 5% Slovakia Romania Poland 0% France 0% 5% Austria 5% Austria 0% %

5 EU5 % % 50% % EU Linear (EU5) R² = % % 0% R² = % 0% 0% 0% R² = % 0% R² = 0.5 0% % 50% R² = , 007, 0 EQLS, % in difficulties to make ends meet across 5 categories % 0% 0% 0% 0% R² = 0.4 5

6 there are more than half of the EU countries where old is problematic on other QoL indicators as well Source: EQLS 0 Eurofound (0) rd EQLS Overview report, p.0 6

7 What social conditions are behind this pattern that is characteristic to a great number of countries?.0% 50.0%.0% 0.0% 0.0% Bulgaria Czech Republic Estonia Hungary Lithuania Latvia Poland Portugal Romania Slovenia Slovakia 0.0% 0.0%

8 And do income statistics tell a consistent story about ing and increasing difficulties?.. In general, older people (d 65+) are not more at risk of poverty than other groups < > Median income of people d 65 as share of the median income of people d 0-64, total and by gender, 0 ( Eurostat / 05 Pension Adequacy report, ) 8

9 Pension adequacy?.. ARR - Ratio of income from pensions of persons d and income from work of persons d ( Eurostat / 05 Pension Adequacy report) 9

10 Pension adequacy?.. SILC 0 Eurostat / 05 Pension Adequacy report, 0

11 SILC 0, HS0 making ends meet by

12 Correlations (SILC 0): Income and Making ends meet: 0. (aver in EU8) correlation positive negative income BE, BG, CZ, DK, DE, EE, IE, EL, ES, FR, HR, IT, CY, LT, LV, HU, MT, AT, NL, PL, PT, RO, SI, SK, SE, FI, UK make ends meet BE, DK, DE, IE, EL, ES, FR, IT, CY, LU, HU, AT, PT, SE, FI, UK BG, EE, HR, LT, LV, PL, RO, SI, SK

13 Top 0 countries where matters most UK, IE, SE, DK, LU, FI the older, the easier to make ends meet; LV, EE, PL, LT the opposite Regression analysis, t values, SILC 0, variable HS0 (coded as is:,,,4,5,6) UK 0.04*** 5.59 LV -0.05*** -. IE 0.0*** 0.87 EE -0.0*** -0. PL *** -9.8 SE 0.00*** 8.9 DK 0.069*** 8.6 LU 0.04*** 8.5 FI *** 7.78 LT *** -7.9

14 LATVIA Factors affecting Making ends meet Multiple regression () [ LV, EE case]; SILC 0 hs0 Coef. Std. Err. t P>t Beta sex Ref.group: ISCED 0- ISCED ISCED Ref.group: Employed unemployed student retirement other Ref. group: p. HH Household of adults HH of or more persons HH income (standardised) _cons

15 Factors affecting Making ends meet Multiple regression (): controlled for ill health LATVIA hs0 Coef. Std. Err. t P>t Beta sex Ref.group: ISCED ISCED ISCED Ref.group: Employed unemployed student retirement other Ref. group: p. HH Household of adults HH of or more persons Problems with health HH income _cons

16 General health very good, 5 - very bad (SILC 0) HR LU HU MT AT PL PT % CI mean 0 SI 0 RO UK..4 SE.5 FI NL LT 4 LV 4 CY IT FR SK 0.5 ES 0 EL.5 IE EE DE DK.5 CZ BG.5 BE Fitted values 0

17 Unmet medical need SILC 0, PH0 (% who had unmet needs at least once in last months, by groups)

18 EQLS 0 EU5 EU0 Regression Model - controlled for: Adjusted R Square Std. Error of the Estimate Adjusted R Square. country country and sex,, empl.status, education, jobless HH, extended family () and income, deprivation, income insecurity, bad health, lack of optimism Std. Error of the Estimate EU5 EU0. [ Excerpt of the results ] Standardiz ed Coefficient s Collinearity Statistics Standardiz ed Coefficient s Collinearity Statistics Beta t Sig. Tolerance VIF Beta t Sig. Tolerance VIF Highestquartile Bad health Medium optimism Low optimism Deprivation levels expects income to be worse

19 Pseudo-cohorts (methods? examples? please share yours) Latent class analysis: Country clustering Factor analysis: Non-monetary dimensions of making ends meet available in EQLS, for example: Standard of living (satisfaction) Relative financial status (better, same, worse than most others) Satisfaction with state pension system Material living conditions How to represent a trend over the life course? (how steep; how to capture non-linear relations) Next to explore and methodological questions 9

20 EQLS 06 on social insecurity ESS 006: On a 0-0 scale, how worried are you that income in old will not be adequate to cover last years? Draft EQLS 06: On a scale of -0, how worried are you that your income in old will not be sufficient to cover your last years? means not worried at all, 0 means extremely worried. Read out if necessary : Your last years is intended to mean the later sts of the respondents life (not the previous year). Some older respondents may think of this moment in time and that is ok. 0

21 THANK YOU