Drivers of wealth inequality in euro area countries*
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- Dwayne Randall
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1 Wiener Institut für Internationale Wirtschaftsvergleiche The Vienna Institute for International Economic Studies Young Economist Conference, AK Wien, 1-3 October 2015 Drivers of wealth inequality in euro area countries* The effect of inheritance and gifts Applying the Shapley value approach to decomposition Sebastian Leitner Wednesday 1 October, 14:00 *Research was supported by the Austrian Chamber of Labour
2 2 Motivation Rise in ratio of private wealth to GDP in Europe from 1950 s onwards after slump: WWI+II and great depression - contrary to the US Slow rise in wealth inequality from mid 1980 s onwards Rise in the ratio of bequests and gifts to stock of wealth detected for some countries: e.g. for DE & FR, while in others it seems to be (still) stable: UK & SE (Piketty and Zucman, 2014)
3 3 Research Question How important are bequests and inter vivos transfers in shaping inequality in gross and net wealth holdings of households in euro area countries? Wealth accumulation takes place over life cycle via saving investment of available funds; but also via transfers from ancestors Results for the US on the share of inter-generational transfers in total household wealth range from ~20% (Modigliani (1988) to ~80% (Kotlikoff and Summers, 1981,1988); Davies and Shorrocks (2000): 35%-45% depending on types of inter vivos transfers taken into account (education or not), degree of capitalisation of inherited wealth; lower results for SE & UK
4 4 Data Eurosystem Household finance and consumption survey (HFCS) for 2010 (first wave), second wave published euro area countries Multiple imputations (5) 1000 replicate weights High level of harmonisation between countries but not complete (like in EU SILC): Sampling frames, sample sizes, survey modes, oversampling of top wealth households, imputation methods, etc. but: still the best dataset for cross-country comparison of wealth levels and inequality...first (big) step (Tiefensee and Grabka (2014) Data for free but you may need a new computer
5 5 Descriptive Statistics AT BE CY DE ES GR LU PT Number of households received inheritance or gift Gini coefficients Gross wealth Net wealth Inheritance present value Gross household income EU-SILC Net disposable income Source: HFCS UDB 1.1, own calculations.
6 6 Methodology 1 Shapley value approach to decomposition Introduction of regression based approches: Shorrocks (1999), Fields (2003), Wan (2004), Gunantilaka et al. (2006), Israeli (2007)... Outline of methodology (3 explanatory variables) Regression of welfare levels on explanatory variables Predicted welfare level used to calculate the Gini coefficient
7 7 Methodology 2 Elimination of one explanatory variable Second round elimination of two explanatory variables Calculation of marginal contributions of variables - first round contribution - second round contributions
8 8 Methodology 3 Total marginal contributions of variables Unexplained contribution to inequality
9 9 Methodology 4 OLS regression - Dependent variables: Gross and net wealth holdings inverse hyperbolic sine transformed (IHS) 2 y i = IHS ( Wi ) = ln Wi + Wi Semilog model ln y i = antilog since we want to decompose wealth (not IHS wealth) e ln y i = e - Explanatory variables β + β x + β x + β x + ε β 0 β x i β x i β x! i ε ( e ) ( e ) ( e ) e Bequests and gifts by asset types present value with CPI ( ), expectation of substantial gifts or inheritance Gross income, household age + squared, education of household, number of adults and children, marital status of the reference person (Canberra definition)
10 10 Scatter plot: Inheritance versus gross wealth (logs) lngross lninherit lngw Fitted values
11 11 Regression results 1: Net wealth (IHS) Independent Variables AT BE CY DE ES GR LU PT Inheritance by asset types Householdmain 0.211*** 0.086*** 0.106** 0.173*** 0.084*** 0.147*** 0.136*** 0.098*** residence -(IHS) (0.021) (0.021) (0.043) (0.020) (0.013) (0.010) (0.035) (0.014) Money -(IHS) 0.058* *** 0.133*** 0.064*** 0.171** 0.080*** 0.071** (0.031) (0.026) (0.047) (0.022) (0.022) (0.074) (0.025) (0.029) Dwellings excl. HH main 0.087*** 0.056** *** 0.073*** *** residence -(IHS) (0.033) (0.025) (0.050) (0.025) (0.014) (0.023) (0.047) (0.016) Land -(IHS) 0.169*** 0.076*** 0.124*** 0.153*** 0.087*** ** 0.129*** (0.026) (0.024) (0.028) (0.041) (0.015) (0.146) (0.035) (0.016) Business, securities *** *** 0.102*** ** and shares -(IHS) (0.180) (0.026) (0.089) (0.040) (0.017). (0.099) (0.081) Other assets-(ihs) 0.124*** ** 0.098** 0.087*** 0.064* 0.054** 0.122*** (0.033) (0.052) (0.044) (0.045) (0.016) (0.034) (0.022) (0.025) Expectation of substantial 0.859** *** *** gift or inheritance (0.425) (0.270) (0.502) (0.286). (0.319) (0.427) (0.188) Gross income -(IHS) 0.993** 0.446*** 0.321* 1.215*** 0.217** 0.353*** *** (0.437) (0.097) (0.185) (0.240) (0.088) (0.129) (0.258) (0.062)
12 12 Regression results 1: Net wealth (IHS) Independent Variables AT BE CY DE ES GR LU PT Inheritance by asset types Householdmain 0.211*** 0.086*** 0.106** 0.173*** 0.084*** 0.147*** 0.136*** 0.098*** residence -(IHS) Money -(IHS) 0.058* *** 0.133*** 0.064*** 0.171** 0.080*** 0.071** Dwellings excl. HH main 0.087*** 0.056** *** 0.073*** *** residence -(IHS) Land -(IHS) 0.169*** 0.076*** 0.124*** 0.153*** 0.087*** ** 0.129*** Business, securities *** *** 0.102*** ** and shares -(IHS) Other assets-(ihs) 0.124*** ** 0.098** 0.087*** 0.064* 0.054** 0.122*** Expectation of substantial 0.859** *** *** gift or inheritance Gross income -(IHS) 0.993** 0.446*** 0.321* 1.215*** 0.217** 0.353*** ***
13 13 Regression results 2: Net wealth (IHS) Independent Variables AT BE CY DE ES GR LU PT Household age 0.130** 0.196*** *** 0.221*** *** (average of adults) Householdage *** *** *** *** Householdeducation 0.226*** 0.162*** 0.186*** 0.279*** 0.160*** 0.123*** 0.261*** 0.223*** (average years of adults) Number of adults 0.412* 0.638*** ** *** 0.669*** 0.302*** Number of children ** * Reference person: single ** ** ** * *** (Canberra definition) Reference person: ** * *** Widowed (Canberra) Reference person: *** ** *** ** *** *** Divorced (Canberra)
14 14 Shapley value decomposition - gross wealth contribution of groups of explanatory variables to Gini index Gini index Residual (unexplained) Ref. person: Marital status HH structure HH av. education HH av. age HH income Inheritance and gifts GR ES BE LU PT CY DE AT Gini-Index (right scale) Source: HFCS UDB 1.1, wiiw calculations.
15 15 Shapley value decomposition - gross wealth contribution of groups of explanatory variables to explained inequality Ref. person: Marital status HH structure HH av. education Gini index HH av. age HH income GR ES BE LU PT CY DE AT Inheritance and gifts Gini-Index (right scale) Source: HFCS UDB 1.1, wiiw calculations.
16 16 Shapley value decomposition net wealth contribution of groups of explanatory variables to explained inequality Gini index GR ES BE LU PT CY DE AT Residual (unexplained) Ref. person: Marital status HH structure HH av. education HH av. age HH income Inheritance and gifts Gini-Index (right scale) Source: HFCS UDB 1.1, wiiw calculations.
17 17 Shapley value decomposition net wealth contribution of groups of explanatory variables to Gini index Ref. person: Marital status Gini index HH structure HH av. education HH av. age HH income Inheritance and gifts 10 0 GR ES BE LU PT CY DE AT Gini-Index (right scale) Source: HFCS UDB 1.1, wiiw calculations.
18 18 Conclusion High contribution of inheritance and gifts (~40%) to household gross and net wealth inequality in AT, DE and some South European countries Rather low contribution of household income (present!) Age and education: can be interpreted in different ways Further research required: - multilevel models, quantile regressions
19 19 Approaching the final result
20 Wiener Institut für Internationale Wirtschaftsvergleiche I grabbed this from Branco Milanovic! The Vienna Institute for International Economic Studies
21 Wiener Institut für Internationale Wirtschaftsvergleiche I grabbed this from Branco Milanovic! The Vienna Institute for International Economic Studies
22 Wiener Institut für Internationale Wirtschaftsvergleiche The Vienna Institute for International Economic Studies Thank you for your attention!
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