Factor Decomposition of the Wealth Distribution in the Euro Area

Factor Decomposition of the Wealth Distribution in the Euro Area Peter Lindner 1 (Economic Analysis Division, OeNB) Conference: The Future of Capitalism 25 th September 2014 1 Additional to the usual disclaimer, the opinions expressed in this paper and this presentation solely represent those of the author and do not necessarily reflect the official viewpoint of the Oesterreichische Nationalbank or of the Eurosystem. Lindner (OeNB) HFCS 25 th September 2014 1 / 38

Motivation Policy relevance Policies often target specific assets Decomposition allows to see the distributional impact Deepening the understanding of the foundation of distribution Investigate cross-country differences Contribution to the literature Factor decomposition of wealth rather than income Application to a large cross country database New decomposition method based in the recentered influence function Benoît Cœuré Lindner (OeNB) HFCS 25 th September 2014 2 / 38

Outline 1 Background / Literature 2 Decomposition Methods 3 Data 4 Results 5 Conclusions Lindner (OeNB) HFCS 25 th September 2014 3 / 38

Background / Literature Methodology Methodology mostly for income decomposition Long history of authors concerned with decomposition of the distribution: Shorrocks (1982), Lambert and Aronson (1993) natural decomposition Lerman and Yitzhaki (1985), Silber (1989) additive decomposition of Gini Coefficient Sastre and Trannoy (2002), Araar (2006), or Shorrocks (2013) decomposition based on Shapley value Fortin et al. (2011), Firpo et al. (2007) decomposition based on recentered influence function Lindner (OeNB) HFCS 25 th September 2014 4 / 38

Background / Literature Income Huge literature on various ways of decomposing income Subgroup decompositions: Okamoto (2011), Chernozhukov et al. (2009), Firpo et al. (2007), Yun (2006), Fields (2003), Juhn et al. (1993) for the U.S. Machado and Mata (2005) for Portugal; Celestin and Clovis (2012) for Cameroon; Fournier (2001) for Taiwan; Morduch and Sicular (2002) for China; Bourguignon et al. (2008) for a comparison of Brazil and the US; López-Feldman et al. (2006) for Mexico. Change over time: Gunatilaka and Chotikapanich (2009), Firpo et al. (2007), Mookherjee and Shorrocks (1982), Fiorio (2006), Yun (2006) Decomposition according to income sources: Paul (2004), Fräßdorf et al. (2011) Lerman and Yitzhaki (1985) Lindner (OeNB) HFCS 25 th September 2014 5 / 38

Background / Literature Wealth Few approaches in the literature tackling wealth Sierminska et al. (2012) and (2008): Differences of certain socio-economic characteristics in explaining the wealth portfolio of households in the United States, Germany, Italy, Luxembourg and Spain. Decomposition of the gender wealth gap in Germany Regression based approach yields wealth gap can be attributed mostly to differences in individuals characteristics. Azpitarte (2008): Includes in his study about the household wealth distribution in Spain a decomposition according to components finding that in Spain for the year 2002 around four fifth of the inequality is explained by real assets and only one fifth by financial assets. Brandoliniet al. (2004) Includes a decomposition with similar results for Italian data. Lindner (OeNB) HFCS 25 th September 2014 6 / 38

Decomposition Methods Natural Early approach based on Shorrocks (1982) showing the contribution is s k = cov(w k, w) σ 2 (w) Lindner (OeNB) HFCS 25 th September 2014 7 / 38

Decomposition Methods Additive Lerman and Yitzhaki (1985) use the additive separability of the covariance to show GC(w) = K k=1 cov[w k, F (w)] 2cov[w k, F (w k )] µ k cov[w k, F (w k )] µ k µ GC(w) = K s k gc k a k. k=1 (Relative) Partial derivative (chain rule) GC(w) ε k := ε k GC(w) = a ks k gc k GC(w) a k. Lindner (OeNB) HFCS 25 th September 2014 8 / 38

Decomposition Methods Shapley Shorrocks (2013) and Chantreuil and Trannoy (2013) provide analytical framework to get the contribution of factor k as s k = z Z k z (z 1)!(K z )! [GC(w(z)) GC(w(z k))] K! Lindner (OeNB) HFCS 25 th September 2014 9 / 38

Decomposition Methods RIF I Based on Fortin et al. (2011) and Firpo et al. (2007) using RIF regressions to decompose income inequality according to subgroups. Extend this approach for factor decomposition. Suppose small changes in source w k, i.e. think about the counterfactual contribution of w corresponding to a proportional increase in w k w(α) := K (1 + α k ) w k, k=1 marginal contribution of factor k to inequality (inequality measure ν(w(α))) can be defined as s k := ν(w(α)) α k If ν has a differentiable recentered influence function, we can write this as RIF (ν(w)) s k = E[ w k ]. w Lindner (OeNB) HFCS 25 th September 2014 10 / 38

Decomposition Methods RIF II For the Gini Coefficient RIF (GC(w)) = w µ GC + 1 w µ + 2 µ hence w s k = E[( GC µ 1 µ + 2 µ F (w)) w k] 0 F (x)dx Since Gini Coefficent is homogeneous of degree zero, i.e. ν(κ α) = ν(α), we have s k = 0 k Lindner (OeNB) HFCS 25 th September 2014 11 / 38

Data Euro Area HFCS Unit of collection: household (some information at the personal level) Information collected includes assets, liabilities, income, socio-demographic characteristics All euro area countries (except Ireland and Estonia in the 1 st wave) Field period of the first wave 2010/2011 (exception ES with some households in 2008) A priori harmonized questionnaire and survey techniques (e.g. CAPI interviewing) Harmonisation also of editing and imputation ECB coordinates and supervises quality and methodological consistency International State of the Art concerning data production Complex probability sampling design representative at the country level 62.521 households surveyed in the euro area (response rate varies across countries) Missing data are multiple imputed (Bayesian approach, 5 implicates) Estimations use final household weights and takes the imputation structure into account Lindner (OeNB) HFCS 25 th September 2014 12 / 38

Data Classification of Real Assets Households main residence (HMR) Further real estate (FRE): All forms of real estate such as holiday homes, landed property, rented out property, but also forests or rented out office buildings; excluding HMR (or potentially owned as BUS). Business assets (BUS): Net value of business assets that are owned by the household and where at least one household member works. Other real assets (REST REAL): Other tangible assets; mainly there are all forms of vehicles, but in some cases also other valuables such as collections of pieces of art. Lindner (OeNB) HFCS 25 th September 2014 13 / 38

Data Classification of Financial Assets Safe financial assets (SAFE): Sight and savings accounts (including savings in building societies accounts) as well as life insurances and voluntary private pension plans. Risky financial investments (RISKY): Shares, bonds, and mutual funds. Other financial assets (REST FIN): All other forms of financial assets such as silent partnerships, managed accounts, or money owed to a household. Lindner (OeNB) HFCS 25 th September 2014 14 / 38

Results Shares I Figure: Share of Total Real Asset Components in terms of Gross Wealth Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 15 / 38

Results Shares II Figure: Share of Total Financial Asset Components in terms of Gross Wealth Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 16 / 38

Results Descriptive Statistics HMR FRE BUS REST REAL SAFE RISKY REST FIN Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) EA 0.601 180 0.231 103 0.111 30 0.841 7 0.967 9 0.202 12 0.125 3 AT 0.477 200 0.134 94 0.094 181 0.799 9 0.994 12 0.146 12 0.114 3 BE 0.696 250 0.164 174 0.066 50 0.802 8 0.979 21 0.307 20 0.106 4 CY 0.767 240 0.516 202 0.195 99 0.895 10 0.859 18 0.363 2 0.101 9 DE 0.442 168 0.178 115 0.091 19 0.732 8 0.991 13 0.230 12 0.223 3 ES 0.827 180 0.362 120 0.142 51 0.799 7 0.982 5 0.140 12 0.080 7 FI 0.692 128 0.298 108 0.138 1 0.679 9 1.000 6 0.387 4 0.000. FR 0.553 194 0.247 116 0.089 53 1.000 4 0.996 9 0.217 8 0.121 4 GR 0.724 100 0.379 62 0.098 36 0.735 6 0.739 4 0.040 7 0.041 3 IT 0.687 200 0.249 100 0.180 15 0.951 10 0.919 7 0.198 22 0.049 10 LU 0.671 500 0.282 300 0.052 98 0.884 19 0.984 23 0.258 28 0.088 5 MT 0.777 187 0.314 120 0.115 137 0.875 7 0.969 18 0.337 22 0.060 9 NL 0.571 240 0.061 166 0.048 52 0.826 7 0.973 30 0.239 8 0.107 2 PT 0.715 90 0.271 53 0.077 47 0.741 5 0.943 4 0.065 9 0.085 4 SI 0.818 111 0.232 52 0.116 25 0.804 3 0.936 1 0.203 3 0.067 4 SK 0.899 56 0.153 16 0.107 5 0.685 5 0.915 2 0.041 1 0.103 1 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 17 / 38

Results Descriptive Statistics HMR FRE BUS REST REAL SAFE RISKY REST FIN Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) EA 0.601 180 0.231 103 0.111 30 0.841 7 0.967 9 0.202 12 0.125 3 AT 0.477 200 0.134 94 0.094 181 0.799 9 0.994 12 0.146 12 0.114 3 BE 0.696 250 0.164 174 0.066 50 0.802 8 0.979 21 0.307 20 0.106 4 CY 0.767 240 0.516 202 0.195 99 0.895 10 0.859 18 0.363 2 0.101 9 DE 0.442 168 0.178 115 0.091 19 0.732 8 0.991 13 0.230 12 0.223 3 ES 0.827 180 0.362 120 0.142 51 0.799 7 0.982 5 0.140 12 0.080 7 FI 0.692 128 0.298 108 0.138 1 0.679 9 1.000 6 0.387 4 0.000. FR 0.553 194 0.247 116 0.089 53 1.000 4 0.996 9 0.217 8 0.121 4 GR 0.724 100 0.379 62 0.098 36 0.735 6 0.739 4 0.040 7 0.041 3 IT 0.687 200 0.249 100 0.180 15 0.951 10 0.919 7 0.198 22 0.049 10 LU 0.671 500 0.282 300 0.052 98 0.884 19 0.984 23 0.258 28 0.088 5 MT 0.777 187 0.314 120 0.115 137 0.875 7 0.969 18 0.337 22 0.060 9 NL 0.571 240 0.061 166 0.048 52 0.826 7 0.973 30 0.239 8 0.107 2 PT 0.715 90 0.271 53 0.077 47 0.741 5 0.943 4 0.065 9 0.085 4 SI 0.818 111 0.232 52 0.116 25 0.804 3 0.936 1 0.203 3 0.067 4 SK 0.899 56 0.153 16 0.107 5 0.685 5 0.915 2 0.041 1 0.103 1 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 18 / 38

Results Descriptive Statistics HMR FRE BUS REST REAL SAFE RISKY REST FIN Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) EA 0.601 180 0.231 103 0.111 30 0.841 7 0.967 9 0.202 12 0.125 3 AT 0.477 200 0.134 94 0.094 181 0.799 9 0.994 12 0.146 12 0.114 3 BE 0.696 250 0.164 174 0.066 50 0.802 8 0.979 21 0.307 20 0.106 4 CY 0.767 240 0.516 202 0.195 99 0.895 10 0.859 18 0.363 2 0.101 9 DE 0.442 168 0.178 115 0.091 19 0.732 8 0.991 13 0.230 12 0.223 3 ES 0.827 180 0.362 120 0.142 51 0.799 7 0.982 5 0.140 12 0.080 7 FI 0.692 128 0.298 108 0.138 1 0.679 9 1.000 6 0.387 4 0.000. FR 0.553 194 0.247 116 0.089 53 1.000 4 0.996 9 0.217 8 0.121 4 GR 0.724 100 0.379 62 0.098 36 0.735 6 0.739 4 0.040 7 0.041 3 IT 0.687 200 0.249 100 0.180 15 0.951 10 0.919 7 0.198 22 0.049 10 LU 0.671 500 0.282 300 0.052 98 0.884 19 0.984 23 0.258 28 0.088 5 MT 0.777 187 0.314 120 0.115 137 0.875 7 0.969 18 0.337 22 0.060 9 NL 0.571 240 0.061 166 0.048 52 0.826 7 0.973 30 0.239 8 0.107 2 PT 0.715 90 0.271 53 0.077 47 0.741 5 0.943 4 0.065 9 0.085 4 SI 0.818 111 0.232 52 0.116 25 0.804 3 0.936 1 0.203 3 0.067 4 SK 0.899 56 0.153 16 0.107 5 0.685 5 0.915 2 0.041 1 0.103 1 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 19 / 38

Results Descriptive Statistics HMR FRE BUS REST REAL SAFE RISKY REST FIN Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) EA 0.601 180 0.231 103 0.111 30 0.841 7 0.967 9 0.202 12 0.125 3 AT 0.477 200 0.134 94 0.094 181 0.799 9 0.994 12 0.146 12 0.114 3 BE 0.696 250 0.164 174 0.066 50 0.802 8 0.979 21 0.307 20 0.106 4 CY 0.767 240 0.516 202 0.195 99 0.895 10 0.859 18 0.363 2 0.101 9 DE 0.442 168 0.178 115 0.091 19 0.732 8 0.991 13 0.230 12 0.223 3 ES 0.827 180 0.362 120 0.142 51 0.799 7 0.982 5 0.140 12 0.080 7 FI 0.692 128 0.298 108 0.138 1 0.679 9 1.000 6 0.387 4 0.000. FR 0.553 194 0.247 116 0.089 53 1.000 4 0.996 9 0.217 8 0.121 4 GR 0.724 100 0.379 62 0.098 36 0.735 6 0.739 4 0.040 7 0.041 3 IT 0.687 200 0.249 100 0.180 15 0.951 10 0.919 7 0.198 22 0.049 10 LU 0.671 500 0.282 300 0.052 98 0.884 19 0.984 23 0.258 28 0.088 5 MT 0.777 187 0.314 120 0.115 137 0.875 7 0.969 18 0.337 22 0.060 9 NL 0.571 240 0.061 166 0.048 52 0.826 7 0.973 30 0.239 8 0.107 2 PT 0.715 90 0.271 53 0.077 47 0.741 5 0.943 4 0.065 9 0.085 4 SI 0.818 111 0.232 52 0.116 25 0.804 3 0.936 1 0.203 3 0.067 4 SK 0.899 56 0.153 16 0.107 5 0.685 5 0.915 2 0.041 1 0.103 1 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 20 / 38

Results Descriptive Statistics HMR FRE BUS REST REAL SAFE RISKY REST FIN Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median Part. Median (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) (in k e ) EA 0.601 180 0.231 103 0.111 30 0.841 7 0.967 9 0.202 12 0.125 3 AT 0.477 200 0.134 94 0.094 181 0.799 9 0.994 12 0.146 12 0.114 3 BE 0.696 250 0.164 174 0.066 50 0.802 8 0.979 21 0.307 20 0.106 4 CY 0.767 240 0.516 202 0.195 99 0.895 10 0.859 18 0.363 2 0.101 9 DE 0.442 168 0.178 115 0.091 19 0.732 8 0.991 13 0.230 12 0.223 3 ES 0.827 180 0.362 120 0.142 51 0.799 7 0.982 5 0.140 12 0.080 7 FI 0.692 128 0.298 108 0.138 1 0.679 9 1.000 6 0.387 4 0.000. FR 0.553 194 0.247 116 0.089 53 1.000 4 0.996 9 0.217 8 0.121 4 GR 0.724 100 0.379 62 0.098 36 0.735 6 0.739 4 0.040 7 0.041 3 IT 0.687 200 0.249 100 0.180 15 0.951 10 0.919 7 0.198 22 0.049 10 LU 0.671 500 0.282 300 0.052 98 0.884 19 0.984 23 0.258 28 0.088 5 MT 0.777 187 0.314 120 0.115 137 0.875 7 0.969 18 0.337 22 0.060 9 NL 0.571 240 0.061 166 0.048 52 0.826 7 0.973 30 0.239 8 0.107 2 PT 0.715 90 0.271 53 0.077 47 0.741 5 0.943 4 0.065 9 0.085 4 SI 0.818 111 0.232 52 0.116 25 0.804 3 0.936 1 0.203 3 0.067 4 SK 0.899 56 0.153 16 0.107 5 0.685 5 0.915 2 0.041 1 0.103 1 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 21 / 38

Results Distribution of Gross Wealth Ratios Ineq. Measures Shares P90/ P75/ P90/ Mean/ Top Top Bottom P10 P25 P50 Median Gini GE2 5% 10% 50% EA 183.0 15.2 3.9 1.8 0.645 4.289 0.348 0.476 0.078 AT 233.7 22.4 6.2 3.0 0.734 4.014 0.455 0.588 0.039 BE 206.5 7.7 3.1 1.5 0.573 1.139 0.293 0.415 0.126 CY 107.8 5.2 4.9 2.2 0.662 2.652 0.397 0.534 0.092 DE 449.1 25.7 7.3 3.3 0.725 4.719 0.424 0.557 0.038 ES 233.7 22.4 6.2 1.5 0.542 6.795 0.290 0.410 0.155 FI 221.5 15.0 3.4 1.5 0.583 1.371 0.268 0.398 0.107 FR 233.7 22.4 6.2 1.7 0.651 5.446 0.345 0.476 0.069 GR 94.1 5.7 3.2 1.4 0.539 0.730 0.242 0.373 0.138 IT 233.7 22.4 6.2 1.5 0.599 1.722 0.314 0.441 0.111 LU 145.2 6.9 3.0 1.6 0.614 2.757 0.371 0.479 0.118 MT 39.0 4.5 3.2 1.7 0.592 5.788 0.344 0.456 0.129 NL 96.4 9.6 2.4 1.2 0.514 0.569 0.206 0.324 0.137 PT 164.0 6.7 3.6 1.8 0.635 5.775 0.375 0.494 0.102 SI 62.6 4.6 3.1 1.5 0.521 0.647 0.214 0.352 0.148 SK 10.4 2.5 2.4 1.3 0.436 0.526 0.213 0.322 0.215 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 22 / 38

Results Distribution of Gross Wealth Ratios Ineq. Measures Shares P90/ P75/ P90/ Mean/ Top Top Bottom P10 P25 P50 Median Gini GE2 5% 10% 50% EA 183.0 15.2 3.9 1.8 0.645 4.289 0.348 0.476 0.078 AT 233.7 22.4 6.2 3.0 0.734 4.014 0.455 0.588 0.039 BE 206.5 7.7 3.1 1.5 0.573 1.139 0.293 0.415 0.126 CY 107.8 5.2 4.9 2.2 0.662 2.652 0.397 0.534 0.092 DE 449.1 25.7 7.3 3.3 0.725 4.719 0.424 0.557 0.038 ES 233.7 22.4 6.2 1.5 0.542 6.795 0.290 0.410 0.155 FI 221.5 15.0 3.4 1.5 0.583 1.371 0.268 0.398 0.107 FR 233.7 22.4 6.2 1.7 0.651 5.446 0.345 0.476 0.069 GR 94.1 5.7 3.2 1.4 0.539 0.730 0.242 0.373 0.138 IT 233.7 22.4 6.2 1.5 0.599 1.722 0.314 0.441 0.111 LU 145.2 6.9 3.0 1.6 0.614 2.757 0.371 0.479 0.118 MT 39.0 4.5 3.2 1.7 0.592 5.788 0.344 0.456 0.129 NL 96.4 9.6 2.4 1.2 0.514 0.569 0.206 0.324 0.137 PT 164.0 6.7 3.6 1.8 0.635 5.775 0.375 0.494 0.102 SI 62.6 4.6 3.1 1.5 0.521 0.647 0.214 0.352 0.148 SK 10.4 2.5 2.4 1.3 0.436 0.526 0.213 0.322 0.215 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 23 / 38

Results Distribution of Gross Wealth Ratios Ineq. Measures Shares P90/ P75/ P90/ Mean/ Top Top Bottom P10 P25 P50 Median Gini GE2 5% 10% 50% EA 183.0 15.2 3.9 1.8 0.645 4.289 0.348 0.476 0.078 AT 233.7 22.4 6.2 3.0 0.734 4.014 0.455 0.588 0.039 BE 206.5 7.7 3.1 1.5 0.573 1.139 0.293 0.415 0.126 CY 107.8 5.2 4.9 2.2 0.662 2.652 0.397 0.534 0.092 DE 449.1 25.7 7.3 3.3 0.725 4.719 0.424 0.557 0.038 ES 233.7 22.4 6.2 1.5 0.542 6.795 0.290 0.410 0.155 FI 221.5 15.0 3.4 1.5 0.583 1.371 0.268 0.398 0.107 FR 233.7 22.4 6.2 1.7 0.651 5.446 0.345 0.476 0.069 GR 94.1 5.7 3.2 1.4 0.539 0.730 0.242 0.373 0.138 IT 233.7 22.4 6.2 1.5 0.599 1.722 0.314 0.441 0.111 LU 145.2 6.9 3.0 1.6 0.614 2.757 0.371 0.479 0.118 MT 39.0 4.5 3.2 1.7 0.592 5.788 0.344 0.456 0.129 NL 96.4 9.6 2.4 1.2 0.514 0.569 0.206 0.324 0.137 PT 164.0 6.7 3.6 1.8 0.635 5.775 0.375 0.494 0.102 SI 62.6 4.6 3.1 1.5 0.521 0.647 0.214 0.352 0.148 SK 10.4 2.5 2.4 1.3 0.436 0.526 0.213 0.322 0.215 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 24 / 38

Results Natural Table Lindner (OeNB) HFCS 25 th September 2014 25 / 38

Results Additive, Contribution Table Lindner (OeNB) HFCS 25 th September 2014 26 / 38

Results Shapley Table Lindner (OeNB) HFCS 25 th September 2014 27 / 38

Results Additive, Elasticities Table Lindner (OeNB) HFCS 25 th September 2014 28 / 38

Results RIF Table Lindner (OeNB) HFCS 25 th September 2014 29 / 38

Conclusions Real Assets are major contributing factor to the distribution of wealth in absolute terms In relative terms less widely held asset types (also with lower median) gain importance Elasticities vary across countries and across asset categories Policies that are not considered to target distribution do affect it Impact of monetary policy Impact of support for HMR Different decomposition methods provide different insights Future research: Sub-group decomposition, maybe according to countries/regions Get some standard errors of the estimates Lindner (OeNB) HFCS 25 th September 2014 30 / 38

Thank you for your attention! Lindner (OeNB) HFCS 25 th September 2014 31 / 38

Appendix Lindner (OeNB) HFCS 25 th September 2014 32 / 38

Appendix: Motivation Benoît Cœuré Monetary policy interventions have distributional effects across the population depending on the composition of the assets and liabilities of households. One could argue that monetary policy is in essence distributional in the intertemporal dimension and the euro area crisis has uncovered distributional effects of monetary policy in the spatial dimension. Such effects are however unintended, or in other words, they are a means to an end, that is price stability. Central banks should steer away from distributional politics. But there can be a thin line between intended and unintended consequences, which makes it even more necessary to understand the cross-sectional effects of monetary policy interventions. Opening remarks at the HFC-Conference of the ECB (Frankfurt, 17 th October 2013); published on http://www.ecb.europa.eu/press/key/date/2013/html/sp131017.en.html [accessed 22 nd September 2014] Back Lindner (OeNB) HFCS 25 th September 2014 33 / 38

Appendix: Results Natural Source: Eurosystem HFCS 2010. HMR FRE BUS REST SAFE RISKY REST REAL FIN EA 0.113 0.303 0.444 0.011 0.044 0.043 0.041 AT 0.211 0.172 0.530 0.014 0.032 0.031 0.009 BE 0.228 0.171 0.119 0.017 0.187 0.252 0.026 CY 0.076 0.299 0.580 0.005 0.021 0.011 0.008 DE 0.121 0.285 0.500 0.011 0.038 0.029 0.016 ES 0.051 0.415 0.452 0.006 0.017 0.021 0.038 FI 0.245 0.234 0.205 0.020 0.046 0.250. FR 0.076 0.248 0.426 0.014 0.076 0.070 0.090 GR 0.317 0.487 0.086 0.025 0.070 0.014 0.002 IT 0.314 0.235 0.337 0.018 0.029 0.044 0.023 LU 0.247 0.639 0.054 0.015 0.017 0.026 0.002 MT 0.051 0.088 0.844 0.007 0.005 0.003 0.001 NL 0.479 0.224 0.025 0.020 0.167 0.074 0.011 PT 0.057 0.182 0.644 0.008 0.065 0.043 0.001 SI 0.381 0.276 0.266 0.024 0.034 0.007 0.010 SK 0.550 0.147 0.180 0.051 0.044 0.003 0.024 Lindner (OeNB) HFCS 25 th September 2014 34 / 38 Back

Appendix: Results Additive, Contribution Source: Eurosystem HFCS 2010. HMR FRE BUS REST SAFE RISKY REST REAL FIN s k s k s k s k s k s k s k EA 0.287 0.153 0.087 0.018 0.060 0.030 0.010 AT 0.297 0.093 0.221 0.022 0.063 0.032 0.006 BE 0.231 0.092 0.038 0.012 0.092 0.094 0.014 CY 0.148 0.266 0.196 0.007 0.031 0.008 0.007 DE 0.277 0.179 0.125 0.020 0.080 0.035 0.008 ES 0.211 0.176 0.078 0.011 0.038 0.015 0.013 FI 0.277 0.166 0.030 0.019 0.045 0.046. FR 0.265 0.160 0.076 0.023 0.084 0.030 0.013 GR 0.250 0.201 0.034 0.016 0.033 0.005 0.001 IT 0.327 0.129 0.071 0.015 0.024 0.025 0.008 LU 0.256 0.253 0.026 0.016 0.031 0.029 0.002 MT 0.185 0.125 0.212 0.013 0.031 0.020 0.006 NL 0.319 0.056 0.012 0.011 0.083 0.027 0.005 PT 0.233 0.193 0.112 0.022 0.057 0.013 0.004 SI 0.291 0.103 0.083 0.015 0.022 0.004 0.003 SK 0.289 0.048 0.040 0.024 0.027 0.002 0.006 Back Lindner (OeNB) HFCS 25 th September 2014 35 / 38

Appendix: Results Additive, Elasticities HMR FRE BUS REST SAFE RISKY REST REAL FIN ε k ε k ε k ε k ε k ε k ε k EA -0.061 0.048 0.039-0.014-0.022 0.008 0.002 AT -0.037 0.017 0.066-0.017-0.034 0.006-0.001 BE -0.113 0.042 0.024-0.009-0.002 0.053 0.006 CY -0.105 0.047 0.081-0.010-0.014 0.000 0.001 DE -0.027 0.041 0.042-0.014-0.040 0.001-0.002 ES -0.150 0.088 0.054-0.010 0.002 0.008 0.008 FI -0.071 0.060 0.019-0.014-0.015 0.021. FR -0.068 0.046 0.032-0.011-0.011 0.009 0.004 GR -0.097 0.095 0.015-0.017 0.000 0.003 0.000 IT -0.062 0.052 0.035-0.021-0.015 0.007 0.004 LU -0.101 0.109 0.013-0.011-0.020 0.010 0.000 MT -0.129 0.044 0.133-0.010-0.038-0.002 0.003 NL 0.008 0.044 0.002-0.013-0.059 0.015 0.002 PT -0.110 0.074 0.057-0.014-0.011 0.005-0.001 SI -0.114 0.058 0.067-0.011-0.001 0.000 0.001 SK -0.081 0.043 0.046-0.005-0.010 0.001 0.006 Source: Eurosystem HFCS 2010. Back Lindner (OeNB) HFCS 25 th September 2014 36 / 38

Appendix: Results Shapley Source: Eurosystem HFCS 2010. HMR FRE BUS REST SAFE RISKY REST REAL FIN EA -0.067 0.148 0.172 0.058 0.053 0.140 0.142 AT 0.006 0.151 0.200 0.058 0.037 0.144 0.139 BE -0.146 0.144 0.155 0.070 0.050 0.157 0.144 CY -0.078 0.121 0.210 0.052 0.077 0.136 0.144 DE 0.021 0.162 0.185 0.068 0.023 0.133 0.133 ES -0.192 0.133 0.171 0.058 0.083 0.142 0.148 FI -0.072 0.152 0.182 0.074 0.077 0.169. FR -0.067 0.140 0.164 0.064 0.066 0.142 0.144 GR -0.145 0.128 0.144 0.041 0.088 0.142 0.141 IT -0.095 0.158 0.171 0.024 0.058 0.136 0.147 LU -0.113 0.193 0.156 0.051 0.046 0.140 0.140 MT -0.129 0.140 0.236 0.067 0.022 0.112 0.144 NL -0.083 0.164 0.141 0.045-0.030 0.138 0.140 PT -0.129 0.160 0.183 0.066 0.073 0.145 0.137 SI -0.209 0.141 0.173 0.058 0.094 0.126 0.138 SK -0.244 0.146 0.162 0.044 0.046 0.141 0.142 Lindner (OeNB) HFCS 25 th September 2014 37 / 38 Back

Appendix: Results RIF HMR FRE BUS REST SAFE RISKY REST REAL FIN EA -0.039 0.031 0.025-0.009-0.014 0.005 0.001 AT -0.027 0.012 0.049-0.012-0.025 0.004-0.001 BE -0.065 0.024 0.014-0.005-0.001 0.031 0.004 CY -0.069 0.031 0.054-0.007-0.009 0.000 0.001 DE -0.019 0.030 0.030-0.010-0.029 0.001-0.001 ES -0.081 0.048 0.029-0.006 0.001 0.004 0.005 FI -0.041 0.035 0.011-0.008-0.009 0.012. FR -0.044 0.030 0.021-0.007-0.007 0.006 0.003 GR -0.051 0.052 0.008-0.009 0.000 0.001 0.000 IT -0.037 0.031 0.021-0.012-0.009 0.004 0.003 LU -0.062 0.067 0.008-0.007-0.012 0.006 0.000 MT -0.076 0.027 0.079-0.006-0.023-0.001 0.002 NL 0.005 0.023 0.001-0.007-0.030 0.008 0.001 PT -0.070 0.047 0.036-0.009-0.007 0.003-0.000 SI -0.055 0.031 0.036-0.005-0.000 0.000 0.000 SK -0.034 0.019 0.020-0.002-0.004 0.001 0.003 Source: Eurosystem HFCS 2010. Lindner (OeNB) HFCS 25 th September 2014 38 / 38 Back