Abstract
Against the ongoing assessment of the root causes of rising economic inequality in industrialized countries, analyses of the distribution of savings along the income and wealth distribution are of high interest. We analyze the concentration of household savings in Germany by estimating saving amounts, saving rates and shares in aggregate savings across income and wealth groups. Our calculations are based on the Sample Survey of Household Income and Expenditure (EVS), containing more than 40,000 households in Germany. We show that the concentration of savings is substantial: while the top income decile’s share in total savings reaches 60 percent, the lower half of the income distribution on average does not save at all. Across wealth groups the concentration of savings is somewhat less pronounced. We also look beyond the top income threshold underlying the EVS (18,000 euros of monthly net household income) and demonstrate that corrected saving rates for the top income groups are considerably higher than those derived from the EVS alone. Hence, the top income groups’ shares in aggregate savings exceed estimated shares solely based on EVS data, revealing a substantially more pronounced concentration of savings along the income distribution.
Article Note
This paper is an outcome of the research project “Bedingte Haushaltsersparnis in Deutschland – zentraler Baustein einer endogenen Akkumulationsdynamik” funded by the Hans Böckler Foundation. We gratefully acknowledge the Hans Böckler Foundation for funding and supporting the project. Also, we thank Rolf Kleimann, Stefan Bach and Tobias Brändle for helpful comments and support with regard to the data. Fabian Mayer is acknowledged for excellent research assistance.
References
Adler, M., K. Schmid (2013), Factor Shares and Income Inequality. Evidence from Germany, 2002–2008. Journal of Applied Social Science Studies 133(2): 121–132.Search in Google Scholar
Aspromourgos, T. (2015), T. Piketty, The Future of Capitalism and the Theory of Distribution: A Review Essay. Metroeconomica 66(2): 284–305.10.1111/meca.12071Search in Google Scholar
Atkinson, A. (2009), Factor Shares: The Principal Problem of Political Economy? Oxford Review of Economic Policy 25(1): 3–16.10.1093/oxrep/grp007Search in Google Scholar
Bach, S., M. Beznoska, V. Steiner (2016), Wer trägt die Steuerlast in Deutschland? Verteilungswirkungen des deutschen Steuer- und Transfersystems. DIW Berlin, Politikberatung kompakt 112.Search in Google Scholar
Bach, S., G. Corneo, V. Steiner (2009), From Bottom to Top: The Entire Income Distribution in Germany, 1992–2003. The Review of Income and Wealth 55(2): 303–330.10.1111/j.1475-4991.2009.00317.xSearch in Google Scholar
Bach, S., G. Corneo, V. Steiner (2013), Effective Taxation of Top Incomes in Germany, 1992–2002. German Economic Review 14(2): 115–137.10.1111/j.1468-0475.2012.00570.xSearch in Google Scholar
Bach, S., A. Thiemann, A. Zucco (2015), The Top Tail of the Wealth Distribution in Germany, France, Spain, and Greece. DIW Berlin Discussion Papers, No. 1502.10.2139/ssrn.2655990Search in Google Scholar
Bartels, C., K. Jenderny (2014), The Role of Capital Income for Top Incomes Shares in Germany. Discussion Papers 2014/32, Freie Universität Berlin, School of Business & Economics.Search in Google Scholar
Bartzsch, N. (2008), Precautionary Saving and Income Uncertainty in Germany – New Evidence from Microdata. Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik) 228(1): 5–24.10.1515/jbnst-2008-0103Search in Google Scholar
Behringer, J., T. Theobald, T. van Treeck (2014), Income and Wealth Distribution in Germany: A Macro-Economic Perspective. IMK Report 99e.Search in Google Scholar
Biewen, M., A. Juhasz (2012), Understanding Rising Income Inequality in Germany, 1999/2000–2005/2006. The Review of Income and Wealth 58(4): 622–647.10.1111/j.1475-4991.2012.00514.xSearch in Google Scholar
Börsch-Supan, A., L. Essig (2005), Household Saving in Germany: Results of the First SAVE Study. in: D. Wise (ed.), Analyses in the Economics of Aging: 317–352. Chicago, IL: University of Chicago Press.10.7208/chicago/9780226903217.003.0011Search in Google Scholar
Börsch-Supan, A., A. Reil-Held, R. Rodepeter, R. Schnabel, J. Winter (2001), The German Savings Puzzle. Research in Economics 55(1): 15–38.10.1006/reec.2000.0241Search in Google Scholar
Börsch-Supan, A., A. Reil-Held, D. Schunk (2006), Das Sparverhalten deutscher Haushalte: Erste Erfahrungen mit der Riesterrente. Gutachten für das Bundesministerium für Bildung und Forschung im Rahmen des Vorhabens „Bildungssparen“. Mannheim Research Institute for the Economics of Aging (MEA).Search in Google Scholar
Brenke, K., M. Grabka (2011), Schwache Lohnentwicklung im letzten Jahrzehnt. DIW Wochenbericht 78(45): 3–15.Search in Google Scholar
Brenke, K., G. Wagner (2013), Ungleiche Verteilung der Einkommen bremst das Wirtschaftswachstum. Wirtschaftsdienst 93(2): 110–116.10.1007/s10273-013-1493-5Search in Google Scholar
Coppola, M., B. Lamla (2013), Saving and Old-Age Provision in Germany (SAVE): Design and Enhancements. Schmollers Jahrbuch 133(1): 109–117.10.3790/schm.133.1.109Search in Google Scholar
Corneo, G. (2015), Kreuz und quer durch die deutsche Einkommensverteilung. Perspektiven der Wirtschaftspolitik 16(2): 109–126.10.1515/pwp-2015-0009Search in Google Scholar
Corneo, G., M. Keese, C. Schröder (2009), The Riester Scheme and Private Savings: An Empirical Analysis Based on the German SOEP. Schmollers Jahrbuch 129: 321–332.10.3790/schm.129.2.321Search in Google Scholar
Crossley, T.F., J.K. Winter (2015), Asking Households about Expenditures: What Have We Learned?: 23–50 in: C.D. Carroll, T.F. Crossley, J. Sabelhaus (eds.), Improving the Measurement of Consumer Expenditures. Studies in Income and Wealth Vol. 74. Chicago, IL: University of Chicago Press.10.7208/chicago/9780226194714.001.0001Search in Google Scholar
Destatis (2008), Wirtschaftsrechnungen. Einkommens- und Verbrauchsstichprobe. Aufgabe, Methode und Durchführung. Statistisches Bundesamt, Fachserie 15, Heft 7.Search in Google Scholar
Destatis (2015), Wirtschaftsrechnungen. Einkommens- und Verbrauchsstichprobe. Einnahmen und Ausgaben privater Haushalte. Statistisches Bundesamt, Fachserie 15, Heft 4.Search in Google Scholar
Deutsche Bundesbank (2013), Vermögen und Finanzen privater Haushalte in Deutschland: Ergebnisse der Bundesbankstudie. Deutsche Bundesbank Monatsbericht Juni 2013, Frankfurt.Search in Google Scholar
Deutsche Bundesbank (2016), Household Wealth and Finances in Germany: Results of the 2014 Survey. Monthly Report, March 2016: 57–82.Search in Google Scholar
Drechsel-Grau, M., A. Peichl, K. Schmid (2015), Einkommensverteilung und gesamtwirtschaftliche Entwicklung in Deutschland: Spitzeneinkommen – ein Missing-Link. Wirtschaftsdienst 95(10): 684–688.10.1007/s10273-015-1887-7Search in Google Scholar
Drechsel-Grau, M., K. Schmid (2014), Consumption–Savings Decisions under Upward-Looking Comparisons. Journal of Economic Behavior & Organization 106: 254–268.10.1016/j.jebo.2014.07.006Search in Google Scholar
Fuchs-Schündeln, N. (2008), The Response of Household Saving to the Large Shock of German Reunification. The American Economic Review 98(5): 1798–1828.10.1257/aer.98.5.1798Search in Google Scholar
Horn, G., S. Gechert, M. Rehm, K. Schmid (2014), Wirtschaftskrise unterbricht Anstieg der Einkommensungleichheit. IMK Report No. 97.Search in Google Scholar
IAW (2011), Aktualisierung der Berichterstattung über die Verteilung von Einkommen und Vermögen in Deutschland für den 4. Armuts- und Reichtumsbericht der Bundesregierung. Tübingen, Institute for Applied Economic Research (IAW).Search in Google Scholar
IAW, ZEW (2015), Analyse der Verteilung von Einkommen und Vermögen in Deutschland. Unpublished report. Tübingen, Institute for Applied Economic Research and Mannheim, Centre for European Economic Research.Search in Google Scholar
IMF (2015), Causes and Consequences of Income Inequality: A Global Perspective. IMF Staff Discussion Note 15(13): 1–39.Search in Google Scholar
Kalina, T., C. Weinkopf (2012), Niedriglohnbeschäftigung 2010: fast jede/r vierte arbeitet für Niedriglohn. IAQ Report, No. 1.Search in Google Scholar
Klär, E., J. Slacalek (2006), Entwicklung der Sparquote in Deutschland: Hindernis für die Erholung der Konsumnachfrage. DIW Wochenbericht 73(40): 537–543.Search in Google Scholar
Krämer, H. (2015), Make no mistake, Thomas! Verteilungstheorie und Ungleichheitsdynamik bei Piketty. in: P. Bofinger, G. Horn, K. Schmid, T. van Treeck (eds.), Thomas Piketty und die Verteilungsfrage. Analysen, Bewertungen und wirtschaftspolitische Implikationen für Deutschland: 37–71. Berlin: SE Publishing.Search in Google Scholar
Mau, S., J. Heuer (2016), Wachsende Ungleichheit als Gefahr für nachhaltiges Wachstum. Wie die Bevölkerung über soziale Unterschiede denkt. Beitrag im Rahmen des Projekts „Gute Gesellschaft – Soziale Demokratie 2017plus“ der Friedrich-Ebert-Stiftung.Search in Google Scholar
OECD (2015), In It Together: Why Less Inequality Benefits All. Paris, OECD Publishing.Search in Google Scholar
Schmid, K., M. Drechsel-Grau, A. Peichl (2015), Factor Shares, Personal Income Distribution and Top Incomes in Germany. Income Inequality - Quo Vadis? IMK Report, No. 108e.Search in Google Scholar
Schmid, K., U. Stein (2013), Explaining Rising Income Inequality in Germany, 1991–2010. IMK Study, No. 32.10.2139/ssrn.2339128Search in Google Scholar
Späth, J., K.D. Schmid (2016), The Distribution of Household Savings in Germany, IAW Discussion Papers 128, Institut für Angewandte Wirtschaftsforschung (IAW).Search in Google Scholar
van Treeck, T. (2014), Zur Bedeutung unterschiedlicher Sparquoten für Pikettys „Gesetze des Kapitalismus“. Einige einfache Simulationen, http://verteilungsfrage.org/2014/07/zur-bedeutung-unterschiedlicher-sparquoten-fuer-piketty/Search in Google Scholar
Vermeulen, P. (2014), How Fat Is the Top Tail of the Wealth Distribution? Working Paper Series 1692, European Central Bank.10.2139/ssrn.2439164Search in Google Scholar
Vermeulen, P. (2016), Estimating the Top Tail of the Wealth Distribution. American Economic Review 106(5): 646–650.10.1257/aer.p20161021Search in Google Scholar
Westermeier, C., M. Grabka (2015), Significant Statistical Uncertainty over Share of High Net Worth Households. DIW Economic Bulletin 5(14/15): 210–219.Search in Google Scholar
Ziegelmeyer, M. (2010), Das Altersvorsorge-Verhalten von Selbständigen - eine Analyse auf Basis der SAVE-Daten. Schmollers Jahrbuch 130(2): 195–240.10.3790/schm.130.2.195Search in Google Scholar
Ziegelmeyer, M. (2011), Nursing Home Residents Make a Difference – The Overestimation of Saving Rates at Older Ages, MEA discussion paper series 210–2010, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.Search in Google Scholar
Ziegelmeyer, M. (2012), Nursing Home Residents Make a Difference - the Overestimation of Saving Rates at Older Ages. Economics Letters 117(3): 569–572.10.1016/j.econlet.2012.07.037Search in Google Scholar
Appendix
Summary statistics on income and wealth groups (in euros).
Household net income per year | Household net wealth | ||||||
---|---|---|---|---|---|---|---|
By income groups | By wealth groups | ||||||
2003 | 2008 | 2013 | 2003 | 2008 | 2013 | ||
1st decile | n | 1,978 | 2,362 | 2,723 | 3,658 | 5,177 | 3,794 |
mean | 10,457 | 9,573 | 9,600 | −10,097 | −12,061 | −16,138 | |
median | 10,665 | 9,749 | 9,732 | 0 | −1,116 | −7,025 | |
sd | 2,073 | 1,872 | 1,768 | 38,005 | 40,229 | 32,241 | |
2nd decile | n | 2,315 | 2,662 | 2,937 | 2,367 | 1,213 | 3,027 |
mean | 15,917 | 14,539 | 14,574 | 1,270 | 303 | 26 | |
median | 15,948 | 14,572 | 14,648 | 1,154 | 268 | 0 | |
sd | 1,358 | 1,271 | 1,326 | 984 | 246 | 90 | |
3rd decile | n | 2,893 | 3,134 | 3,333 | 3,175 | 3,155 | 3,307 |
mean | 20,488 | 18,945 | 19,065 | 6,787 | 3,193 | 2,330 | |
median | 20,476 | 18,962 | 19,064 | 6,616 | 3,042 | 2,103 | |
sd | 1,350 | 1,291 | 1,299 | 2,242 | 1,662 | 1,386 | |
4th decile | n | 3,611 | 3,549 | 3,798 | 3,700 | 3,759 | 3,806 |
mean | 25,496 | 23,298 | 23,583 | 17,394 | 11,653 | 10,173 | |
median | 25,453 | 23,314 | 23,532 | 17,099 | 11,295 | 9,951 | |
sd | 1,536 | 1,255 | 1,330 | 4,116 | 3,361 | 3,279 | |
5th decile | n | 3,945 | 4,063 | 4,385 | 4,302 | 4,320 | 4,215 |
mean | 31,034 | 27,965 | 28,619 | 37,304 | 27,837 | 26,200 | |
median | 31,108 | 27,940 | 28,612 | 36,228 | 27,234 | 25,521 | |
sd | 1,619 | 1,451 | 1,565 | 7,711 | 6,294 | 6,333 | |
6th decile | n | 4,289 | 4,601 | 4,778 | 4,506 | 4,758 | 4,648 |
mean | 36,916 | 33,543 | 34,506 | 74,397 | 57,518 | 58,667 | |
median | 36,915 | 33,479 | 34,388 | 73,680 | 56,566 | 57,686 | |
sd | 1,787 | 1,810 | 1,892 | 13,683 | 11,110 | 12,585 | |
7th decile | n | 4,624 | 5,163 | 5,049 | 4,880 | 5,081 | 4,843 |
mean | 43,578 | 40,461 | 41,863 | 132,423 | 106,715 | 109,787 | |
median | 43,542 | 40,356 | 41,820 | 131,038 | 106,105 | 108,891 | |
sd | 2,029 | 2,191 | 2,363 | 19,449 | 17,051 | 17,121 | |
8th decile | n | 5,430 | 5,822 | 5,265 | 5,201 | 5,340 | 4,985 |
mean | 51,748 | 49,118 | 51,214 | 209,502 | 174,822 | 178,743 | |
median | 51,613 | 48,973 | 51,040 | 208,686 | 173,365 | 177,653 | |
sd | 2,813 | 2,910 | 3,072 | 25,221 | 22,901 | 23,011 | |
9th decile | n | 6,431 | 6,496 | 5,594 | 5,259 | 5,631 | 5,123 |
mean | 64,241 | 61,838 | 64,990 | 314,945 | 277,636 | 281,536 | |
median | 63,868 | 61,316 | 64,552 | 311,179 | 272,637 | 278,312 | |
sd | 4,683 | 4,802 | 5,096 | 37,848 | 39,313 | 38,404 | |
91st–95th percentile | n | 3,565 | 3,338 | 2,683 | 2,761 | 2,916 | 2,653 |
mean | 80,520 | 78,822 | 82,699 | 452,438 | 424,910 | 428,286 | |
median | 79,976 | 78,405 | 82,172 | 447,968 | 420,719 | 422,582 | |
sd | 4,766 | 4,830 | 4,999 | 41,331 | 46,481 | 46,842 | |
96th–99th percentile | n | 2,996 | 2,388 | 1,910 | 2,310 | 2,258 | 1,950 |
mean | 105,695 | 104,250 | 109,092 | 705,800 | 711,106 | 694,387 | |
median | 102,660 | 101,501 | 105,972 | 673,195 | 675,777 | 661,476 | |
sd | 12,252 | 11,921 | 13,015 | 133,444 | 153,409 | 135,056 | |
100th percentile | n | 653 | 455 | 329 | 611 | 425 | 433 |
mean | 170,347 | 162,307 | 166,679 | 1,868,203 | 1,819,950 | 1,625,481 | |
median | 161,420 | 154,907 | 161,916 | 1,323,268 | 1,457,590 | 1,357,254 | |
sd | 30,339 | 24,278 | 20,337 | 2,018,637 | 1,108,865 | 840,959 | |
Total | n | 42,730 | 44,033 | 42,784 | 42,730 | 44,033 | 42,784 |
mean | 39,941 | 37,660 | 38,962 | 147,704 | 131,954 | 130,558 | |
median | 33,877 | 30,564 | 31,364 | 52,808 | 40,193 | 38,753 | |
sd | 27,077 | 26,583 | 27,892 | 319,215 | 266,696 | 242,571 |
Source: Research Data Centers of the Federal Statistical Office and the statistical offices of the Länder, EVS, 2003–2013, own calculations. Calculations based on 2013 euros.
Summary statistics, yearly saving amounts by income and wealth groups (in euros).
Savings | |||||||
---|---|---|---|---|---|---|---|
By income groups | By wealth groups | ||||||
2003 | 2008 | 2013 | 2003 | 2008 | 2013 | ||
1st decile | n | 1,978 | 2,362 | 2,723 | 3,658 | 5,177 | 3,794 |
mean | −1,006 | −1,247 | −1,213 | 1,780 | 1,698 | 2,243 | |
median | 0 | 0 | 0 | 566 | 514 | 1,664 | |
sd | 5,210 | 5,710 | 8,155 | 16,407 | 9,909 | 13,521 | |
2nd decile | n | 2,315 | 2,662 | 2,937 | 2,367 | 1,213 | 3,027 |
mean | 50 | −491 | −741 | 1,046 | 313 | 398 | |
median | 368 | 116 | 60 | 533 | 219 | 0 | |
sd | 6,145 | 6,485 | 5,652 | 12,112 | 6,847 | 7,417 | |
3rd decile | n | 2,893 | 3,134 | 3,333 | 3,175 | 3,155 | 3,307 |
mean | 123 | −138 | −602 | 1,126 | 791 | 890 | |
median | 1,005 | 643 | 492 | 1,090 | 630 | 492 | |
sd | 10,957 | 7,016 | 9,731 | 14,132 | 7,550 | 7,348 | |
4th decile | n | 3,611 | 3,549 | 3,798 | 3,700 | 3,759 | 3,806 |
mean | 662 | 464 | 197 | 2,031 | 1,873 | 1,289 | |
median | 1,637 | 1,299 | 996 | 1,825 | 1,248 | 1,008 | |
sd | 11,773 | 10,243 | 9,999 | 11,783 | 11,241 | 11,994 | |
5th decile | n | 3,945 | 4,063 | 4,385 | 4,302 | 4,320 | 4,215 |
mean | 1,567 | 535 | 821 | 3,218 | 2,386 | 2,446 | |
median | 2,830 | 1,929 | 1,736 | 3,090 | 2,058 | 2,040 | |
sd | 21,129 | 12,283 | 18,670 | 29,171 | 11,694 | 16,502 | |
6th decile | n | 4,289 | 4,601 | 4,778 | 4,506 | 4,758 | 4,648 |
mean | 2,076 | 1,266 | 1,248 | 4,404 | 3,553 | 3,953 | |
median | 3,863 | 2,997 | 2,720 | 4,717 | 3,464 | 3,300 | |
sd | 18,492 | 19,851 | 15,153 | 23,394 | 14,756 | 25,024 | |
7th decile | n | 4,624 | 5,163 | 5,049 | 4,880 | 5,081 | 4,843 |
mean | 4,047 | 3,595 | 2,244 | 6,102 | 5,091 | 5,166 | |
median | 5,571 | 4,737 | 4,328 | 5,325 | 4,592 | 4,280 | |
sd | 24,536 | 15,722 | 28,063 | 30,101 | 16,349 | 20,310 | |
8th decile | n | 5,430 | 5,822 | 5,265 | 5,201 | 5,340 | 4,985 |
mean | 6,125 | 5,962 | 5,542 | 5,955 | 5,632 | 5,254 | |
median | 7,585 | 6,997 | 6,540 | 5,613 | 5,158 | 4,704 | |
sd | 29,248 | 20,016 | 25,559 | 25,514 | 20,050 | 21,249 | |
9th decile | n | 6,431 | 6,496 | 5,594 | 5,259 | 5,631 | 5,123 |
mean | 8,451 | 8,255 | 8,478 | 7,017 | 7,247 | 5,764 | |
median | 10,363 | 9,723 | 10,032 | 6,500 | 5,874 | 5,372 | |
sd | 27,163 | 21,273 | 36,702 | 24,087 | 23,423 | 34,688 | |
91st–95th percentile | n | 3,565 | 3,338 | 2,683 | 2,761 | 2,916 | 2,653 |
mean | 13,988 | 14,923 | 14,031 | 9,690 | 10,227 | 8,951 | |
median | 15,217 | 14,812 | 14,228 | 8,458 | 7,305 | 7,300 | |
sd | 34,277 | 28,271 | 32,994 | 26,837 | 27,809 | 32,163 | |
96th–99th percentile | n | 2,996 | 2,388 | 1,910 | 2,310 | 2,258 | 1,950 |
mean | 22,964 | 24,028 | 25,411 | 12,632 | 13,599 | 11,682 | |
median | 24,297 | 23,005 | 23,836 | 10,769 | 11,134 | 11,244 | |
sd | 43,885 | 39,473 | 43,419 | 41,632 | 45,480 | 56,897 | |
100th percentile | n | 653 | 455 | 329 | 611 | 425 | 433 |
mean | 67,334 | 64,196 | 58,349 | 23,000 | 17,824 | 24,204 | |
median | 57,906 | 62,825 | 55,344 | 15,684 | 13,273 | 17,932 | |
sd | 84,119 | 70,448 | 62,287 | 76,057 | 91,129 | 81,887 | |
Total | n | 42,730 | 44,033 | 42,784 | 42,730 | 44,033 | 42,784 |
mean | 4,500 | 4,169 | 3,897 | 4,500 | 4,169 | 3,897 | |
median | 2,854 | 2,109 | 1,860 | 2,854 | 2,109 | 1,860 | |
sd | 24,623 | 20,229 | 24,492 | 24,623 | 20,229 | 24,492 |
Source: Research Data Centers of the Federal Statistical Office and the statistical offices of the Länder, EVS, 2003–2013, own calculations. Calculations based on 2013 euros.
Summary statistics, yearly saving rates by income and wealth groups (in percent).
Saving rates | |||||||
---|---|---|---|---|---|---|---|
By income groups | By wealth groups | ||||||
2003 | 2008 | 2013 | 2003 | 2008 | 2013 | ||
1st decile | n | 1,978 | 2,362 | 2,723 | 3,658 | 5,177 | 3,794 |
mean | −9.6 | −13.0 | −12.6 | 7.4 | 7.2 | 7.7 | |
median | 0.0 | 0.0 | 0.0 | 8.5 | 8.0 | 9.9 | |
sd | 91.6 | 96.1 | 111.1 | 52.1 | 34.5 | 34.4 | |
2nd decile | n | 2,315 | 2,662 | 2,937 | 2,367 | 1,213 | 3,027 |
mean | 0.3 | −3.4 | −5.1 | 5.0 | 1.7 | 2.4 | |
median | 2.4 | 0.9 | 0.4 | 4.7 | 2.6 | 0.0 | |
sd | 38.3 | 45.2 | 38.8 | 46.8 | 29.8 | 39.2 | |
3rd decile | n | 2,893 | 3,134 | 3,333 | 3,175 | 3,155 | 3,307 |
mean | 0.6 | −0.7 | −3.2 | 4.5 | 3.6 | 4.1 | |
median | 4.9 | 3.3 | 2.7 | 7.6 | 5.3 | 4.7 | |
sd | 52.9 | 37.3 | 50.9 | 46.7 | 30.2 | 29.6 | |
4th decile | n | 3,611 | 3,549 | 3,798 | 3,700 | 3,759 | 3,806 |
mean | 2.6 | 2.0 | 0.8 | 7.0 | 7.1 | 4.8 | |
median | 6.6 | 5.7 | 4.2 | 9.5 | 8.0 | 7.2 | |
sd | 46.0 | 44.2 | 42.2 | 42.7 | 32.5 | 49.3 | |
5th decile | n | 3,945 | 4,063 | 4,385 | 4,302 | 4,320 | 4,215 |
mean | 5.1 | 1.9 | 2.9 | 8.9 | 7.5 | 7.4 | |
median | 9.1 | 7.0 | 6.0 | 12.3 | 10.5 | 9.9 | |
sd | 67.5 | 43.7 | 65.0 | 70.6 | 32.6 | 38.7 | |
6th decile | n | 4,289 | 4,601 | 4,778 | 4,506 | 4,758 | 4,648 |
mean | 5.6 | 3.8 | 3.6 | 10.6 | 9.5 | 10.2 | |
median | 10.5 | 9.0 | 8.0 | 14.7 | 12.9 | 12.2 | |
sd | 50.1 | 59.8 | 44.4 | 50.9 | 35.6 | 57.9 | |
7th decile | n | 4,624 | 5,163 | 5,049 | 4,880 | 5,081 | 4,843 |
mean | 9.3 | 8.9 | 5.4 | 13.3 | 11.7 | 11.6 | |
median | 12.8 | 11.8 | 10.3 | 14.9 | 14.7 | 13.9 | |
sd | 56.2 | 38.9 | 66.0 | 57.9 | 36.5 | 43.5 | |
8th decile | n | 5,430 | 5,822 | 5,265 | 5,201 | 5,340 | 4,985 |
mean | 11.8 | 12.1 | 10.8 | 11.8 | 12.0 | 10.6 | |
median | 14.7 | 14.3 | 13.0 | 14.8 | 14.8 | 13.9 | |
sd | 56.2 | 40.5 | 50.6 | 48.1 | 42.5 | 40.2 | |
9th decile | n | 6,431 | 6,496 | 5,594 | 5,259 | 5,631 | 5,123 |
mean | 13.2 | 13.3 | 13.0 | 12.7 | 13.5 | 10.2 | |
median | 16.3 | 15.9 | 15.5 | 15.5 | 15.9 | 14.5 | |
sd | 42.1 | 34.5 | 55.2 | 40.8 | 44.5 | 64.0 | |
91st–95th percentile | n | 3,565 | 3,338 | 2,683 | 2,761 | 2,916 | 2,653 |
mean | 17.4 | 18.9 | 17.0 | 15.5 | 16.2 | 13.6 | |
median | 19.2 | 18.8 | 17.5 | 18.2 | 17.8 | 16.9 | |
sd | 42.5 | 35.7 | 39.4 | 39.4 | 51.8 | 51.6 | |
96th–99th percentile | n | 2,996 | 2,388 | 1,910 | 2,310 | 2,258 | 1,950 |
mean | 21.7 | 23.0 | 23.3 | 17.1 | 18.4 | 15.6 | |
median | 23.4 | 22.5 | 23.2 | 20.7 | 21.5 | 22.2 | |
sd | 41.5 | 37.5 | 39.2 | 61.0 | 68.1 | 75.6 | |
100th percentile | n | 653 | 455 | 329 | 611 | 425 | 433 |
mean | 39.5 | 39.6 | 35.0 | 23.8 | 19.8 | 25.4 | |
median | 37.3 | 42.0 | 35.0 | 25.2 | 25.8 | 26.2 | |
sd | 45.4 | 41.3 | 36.2 | 70.1 | 104.2 | 120.6 | |
Total | n | 42,730 | 44,033 | 42,784 | 42,730 | 44,033 | 42,784 |
mean | 11.3 | 11.1 | 10.0 | 11.3 | 11.1 | 10.0 | |
median | 13.6 | 12.8 | 12.0 | 13.6 | 12.8 | 12.0 | |
sd | 52.1 | 44.8 | 53.7 | 52.1 | 44.8 | 53.7 |
Source: Research Data Centers of the Federal Statistical Office and the statistical offices of the Länder, EVS, 2003–2013, own calculations. Calculations based on 2013 euros.
Distribution of income conditional on wealth, 2013.
Wealth decile | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Total | ||
Income decile | 1 | 13.7 | 40.6 | 21.7 | 11.0 | 5.5 | 3.1 | 1.7 | 1.0 | 1.1 | 0.8 | 10.0 |
2 | 14.1 | 23.1 | 21.3 | 15.6 | 10.9 | 7.2 | 4.1 | 2.0 | 1.1 | 0.6 | 10.0 | |
3 | 13.7 | 14.5 | 17.4 | 16.8 | 13.7 | 9.1 | 6.9 | 4.1 | 2.6 | 1.2 | 10.0 | |
4 | 13.0 | 8.6 | 12.2 | 15.4 | 13.4 | 12.1 | 9.3 | 8.3 | 4.9 | 3.0 | 10.0 | |
5 | 12.2 | 5.4 | 9.6 | 12.5 | 13.1 | 12.8 | 11.9 | 10.5 | 7.9 | 4.1 | 10.0 | |
6 | 10.1 | 3.6 | 6.9 | 10.1 | 12.8 | 13.7 | 12.1 | 13.1 | 11.3 | 6.3 | 10.0 | |
7 | 8.2 | 2.1 | 5.4 | 8.3 | 11.5 | 12.4 | 13.3 | 15.0 | 14.2 | 9.6 | 10.0 | |
8 | 7.9 | 1.2 | 3.2 | 5.7 | 9.3 | 13.0 | 15.6 | 14.8 | 15.9 | 13.7 | 10.0 | |
9 | 4.8 | 0.6 | 1.8 | 3.2 | 6.4 | 10.5 | 15.3 | 16.6 | 19.6 | 21.2 | 10.0 | |
10 | 2.5 | 0.3 | 0.6 | 1.5 | 3.6 | 6.2 | 9.9 | 14.6 | 21.4 | 39.5 | 10.0 | |
Total | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
Source: Research Data Centers of the Federal Statistical Office and the statistical offices of the Länder, EVS, 2013, own calculations. Table entries denote column percentages.
Regression models for the saving rate.
Dependent variable: saving rate | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) |
---|---|---|---|---|---|---|---|---|---|
ln(income) | 12.852*** | ||||||||
(0.317) | |||||||||
income | 0.003*** | 0.004*** | 0.006*** | 0.007*** | 0.010*** | 0.009** | 0.008 | 0.027*** | |
(0.000) | (0.000) | (0.001) | (0.001) | (0.002) | (0.003) | (0.006) | (0.010) | ||
income2 | −0.000*** | −0.000*** | −0.000** | −0.000** | −0.000 | −0.000 | −0.000* | ||
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |||
income3 | 0.000*** | 0.000 | 0.000 | 0.000 | 0.000 | 0.000* | |||
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | (0.000) | ||||
income4 | −0.000 | −0.000 | 0.000 | 0.000 | −0.000 | ||||
(0.000) | (0.000) | (0.000) | (0.000) | (0.000) | |||||
income5 | 0.000 | −0.000 | −0.000 | 0.000 | |||||
(0.000) | (0.000) | (0.000) | (0.000) | ||||||
income6 | 0.000 | 0.000 | −0.000 | ||||||
(0.000) | (0.000) | (0.000) | |||||||
income7 | −0.000 | 0.000 | |||||||
(0.000) | (0.000) | ||||||||
income8 | −0.000 | ||||||||
(0.000) | |||||||||
constant | −94.177*** | −0.800** | −3.575*** | −6.908*** | −8.232*** | −10.587*** | −9.813*** | −9.579*** | −18.117*** |
(2.527) | (0.367) | (0.503) | (0.753) | (1.095) | (1.587) | (2.238) | (3.291) | (4.640) | |
N | 41,784 | 41,784 | 41,784 | 41,784 | 41,784 | 41,784 | 41,784 | 41,784 | 41,784 |
Adjusted R2 | 0.123 | 0.125 | 0.127 | 0.128 | 0.129 | 0.129 | 0.129 | 0.129 | 0.129 |
RMSE | 22.0 | 22.0 | 22.0 | 22.0 | 22.0 | 22.0 | 22.0 | 22.0 | 22.0 |
AIC | 377,049 | 376,945 | 376,837 | 376,768 | 376,763 | 376,755 | 376,755 | 376,755 | 376,742 |
BIC | 377,066 | 376,962 | 376,863 | 376,794 | 376,789 | 376,781 | 376,781 | 376,781 | 376,768 |
*/**/***=significant at the 10/5/1 % level.
Source: Research Data Centers of the Federal Statistical Office and the statistical offices of the Länder, EVS, 2003–2013, own calculations. Monthly income used as regressors, 2013 prices. Standard errors robust against heteroskedasticity.
© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston