Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg February 9, 2018

The Distribution of Household Savings in Germany

  • Jochen Späth ORCID logo EMAIL logo and Kai Daniel Schmid

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.

JEL Classification: D14; E21

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

A
Table 5:

Summary statistics on income and wealth groups (in euros).

Household net income per yearHousehold net wealth
By income groupsBy wealth groups
200320082013200320082013
1st decilen1,9782,3622,7233,6585,1773,794
mean10,4579,5739,600−10,097−12,061−16,138
median10,6659,7499,7320−1,116−7,025
sd2,0731,8721,76838,00540,22932,241
2nd decilen2,3152,6622,9372,3671,2133,027
mean15,91714,53914,5741,27030326
median15,94814,57214,6481,1542680
sd1,3581,2711,32698424690
3rd decilen2,8933,1343,3333,1753,1553,307
mean20,48818,94519,0656,7873,1932,330
median20,47618,96219,0646,6163,0422,103
sd1,3501,2911,2992,2421,6621,386
4th decilen3,6113,5493,7983,7003,7593,806
mean25,49623,29823,58317,39411,65310,173
median25,45323,31423,53217,09911,2959,951
sd1,5361,2551,3304,1163,3613,279
5th decilen3,9454,0634,3854,3024,3204,215
mean31,03427,96528,61937,30427,83726,200
median31,10827,94028,61236,22827,23425,521
sd1,6191,4511,5657,7116,2946,333
6th decilen4,2894,6014,7784,5064,7584,648
mean36,91633,54334,50674,39757,51858,667
median36,91533,47934,38873,68056,56657,686
sd1,7871,8101,89213,68311,11012,585
7th decilen4,6245,1635,0494,8805,0814,843
mean43,57840,46141,863132,423106,715109,787
median43,54240,35641,820131,038106,105108,891
sd2,0292,1912,36319,44917,05117,121
8th decilen5,4305,8225,2655,2015,3404,985
mean51,74849,11851,214209,502174,822178,743
median51,61348,97351,040208,686173,365177,653
sd2,8132,9103,07225,22122,90123,011
9th decilen6,4316,4965,5945,2595,6315,123
mean64,24161,83864,990314,945277,636281,536
median63,86861,31664,552311,179272,637278,312
sd4,6834,8025,09637,84839,31338,404
91st–95th percentilen3,5653,3382,6832,7612,9162,653
mean80,52078,82282,699452,438424,910428,286
median79,97678,40582,172447,968420,719422,582
sd4,7664,8304,99941,33146,48146,842
96th–99th percentilen2,9962,3881,9102,3102,2581,950
mean105,695104,250109,092705,800711,106694,387
median102,660101,501105,972673,195675,777661,476
sd12,25211,92113,015133,444153,409135,056
100th percentilen653455329611425433
mean170,347162,307166,6791,868,2031,819,9501,625,481
median161,420154,907161,9161,323,2681,457,5901,357,254
sd30,33924,27820,3372,018,6371,108,865840,959
Totaln42,73044,03342,78442,73044,03342,784
mean39,94137,66038,962147,704131,954130,558
median33,87730,56431,36452,80840,19338,753
sd27,07726,58327,892319,215266,696242,571
  1. 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.

Table 6:

Summary statistics, yearly saving amounts by income and wealth groups (in euros).

Savings
By income groupsBy wealth groups
200320082013200320082013
1st decilen1,9782,3622,7233,6585,1773,794
mean−1,006−1,247−1,2131,7801,6982,243
median0005665141,664
sd5,2105,7108,15516,4079,90913,521
2nd decilen2,3152,6622,9372,3671,2133,027
mean50−491−7411,046313398
median368116605332190
sd6,1456,4855,65212,1126,8477,417
3rd decilen2,8933,1343,3333,1753,1553,307
mean123−138−6021,126791890
median1,0056434921,090630492
sd10,9577,0169,73114,1327,5507,348
4th decilen3,6113,5493,7983,7003,7593,806
mean6624641972,0311,8731,289
median1,6371,2999961,8251,2481,008
sd11,77310,2439,99911,78311,24111,994
5th decilen3,9454,0634,3854,3024,3204,215
mean1,5675358213,2182,3862,446
median2,8301,9291,7363,0902,0582,040
sd21,12912,28318,67029,17111,69416,502
6th decilen4,2894,6014,7784,5064,7584,648
mean2,0761,2661,2484,4043,5533,953
median3,8632,9972,7204,7173,4643,300
sd18,49219,85115,15323,39414,75625,024
7th decilen4,6245,1635,0494,8805,0814,843
mean4,0473,5952,2446,1025,0915,166
median5,5714,7374,3285,3254,5924,280
sd24,53615,72228,06330,10116,34920,310
8th decilen5,4305,8225,2655,2015,3404,985
mean6,1255,9625,5425,9555,6325,254
median7,5856,9976,5405,6135,1584,704
sd29,24820,01625,55925,51420,05021,249
9th decilen6,4316,4965,5945,2595,6315,123
mean8,4518,2558,4787,0177,2475,764
median10,3639,72310,0326,5005,8745,372
sd27,16321,27336,70224,08723,42334,688
91st–95th percentilen3,5653,3382,6832,7612,9162,653
mean13,98814,92314,0319,69010,2278,951
median15,21714,81214,2288,4587,3057,300
sd34,27728,27132,99426,83727,80932,163
96th–99th percentilen2,9962,3881,9102,3102,2581,950
mean22,96424,02825,41112,63213,59911,682
median24,29723,00523,83610,76911,13411,244
sd43,88539,47343,41941,63245,48056,897
100th percentilen653455329611425433
mean67,33464,19658,34923,00017,82424,204
median57,90662,82555,34415,68413,27317,932
sd84,11970,44862,28776,05791,12981,887
Totaln42,73044,03342,78442,73044,03342,784
mean4,5004,1693,8974,5004,1693,897
median2,8542,1091,8602,8542,1091,860
sd24,62320,22924,49224,62320,22924,492
  1. 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.

Table 7:

Summary statistics, yearly saving rates by income and wealth groups (in percent).

Saving rates
By income groupsBy wealth groups
200320082013200320082013
1st decilen1,9782,3622,7233,6585,1773,794
mean−9.6−13.0−12.67.47.27.7
median0.00.00.08.58.09.9
sd91.696.1111.152.134.534.4
2nd decilen2,3152,6622,9372,3671,2133,027
mean0.3−3.4−5.15.01.72.4
median2.40.90.44.72.60.0
sd38.345.238.846.829.839.2
3rd decilen2,8933,1343,3333,1753,1553,307
mean0.6−0.7−3.24.53.64.1
median4.93.32.77.65.34.7
sd52.937.350.946.730.229.6
4th decilen3,6113,5493,7983,7003,7593,806
mean2.62.00.87.07.14.8
median6.65.74.29.58.07.2
sd46.044.242.242.732.549.3
5th decilen3,9454,0634,3854,3024,3204,215
mean5.11.92.98.97.57.4
median9.17.06.012.310.59.9
sd67.543.765.070.632.638.7
6th decilen4,2894,6014,7784,5064,7584,648
mean5.63.83.610.69.510.2
median10.59.08.014.712.912.2
sd50.159.844.450.935.657.9
7th decilen4,6245,1635,0494,8805,0814,843
mean9.38.95.413.311.711.6
median12.811.810.314.914.713.9
sd56.238.966.057.936.543.5
8th decilen5,4305,8225,2655,2015,3404,985
mean11.812.110.811.812.010.6
median14.714.313.014.814.813.9
sd56.240.550.648.142.540.2
9th decilen6,4316,4965,5945,2595,6315,123
mean13.213.313.012.713.510.2
median16.315.915.515.515.914.5
sd42.134.555.240.844.564.0
91st–95th percentilen3,5653,3382,6832,7612,9162,653
mean17.418.917.015.516.213.6
median19.218.817.518.217.816.9
sd42.535.739.439.451.851.6
96th–99th percentilen2,9962,3881,9102,3102,2581,950
mean21.723.023.317.118.415.6
median23.422.523.220.721.522.2
sd41.537.539.261.068.175.6
100th percentilen653455329611425433
mean39.539.635.023.819.825.4
median37.342.035.025.225.826.2
sd45.441.336.270.1104.2120.6
Totaln42,73044,03342,78442,73044,03342,784
mean11.311.110.011.311.110.0
median13.612.812.013.612.812.0
sd52.144.853.752.144.853.7
  1. 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.

Table 8:

Distribution of income conditional on wealth, 2013.

Wealth decile
12345678910Total
Income decile113.740.621.711.05.53.11.71.01.10.810.0
214.123.121.315.610.97.24.12.01.10.610.0
313.714.517.416.813.79.16.94.12.61.210.0
413.08.612.215.413.412.19.38.34.93.010.0
512.25.49.612.513.112.811.910.57.94.110.0
610.13.66.910.112.813.712.113.111.36.310.0
78.22.15.48.311.512.413.315.014.29.610.0
87.91.23.25.79.313.015.614.815.913.710.0
94.80.61.83.26.410.515.316.619.621.210.0
102.50.30.61.53.66.29.914.621.439.510.0
Total100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0100.0
  1. 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.

Table 9:

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)
income0.003***0.004***0.006***0.007***0.010***0.009**0.0080.027***
(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)
income30.000***0.0000.0000.0000.0000.000*
(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)
income4−0.000−0.0000.0000.000−0.000
(0.000)(0.000)(0.000)(0.000)(0.000)
income50.000−0.000−0.0000.000
(0.000)(0.000)(0.000)(0.000)
income60.0000.000−0.000
(0.000)(0.000)(0.000)
income7−0.0000.000
(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)
N41,78441,78441,78441,78441,78441,78441,78441,78441,784
Adjusted R20.1230.1250.1270.1280.1290.1290.1290.1290.129
RMSE22.022.022.022.022.022.022.022.022.0
AIC377,049376,945376,837376,768376,763376,755376,755376,755376,742
BIC377,066376,962376,863376,794376,789376,781376,781376,781376,768
  1. */**/***=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.

Received: 2017-06-23
Revised: 2017-11-06
Accepted: 2018-01-18
Published Online: 2018-02-09
Published in Print: 2018-03-26

© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston

Downloaded on 28.3.2024 from https://www.degruyter.com/document/doi/10.1515/jbnst-2017-0120/html
Scroll to top button