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Abstract
This paper estimates rates of return across the gross wealth distribution in eight European countries. Like differential saving rates, differential rates of return matter for post Keynesian theory, because they impact the income and wealth distribution and add an explosive element to growth models. We show that differential rates of return matter empirically by merging data on household balance sheets with long-run returns for individual asset categories. We find that (a) the composition of wealth differentiates three socioeconomic groups: 30% are asset-poor, 65% are middle-class home owners, and the top 5% are business-owning capitalists; (b) rates of return rise across all groups; and (c) rates of return broadly follow a log-shaped function across the distribution, where inequality in the lower half of the distribution is higher than in the upper half. If socioeconomic groups are collapsed into the bottom 95% workers and top 5% capitalists, then rates of return are 5.6% for the former and 7.2% for the latter.
Disclosure statement
There are no conflicts of interest to report.
Notes
1 Pasinetti states that “in a long-run equilibrium model, the obvious hypothesis is that of a rate of interest equal to the rate of profits” (Pasinetti Citation1962, 271–272). Samuelson and Modigliani (Citation1966) point out that although it is necessary to make this assumption explicit in Pasinetti's framework, it is not relevant in Kaldor's framework, given that the latter distinguishes between income groups.
2 For a comprehensive overview of this theoretical literature, see Baranzini and Mirante (Citation2013).
3 As opposed to the “dual equilibrium” by Samuelson and Modigliani (Citation1966), in which capitalists cease to exist and are replaced by workers, who own all wealth.
4 Rubin’s rule states that in multiply imputed data sets, each step of analysis needs to be computed for each data set, and pooled only at the end of the analysis.
5 These are Belgium, Finland, France, Germany, Italy, the Netherlands, Portugal, and Spain.
6 Data for rates of return are only available as long-run averages in JKKST.
7 Differences in returns for each asset class by socioeconomic is group is unfortunately not available in our data, even though it is likely that this is another channel for differential returns. See the discussion in the literature review.
8 More precisely, Bach, Calvet, and Sodini (CitationForthcoming) assume no excess return over the risk-free interest rate for deposit-like wealth. The risk-free interest rate on 10-year government bonds has hovered near zero in several European countries.
9 Negative values are excluded. For detailed wealth levels by socioeconomic group, see the Appendix.
10 For the distribution of absolute values of household asset categories across unconditional gross wealth vingtiles, see Table 6A in the Appendix.
11 In the distribution of net wealth, the bottom vingtiles are marked by households with a long balance sheet who typically own a main residence but are also indebted. For details, see Figure 3A in the Appendix.
12 We also checked for differential returns across age groups and education levels. Differences in returns are much smaller than by wealth, and are inverted u-shaped for age and some countries for education, and rising with the education level for other countries. For details, see Tables 8A and 9A in the Appendix.
13 For cut-off vingtiles, see Table 7A in the Appendix.
14 The uptick in the 10th decile in the Netherlands is due to one household with very high business assets. However, we choose not to deleted single observations from our data.
15 Ideally, we would like to use observed rates of return, which our data quality unfortunately does not permit, as discussed in the data section.
Additional information
Notes on contributors
Stefan Ederer
Stefan Ederer is at Austrian Institute of Economic Research (WIFO) & Department of Socioeconomics, Vienna University of Economics and Business (WU), Vienna, Austria.
Maximilian Mayerhofer
Maximilian Mayerhofer is at Department of Economic Affairs, Labour and Statistics at the Vienna City Administration.
Miriam Rehm
Miriam Rehm is at Institute for Socio-Economics, University of Duisburg-Essen, Duisburg, Germany and Department of Socioeconomics, Vienna University of Economics and Business (WU), Vienna, Austria.