Comparing Augmented Wealth in the US and Germany

Department(s)/ Research Infrastructure
German Socio- Economic Panel study
Project Status
Completed Project
Project Duration
since/from 2015 to 2016
Commissioned by
Funded by
Deutsche Forschungsgemeinschaft (DFG)
In Cooperation with
Professor Edward N. Wolff, New York University
Project Manager
Prof. Dr. Carsten Schröder, DIW Berlin
Project Team/Contacts at DIW Berlin


Influential economists argue that the recent rise in inequality in many societies is the most important problem we are facing today (OECD 2011, Ostry et al. 2014, Stiglitz 2012, Acemoglu and Robinsion 2012). This is for economic, societal, as well as political reasons. High inequality may harm the economy because credit rationing prevents the poor from investing in education and weakens innovations. High inequality may reduce social cohesion because people are less likely to trust each other and therefore reduce their community involvement. High inequality may lead to the emergence of economic elites who may use their power to (re)shape the political system and gain special benefits, creating a vicious circle.

A broad empirical literature studies inequality in the distribution of income. We propose to start a collaboration to study wealth inequalities – focusing on a comparison between Germany and the US. Estimates of wealth inequalities add important insights to those for incomes/earnings. This is because wealth reflects a household’s total opportunity to secure a standard of living, enables the inter-generational transmission of social status, provides for financial security, and contributes to political power. In sum, wealth is a powerful measure for the ability of people to act. Comparable figures on wealth and wealth inequalities in Germany and the US thus should help policy makers making informed decisions for designing policies (in the areas of taxation, social security, etc.), and should serve as a valuable ingredient for future research on the determinants of wealth accumulation or the implications of pension system reforms on household savings decisions.

Our first aim is to construct a comparable database on a broad “augmented” wealth concept which goes beyond the standard measure of net worth, as it includes an important wealth component: social security, in particular pension wealth (details below). Our second aim is a rigorous analysis of augmented wealth in the US and Germany, including a comparison of wealth levels, wealth composition, wealth inequalities, and the determinants of wealth.

Our project has three aims: Our first aim is to provide an infrastructure of comparable micro data on household wealth in Germany and the US. We make use of the Socio-economic Panel (SOEP). The SOEP is a representative panel survey of households in Germany started in 1984. Most important for our purpose, it collects wealth information in a five-year rotating extra survey module (2002, 2007, 2012). First results on a standard wealth measure suggest that mean and median net worth (excluding social security wealth) is markedly lower than in the US (see Smeeding et al., 2006).  Most likely, this discrepancy results from differences in social security wealth. As off 2013, the SOEP for the first time also gathers data on complete pension wealth (from private and statutory pension insurance), necessary for the construction of augmented net worth. Previous work of (Frick and Grabka 2013) on augmented wealth relies on statistically matched data base (SOEP households with administrative pension insurance data). Matching means that only statistical twins could be constructed. Further, the authors did not consider company pensions. For the United States, we will make use of the 2013 Survey of Consumer Finances (SCF) conducted by the Federal Reserve Board of Washington. The survey consists of a core representative sample combined with a high-income supplement. The SCF provides considerable detail on both pension plans and Social Security contributions. In particular, it gives detailed information on expected pension and Social Security benefits for both husband and wife. Moreover, for current workers, it provides information on pension coverage, including the type of plan, the expected benefit at retirement or the formula used to determine the benefit amount (for example, a fixed percentage of the average of the last five year’s earnings), the expected retirement age when the benefits are effective, the likely retirement age of the worker, and vesting requirements. Information is provided not only for the current job (or jobs) of each spouse but for up to five past jobs as well. Most importantly, for achieving our first aim is the computation of present values of pension entitlements. Here we can rely on the knowledge and experience of Edward Wolff (2014) and Carsten Schroeder (2012). The methods to construct the data should be made available to other researchers.

Our second aim is a rigorous analysis of augmented wealth in the US and Germany. Particularly, in a first step we will provide estimates on the incidence of various wealth components (by societal groups), wealth levels, and wealth composition. In a second step, we will conduct an in-depth distributional analysis by providing a set of inequality indices (Gini, entropy measures, etc.), a factor decomposition (Shorrocks, 1982), and tests of statistical significance (Karoly and Schröder, 2014, and Schröder, 2014).

In a third step we decompose our estimates by age groups to study to which extent cross country differences in the distribution of household wealth represent pure cross-country differences in the age composition and the household structure of their populations (see Cowell et al., 2012). Further, we seek to control for the relevance of different mortality rates when constructing a present value of pension wealth by means of a counterfactual approach, as longevity differences across the US and Germany are a potential cause for differences in pension wealth levels.

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SOEPpapers (2016)

The Joint Distribution of Net Worth and Pension Wealth in Germany

Timm Bönke, Markus M. Grabka, Carsten Schröder, Edward N. Wolff, Lennard Zyska