Wealth Inequality – Rich Pickings? Risk, Return, And Skill In The Portfolios Of The WealthyVW Staff
Wealth Inequality – Rich Pickings? Risk, Return, And Skill In The Portfolios Of The Wealthy
Swedish House of Finance
HEC Paris – Finance Department
Stockholm School of Economics – Department of Finance
December 15, 2015
This paper empirically investigates the portfolios of wealthy households and their potential Implications for the dynamics of inequality. Using an administrative panel of all Swedish residents, we document that returns on financial wealth are on average 4% per year higher for households in the top 1% compared to the median household. The financial capital of the wealthy is much more exposed to systematic risk. The top 1% allocate a high proportion of financial capital to risky assets and select risky assets with high exposures to systematic risk. Moreover, the wealthy select portfolios of risky assets with average levels of idiosyncratic risk that do not seem to yield abnormal risk-adjusted returns. Overall, the evidence suggests that the high average financial returns earned by the wealthy are primarily compensations for the high levels of systematic risk that they take. The implications for inequality dynamics and public policy are discussed.
Rich Pickings? Risk, Return, And Skill In The Portfolios Of The Wealthy – Introduction
Economic theory suggests that capital income should hold a fundamental role in the level and dynamics of wealth inequality. Returns on household savings accumulate multiplicatively over time and therefore have the potential to generate levels of wealth concentration that far exceed the levels of income concentration, especially at the top (Benhabib Bisin and Zhu 2011, Cagetti and de Nardi 2008). Capital income also has the potential to reduce mobility across wealth groups: high average returns on investments allow for the perpetuation of a dynasty’s standing without having to rely on low consumption or costly-to- generate labor income (Piketty 2011). Furthermore, the impact of capital income on the wealth distribution might be considerably magnified if the wealthy select portfolios with high average returns, as Piketty (2014) suggests.
Despite the theoretical importance of capital income, empirical evidence is scant due to the lack of available data on the wealthiest households. This paper uses an administrative data set of the entire Swedish population to shed light on the dynamics of investment and wealth. We document substantial differences in the risk and return characteristics of financial investments across socioeconomic groups. Consistent with Piketty (2014), we report that wealthier households earn higher average returns than other households. We also show that these higher average returns compensate richer households for the higher systematic risk that they take. Furthermore, we find no evidence that abnormal risk-adjusted returns provide a substantial contribution to returns on financial portfolios of the wealthy.
In order to analyze empirically the determinants of wealth inequality, one needs to use a data set that meets several key requirements. First, households at the very top of the wealth distribution should be sampled exhaustively and given strong incentives to truthfully report their holdings. For instance, the U.S. Survey of Consumer Finances (SCF), which oversamples the wealthy, contains only about 700 households in the top 1% of the wealth distribution and the response rate in this percentile is only 12% (Kennickell 2009). These limitations of the SCF make it very difficult to provide an accurate description of investment strategies at the top, even though the top 1% own more than a third of total U.S. market wealth. Second, the financial holdings of households must be measured exhaustively and accurately. The few existing studies on differences in rates of return across the wealth distribution are restricted to U.S. foundations and university endowments, for
which data on asset holdings and capital income flows are available only for broad asset classes (Piketty 2014, Saez and Zucman 2015). Because traditional data sets preclude the measurement of systematic risk and the estimation of expected returns, earlier studies only estimate differences in realized returns across wealth groups. The problem is that sample means of realized returns are notoriously noisy, which makes it hard to assess the statistical significance of differences in returns across wealth groups.
In this paper, we use a data set based on the individual wealth tax records of the entire Swedish population between 1999 and 2007. The Swedish Income and Wealth Registry is recognized as the most accurate source for the measurement of top wealth holdings in Sweden (Roine and Waldenstrom 2009). The sampling and response rates are very close to 100%. Since Sweden has a population of 9 million, we observe each year about 40,000 households from the top 1% of the wealth distribution. The Swedish Income and Wealth Registry also turns out to be one of the richest sources for the analysis of household investment decisions (Betermier Calvet and Sodini 2015; Calvet Campbell and Sodini 2007, 2009a, 2009b). The data include individual holdings of every asset on December 31st of each year. We are able to match this information with the corresponding price data at security or mutual fund-level. We can therefore use standard asset pricing methods to evaluate portfolio performance, expected returns, and exposure to systematic and idiosyncratic risk at the level of each household.
The impact of wealth on investment risk and return has long been documented in household finance. Richer individuals are empirically more risk-tolerant and therefore more willing to take on additional risk in exchange for higher expected return.2 Until now, however, the literature has focused on wealth effects for the average investor, with little interest in how extreme wealth affects investment decisions. The contribution of the present paper is to analyze fine-grained differences in investment decisions at the top, i.e. between centiles and even thousandths of the wealth distribution. This approach to household finance is motivated by recent evidence that in the United States, more than 90% of equity wealth is held by the top wealth decile, 70% by the top percentile, and 45% by the top permille (Saez and Zucman 2015). In other words, whatever we will learn about the top of the distribution may concern few people directly but will have a significant impact on the aggregate demand for risky assets. Another limitation of the existing literature is that we know little about the impact of wealth on the allocation of risky assets. We are able to precisely investigate the risk exposures sought by investors with varying degrees of wealth. We can also test whether very rich households are able to reach higher-risk adjusted returns.
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