I estimate the welfare benefits of eliminating idiosyncratic consumption shocks in the United States related (unrelated) to the business cycle as 36%–39% (lower than 1%) of household utility. Estimates of the former exceed earlier ones because I distinguish between idiosyncratic shocks related/unrelated to the business cycle, estimate the negative skewness of shocks, target moments of idiosyncratic shocks from household-level CEX data, and target market moments. Benefits of eliminating aggregate shocks are lower than 1% of utility. Policy should facilitate the insurance of idiosyncratic shocks related to the business cycle, such as job layoffs, with proof that individuals diligently seek suitable employment during periods of unemployment.

Asset pricing models predict a strong connection between the real risk-free interest rate and the macroeconomy, but prior research finds little empirical support for the connection when examining expected growth. This paper documents a robust relation between the interest rate and macroeconomic uncertainty (i.e., conditional variance). Consistent with precautionary savings, high uncertainty is associated with a low interest rate using numerous data sources, time periods, and measures. A relation between habit and the interest rate disappears after including uncertainty, and the relation is stronger using long-run uncertainty. The results imply that analyses of the interest rate without uncertainty are seriously incomplete.

We find that the degree of expected idiosyncratic skewness in seasoned equity issuers’ stock returns is an important determinant of flotation costs and subsequent abnormal stock performance. High skewness issuers incur significantly greater offer price discounts, particularly when institutional share allocation is largest, pay higher gross underwriting spreads, and exhibit poorer stock performance in the three years after issuance, all compared to low skewness issuers. These results suggest that skewness-induced overpricing increases the flotation costs of seasoned equity offers and leads to poor subsequent stock performance.

Contrary to the predictions of traditional life-cycle models, household consumption is excessively sensitive to current income. Similarly, weak evidence of income hedging runs against standard portfolio theory. We link these two puzzles by modifying the theoretical framework of Viceira (2001) to study how consumption-income sensitivities generated by income in the utility function affect households' portfolio choices. Empirically, we find that consumption-income sensitivities affect asset allocation through the income hedging channel. In particular, we show that the interaction between consumption-income sensitivity and the correlation of income growth to stock market returns is an important explanatory variable for households' stock market holdings. Received October 20, 2016; editorial decision April 25, 2018 by Editor Wayne Ferson.

We use the U.S. Department of Housing and Urban Development’s Housing Choice Voucher program as a setting to evaluate the interaction of homeownership and race on the wealth accumulation of low-income households. Using a within-treatment difference-in-differences framework, we establish that low-income households that receive assistance in owning a home experience increased wealth accumulation relative to their tenure as renters. These wealth gains are not present among low-income minority households. Our findings provide evidence that homeownership is a driver of wealth formation for low-income households and that homeownership does not inherently reduce racial disparities in wealth.

We use bank-firm matched data to study how the capital buffers that large U.S. banks must satisfy to “pass” the Federal Reserve's stress tests impact banks’ lending and firms’ loan volumes, overall debt, investment, and employment. We find that larger stress-test capital buffers lead to reductions in banks’ lending, modest increases in loan rates and spreads, and reductions in new loan originations. However, we do not find an impact of higher capital buffers on firms’ overall debt, investment, and employment, suggesting that firms find other credit sources to substitute for the reduction in loans from banks that participate in the stress tests.

We contribute to identifying proxies for the information set of investors in financial markets. We show that the marketwide price-dividend ratio highly correlates with inflation and labor market variables that also forecast consumption, dividend, and GDP growth, but not with aggregate consumption or GDP growth. Our model with learning from inflation and wage earnings rationalizes the moments of consumption and dividend growth, market return, the price-dividend ratio, real and nominal term structures, the low predictive power of the price-dividend ratio for consumption and dividends, and the dynamics of the price-dividend ratio, unlike a nested model with learning from consumption alone.

We present a novel methodology for estimating/testing the Bansal and Yaron (2004) and related long-run risks (LRR) models based on the observation that the latent state variables are known functions of observables. The large standard error of the estimated elasticity of intertemporal substitution explains the controversy on its magnitude. The model requires higher persistence of consumption and dividend growth to explain the cross-section of returns than that observed in the data. The model matches the unconditional moments of consumption and dividend growth, but implies a higher risk-free rate and lower volatility of the price/dividend ratio, risk-free rate, and market return than those observed in the data. Contrary to the model implications, the conditional variance of the LRR variable fails to capture the large time variation in the equity premium.

An extensive literature studies interactions of stock market anomalies using double-sorted portfolios. But given hundreds of known candidate anomalies, examining selected interactions is subject to a data mining critique. In this paper, we conduct a comprehensive analysis of all possible double-sorted portfolios constructed from 102 underlying anomalies. We find hundreds of statistically significant anomaly interactions, even after accounting for multiple hypothesis testing. An out-of-sample trading strategy that invests in the top backward-looking double-sort strategy generates equal-weighted (value-weighted) monthly average returns of 4% (2.7%) at an annualized Sharpe ratio of 2 (1.38), on par with state-of-the-art anomaly-based machine learning strategies.

We examine real outcomes for biotech startups going public around the Jumpstart Our Business Startups (JOBS) Act. Reduced compliance costs associate with greater innovation capital formation as biotech IPO volume and proceeds increase after the JOBS Act. Biotechs, which conduct over 30% of IPOs since 2012, go public with products earlier in the FDA approval process and more frequently target rare diseases and cancer. Consistent with our survey evidence that managers use compliance savings to invest in R&D, we link the JOBS Act to post-IPO increases in project-level development, such as new patents, clinical trials, and staffing of laboratories. Post-JOBS Act product candidates are more likely to reach key milestones in the FDA approval process and these startups fail at lower rates. Benefits accrue to shareholders without sacrificing financial reporting quality. Our results demonstrate how tailoring regulations for startups can provide economic and societal benefits.