Knowledge that Transforms

I study how promotion incentives within the public sector affect financial regulation. I assemble individual data for all SEC enforcement attorneys between 2002 and 2017, including enforcement cases, salaries, and ranks. Consistent with tournament model, attorneys with stronger promotion incentives are involved in more enforcement, especially against severe misconduct, and in tougher settlement terms. For identification, I rely on cross-sectional tests within offices and ranks and on exogenous variation in salaries resulting from a conversion to a new pay system. The findings highlight a novel link between incentives and regulation and show that the regulator’s organizational design affects securities markets.

Exposures of expected future nominal depreciation rates to the current interest rate differential violate the UIP hypothesis in a pattern that is a nonmonotonic function of horizon. Forward expected nominal depreciation rates are monotonic. We explain the two patterns by simultaneously incorporating the weak form of PPP into a joint model of the stochastic discount factor, the nominal exchange rate, and domestic and foreign yield curves. Departures from PPP generate the first pattern. The risk premiums for these departures generate the second pattern. Thus, the variance of the stochastic discount factor is related to the real exchange rate.

Cross-border merger activity is growing in importance. We map the global trade network each year from 1989 to 2016 and compare it to cross-border and domestic merger activity. Trade-weighted merger activity in trading partner countries has statistically and economically significant explanatory power for the likelihood that a given country will be in a merger wave state, at both the cross-border and domestic levels, even controlling for its own lagged merger activity. The role of trade as a channel for transmitting merger waves is confirmed using import tariff cuts and trade sanctions as instruments to mitigate endogeneity. Overall, the full trade network helps our understanding of merger waves and how merger activity propagate across borders.

We propose a new methodology for forming arbitrage portfolios that utilizes the information contained in firm characteristics for both abnormal returns and factor loadings. The methodology gives maximal weight to risk-based interpretations of characteristics’ predictive power before any attribution is made to abnormal returns. We apply the methodology to simulated economies and to a large panel of U.S. stock returns. The methodology works well in our simulation and when applied to stocks. Empirically, we find the arbitrage portfolio has (statistically and economically) significant alphas relative to several popular asset pricing models and annualized Sharpe ratios ranging from 1.31 to 1.66.

There is a discrepancy between CAPM-implied and realized returns. Using the CAPM in capital budgeting—as recommended in textbooks—should thus have real effects. For instance, low beta projects should be valued more by CAPM users than by the market. We test this hypothesis using M&A data and show that bids for low-beta private targets entail lower bidder returns. We provide further support by testing several ancillary predictions. Our analyses suggest that using the CAPM when valuing targets leads to valuation errors (relative to the market’s view) corresponding on average to 12% to 33% of the deal values.

We develop a new approach to modeling and predicting stock returns in the presence of breaks that simultaneously affect a large cross-section of stocks. Exploiting information in the cross-section enables us to detect breaks in return prediction models with little delay and to generate out-of-sample return forecasts that are significantly more accurate than those from existing approaches. To identify the economic sources of breaks, we explore the asset pricing restrictions implied by a present value model which links breaks in return predictability to breaks in the cash flow growth and discount rate processes.

This paper documents a link between bank concentration and markups in nonfinancial sectors. We exploit concentration-increasing bank mergers and variation in banks’ market shares across industries and show that higher credit concentration is associated with higher markups and that high-market-share lenders charge lower loan rates. We argue that this is due to the greater incidence of competing firms sharing common lenders that induce less aggressive product market behavior among their borrowers, thereby internalizing potential adverse effects of higher rates. Consistent with our conjecture, the effect is stronger in industries with competition in strategic substitutes where negative product market externalities are greatest.

This paper shows that collateralized short-term debt, although privately optimal for reducing borrowers’ risk-taking incentives, can induce fragility (multiple equilibria). Despite sequential-service property being absent in collateralized debt, such as repurchase agreements, a systemic run can arise, featuring large increases in default risks, fire-sale discounts of collateral, cost of credit, and amount of credit rationing. Asset price guarantees, leverage caps, and central clearing promote stability and welfare. Using global games techniques, I show that a systemic run is more likely in bad times, and a large enough asset price guarantee reduces run risks.

This paper isolates the causal impact of neighborhood environment on the credit outcomes of low-income borrowers by analyzing the participants of the Moving to Opportunity (MTO) experiment. MTO was a unique, large-scale experiment that offered families vouchers to move to better neighborhoods via randomized lottery. We find higher credit scores and use among those required to move to the lowest poverty areas as young children. For those who moved as adults, we find that better neighborhoods lead to a reduction of overdue debts and delinquencies, but only among those given unrestricted neighborhood choice.

We use brokerage account records to study trading during the Chinese put warrants bubble and find evidence consistent with extrapolative theories of speculative asset price bubbles. We identify the event that started the bubble and show that investors engaged in a form of feedback trading based on their own past returns. The interaction of feedback trading with the precipitating event caused additional buying and price increases in a feedback loop, and estimates of the trading volume due to this mechanism explain prices and returns during the bubble.