Measuring Under- and Overreaction in Expectation Formation
The Review of Economics and Statistics, forthcoming.
(with Simas Kucinskas)
Abstract: We develop a framework for measuring under- and overreaction in expectation formation. The basic insight is that under- and overreaction to new information is identified (up to sign) by the impulse response function of forecast errors. This insight leads to a widely applicable measurement procedure. The procedure yields estimates of under- and overreaction to different shocks at various horizons. In an application to inflation expectations, we find that forecasters underreact to aggregate shocks but overreact to idiosyncratic shocks. Finally, we illustrate how our approach can be used to (i) calibrate theoretical models; and (ii) shed light on existing empirical puzzles.
Additional material: Replication files

Enforceability of Noncompetition Agreements and Forced CEO Turnover
The Journal of Law and Economics, vol. 65, no. 1, pp. 177-209, February 2022.
(with Yupeng Lin and Hojun Seo)
Abstract: We examine whether corporate boards factor the potential cost of competitive harm caused by a departing CEO into the forced CEO turnover decision. Using staggered changes in the state-level enforceability of Covenants Not to Compete (CNC) for identification, we find that enhanced CNC enforceability increases both the likelihood of forced CEO turnover and the sensitivity of forced CEO turnover to firm performance. We present additional cross-sectional evidence that shows such effects are more pronounced when firms face more severe product market threats or operate in industries with greater potential threats of predatory hiring. Investors react to turnover announcements more positively when CNC enforceability increases, indicating that enhanced CNC enforceability increases efficiency in CEO replacement decisions.

Product Market Peers and Relative Performance Evaluation
The Accounting Review, vol. 96, no. 4, pp. 341-366, 2021.
(with Sudarshan Jarayaman, Todd Milbourn and Hojun Seo)
Abstract: We investigate the role of Relative Performance Evaluation (RPE) theory in CEO pay and turnover using a product similarity-based definition of peers (Hoberg and Phillips 2016). RPE predicts that firms filter out common shocks (i.e., those affecting the firm and its peers) while evaluating CEO performance and that the extent of filtering increases with the number of peers. Despite the intuitive appeal of the theory, previous tests of RPE find weak and inconsistent evidence, which we argue is due to the imprecise categorization of peers. Using product market peers, we find three pieces of evidence consistent with RPE in relation to CEO pay and forced turnover: (i) on average, firms partially filter out common shocks to stock returns, (ii) the extent of filtering increases with the number of peers, and (iii) firms completely filter out common shocks in the presence of a large number of peers.

Winning by Losing: Evidence on the Long-Run Effects of Mergers
The Review of Financial Studies, vol. 31, no. 8, pp. 3212-3264, 2018.
(with Ulrike Malmendier and Enrico Moretti)
Abstract: We propose a novel approach to measuring long-run returns to mergers. In a new data set of close bidding contests we use losers‘ post-merger performance to construct the counterfactual performance of winners had they not won the contest. Stock returns of winners and losers closely track each other over the 36 months before the merger, and bidders are also very similar in terms of Tobin’s Q, profitability and other accounting measures. Over the three years after the merger, however, losers outperform winners by 24 percent (14 percent internationally). Commonly used methodologies such as announcement returns fail to identify acquirors‘ underperformance.

The Executive Turnover Risk Premium
The Journal of Finance, vol. 69, no. 4, pp. 1529-1563, 2014.
(with Alexander Wagner)
Abstract: We establish that CEOs of companies experiencing volatile industry conditions are more likely to be dismissed. At the same time, industry risk is, accounting for various other factors, unlikely to be associated with CEO compensation other than through dismissal risk. Using this identification strategy, we document that CEO turnover risk is significantly positively associated with compensation. This finding is important because job-risk compensating wage differentials arise naturally in competitive labor markets. By contrast, the evidence rejects an entrenchment model according to which powerful CEOs have lower job risk and at the same time secure higher compensation.


Optimal Peers, 2024
Presented at the Universities of Amsterdam, Paris Dauphine.

Abstract: This paper provides a theoretical foundation for constructing optimal benchmarks via machine learning (ML). For a broad class of models, the optimal benchmark is given by an appropriately weighted portfolio of peers. While Ordinary Least Squares (OLS) provides the theoretically optimal weights in the population, ML methods, notably the lasso, can provide a robust, implementable solution. In an application to a large sample of U.S. public firms, ML-based benchmarks strongly outperform traditional industry benchmarks in out-of-sample explanatory power. This suggests that ML-based benchmarks can substantially improve outcomes in a wide range of applications such as incentive contracts or relative performance evaluation.

Bias Propagation in Economically Linked Firms, 2019
(with Torsten Jochem)
Presented at Miami Behavioral Finance Conference 2017, AFA 2018, EFA 2016, Research in Behavioral Finance Conference 2016, Columbia University,  Dutch National Bank, Norwegian School of Economics, Universities of Amsterdam, Bonn, Michigan

Abstract: We document that managerial biases spread across firms along supply chains. Supporting a causal interpretation, we show that beliefs trickle up the supply chain, not down, and that biases in supplier forecasts are only affected by customer forecasts issued before, not after, the supplier’s forecast. We further find that bias propagation increases when suppliers have less confidence in their own views and when the perceived precision and importance of customer forecasts increase. Biases cause changes in the corporate policies of suppliers, suggesting that contagious beliefs in production networks contribute to fluctuations of business and financing cycles.

Risk Premia in Executive Compensation: A Life-Cycle Perspective, 2010

Presented at the Mitsui Finance Symposium, 2010, UC Berkeley Macro Lunch, UC Berkeley
Corporate Finance Lunch

Abstract: How much of the rise in CEO pay can be explained by the increased risk that CEOs are exposed to? This paper employs a life-cycle model of consumption and saving to answer this question, and, more broadly, to study the relationship between the risk and level of CEO compensation. The model incorporates the main types of risk that executives of public corporations face: option- and stock-based pay, pay-performance sensitivity, dismissal risk, and stock return volatility. I use the model to compute risk premia in pay levels, and analyze how well they explain the observed variation in CEO pay. A calibration to a large panel of CEOs shows that, for realistic degrees of risk aversion, risk premia explain about 20 percent of the variation in CEO pay, both in the cross-section and the time-series. The model captures the higher moments of the cross-sectional pay distribution particularly well. The structural framework provided in this paper is robust to some sources of endogeneity typically encountered in reduced-form empirical research, and allows for the welfare analysis of policy interventions such pay limits for executives.