The Executive Turnover Risk Premium
The Journal of Finance, vol. 69, no. 4, pp.
1529-1563, 2014.
(with Alexander Wagner)
Presented at the AFA Meetings 2010.

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.

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)

Presented at AFA Meetings 2009, EFA Meeting 2011, FIRS Meeting 2014, , Herzliya Summer Finance Conference 2014, Chicago Booth, DePaul, LSE, MIT Sloan, NBER Summer Institute 2013, NYU, Ohio State, Princeton, Tinbergen Institute, Yale.
Media mentions: CNN Money (May 2, 2012), Wall Street Daily (May 2, 2012)

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.


Product Market Peers and Relative Performance Evaluation, 2020

Conditionally accepted at The Accounting Review
(with Sudarshan Jayaraman, Todd Milbourne and Hojun Seo)
Presented at 2015 Conference on Convergence of Financial and Managerial Accounting Research, AFA 2016, 2016 MIT Asia Accounting Conference, 2016 FMA conference, Washington University in St. Louis.

Abstract: Relative Performance Evaluation (RPE) theory 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 firms in the peer group. Despite the intuitive appeal of the theory, previous tests of RPE find weak and inconsistent evidence. We hypothesize that one reason for the mixed evidence is the inaccurate classification of peers. Rather than using static, pre-defined Standard Industry Classifications (SIC), we exploit recent advances in textual analysis and define peers based on firms’ product descriptions in their 10-K filings (Hoberg and Phillips, 2016). This alternative classification not only captures common shocks to firms’ product markets more effectively but also tracks the evolving nature of these markets, as 10-Ks are updated annually. Using product market peers, we find three pieces of evidence consistent with RPE in relation to CEO pay  – (i) firms on average 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. We also examine forced CEO turnover decisions and find evidence consistent with RPE theory. Overall, our results suggest that a key identification strategy to testing RPE theory lies in accurately defining the peer group.

Measuring Biases in Expectation Formation, 2019

Revise and resubmit at The Review of Economics and Statistics
(with Simas Kucinskas)
Presented at AEA 2020, Bank of Lithuania, Dutch National Bank, HEC Paris, University of Amsterdam, University of Bonn, Vrije Universiteit Amsterdam.

Abstract: We develop a framework for measuring biases in expectation formation. The basic insight is that under- and overreaction to new information is identified by the impulse response function of forecast errors. This insight leads to a simple and widely applicable measurement procedure. The procedure yields estimates of under- and overreaction to new information at different horizons. Our framework encompasses all major models of expectations, sheds light on existing approaches to measuring biases, and provides new empirical predictions. In an application to inflation expectations, we find that forecasters underreact to aggregate shocks but overreact to idiosyncratic shocks.

Additional material: SlidesReplication files. See also my co-author’s blog for a non-technical summary: link.

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, U Amsterdam, U Bonn, U 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.


  • Common Ownership, Competition, and Top Management Turnover (with Martin Schmalz)
  • Bias Contagion Among Sell-Side Analysts