Person: Wang, Charles
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
First Name
Name
Search Results
Publication Core Earnings: New Data and Evidence
(Elsevier BV, 2021-12) Rouen, Ethan; So, Eric C.; Wang, CharlesUsing a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the 10-K. Excluding them from GAAP earnings yields a core earnings measure that distinguishes between the recurring and non-recurring components of net income and forecasts future performance. Analysts and market participants are slow to impound these earnings components' implications, particularly the amounts disclosed in footnotes. Trading strategies that exploit non-core earnings produce abnormal returns of 8% per year.
Publication Can Staggered Boards Improve Value? Causal Evidence from Massachusetts
(Wiley, 2021-09-14) Daines, Robert; Li, Shelley Xin; Wang, CharlesWe study the effect of staggered boards (SBs) using a quasi-experiment: a 1990 law that imposed an SB on all Massachusetts-incorporated firms. The law led to an increase in Tobin's Q, investment in CAPEX and R&D, patents, higher-quality patented innovations, and resulted in higher profitability. These effects are concentrated at innovating firms, especially those facing greater Wall Street scrutiny. An increase in institutional and dedicated investors also accompanied the imposition of SBs, facilitating a longer-term orientation. The evidence suggests that early-life-cycle firms facing high information asymmetries benefit from SBs by allowing managers to focus on long-term investments and innovations.
Publication How Much Should We Trust Staggered Difference-in-Differences Estimates?
(Elsevier BV, 2022-05) Baker, Andrew C.; Larcker, David F.; Wang, CharlesWe explain when and how staggered difference-in-differences regression estimators, commonly applied to assess the impact of policy changes, are biased. These biases are likely to be relevant for a large portion of research settings in finance, accounting, and law that rely on staggered treatment timing, and can result in Type-I and Type-II errors. We summarize three alternative estimators developed in the econometrics and applied literature for addressing these biases, including their differences and tradeoffs. We apply these estimators to re-examine prior published results and show, in many cases, the alternative causal estimates or inferences differ substantially from prior papers.
Publication The Sustainable Corporate Governance Initiative in Europe
(2021) Roe, Mark; Spamann, Holger; Fried, Jesse; Wang, CharlesIn July 2020, the European Commission published the “Study on directors’ duties and sustainable corporate governance” by EY. The Report purports to find evidence of debilitating short-termism in EU corporate governance and recommends many changes to support sustainable corporate governance. In this paper, we point out deep flaws in the Report’s evidence and analysis. We recently submitted the content of this paper in response to the European Commission’s call for feedback.
Publication Expected Stock Returns Worldwide: A Log-Linear Present-Value Approach
(American Accounting Association, 2021-04-08) Chattopadhyay, Akash; Lyle, Matthew R.; Wang, CharlesThis study provides the first large-scale study of the performance of expected-return proxies (ERPs) internationally. Analyst-forecast-based ICCs are sparsely populated and not robustly associated with future returns. Earnings-model-forecast-based ICCs are well-populated, but are unreliable outside the U.S. We adapt and extend the log-linear and present-value (LPV) framework—combining an accounting valuation anchor, its expected growth, and market prices—for estimating ERPs internationally, and implement a correction for the use of stale accounting data. An LPV ERP anchored on the book value of equity is positively associated with future returns in 26 of 29 equity markets, and largely subsumes the predictive ability of a broad set of firm characteristics previously shown to be associated with expected returns.