第104回研究会

開催日：

2025年11月5日(水) 16:00-17:00

会場：

丸の内永楽ビルディング18階 東京都立大学 丸の内サテライトキャンパス
(Zoomでも同時配信します)

報告者：

Lei Gao 氏（George Mason University）

タイトル：

Political alignment and voluntary forward-looking disclosure: Evidence from a quasi-natural experiment of presidential turnovers

概要Overview

We investigate the impact of political alignment on management earnings forecasts (MEFs) using presidential turnover as a quasi-natural experiment that imposes exogenous variation in executives’ partisan alignment. Firms with partisan-aligned executives issue significantly more optimistic forecasts following presidential transitions, with effects particularly pronounced among firms led by overconfident CEOs, those operating in politically uncertain environments, and firms headquartered in states where the governor shares the president’s party. Importantly, we distinguish between CEO and CFO influences, demonstrating that both executive roles independently contribute to disclosure optimism. Using difference-in-differences estimation, propensity score matching, and multiple robustness checks—including alternative alignment
measures and forecast-level regressions—we ensure credible inference. Our findings highlight the importance of political ideology in shaping voluntary disclosure practices, with implications for investors, regulators, and the design of corporate communication strategies.

講師ご略歴Profile for speakers

Dr. Gao is an associate professor of finance at George Mason University, where he teaches courses on corporate finance, investments, and empirical methods in finance. Dr. Gao has taught at Iowa State University, University of Memphis, University of Georgia, and Michigan State University. Dr. Gao is an active member of the American Finance Association and Financial Management Association. His research interests include market structure, investments, lending, corporate finance, and FinTech. His research has been published in top journals such as the Proceedings of the National Academy of Sciences of USA (PNAS), Journal of Financial Economics (JFE), Journal of Financial and Quantitative Analysis(JFQA), and Research Policy(RP) among others. Dr. Gao’s research has been featured in national news media, including ABC, Bloomberg, CNN, Financial Times, Fortune, Harvard Business Review, NBC, Washington Post, and academic press, including ASSA, etc. His publication at PNAS about COVID-19 is one of the outputs of his COVID-19 project, which the CDC has adapted to forecast the mortality of COVID-19 in the U.S. and fight the pandemic. His publication at PNAS about Fair Lending is ranked by the Financial Times as #15 in its “Top 100 Business School Research with Social Impact” globally. Dr. Gao has given a speech at the Department of Housing and Urban Development (HUD) about fair lending. He has also been invited to be an expert witness before the U.S. Congress and his research has been the base for the testimony. His publication at JFE about “Market Intraday Momentum” is one of the most downloaded papers at SSRN in concurrent research. His research about short-selling regulation at JCF has been featured in the Cato Institute Research Brief. Dr. Gao has been a Financial Economist at the Securities and Exchange Commission (SEC), where he provides economics analysis and memos to support the Commission’s enforcement and regulation, Protecting investors; maintaining fair, orderly, and efficient markets; facilitating capital formation. Dr. Gao earned a Ph.D. in Finance from the University of Georgia, an M.S. in Industrial Math from Michigan State University, and a B.S. in Computer Science from Peking University.

Dr. Gao has served as a reviewer for the NSF CAREER Award and top academic journals, including American Economic Review: Insights, Journal of Financial and Quantitative Analysis, Management Science, Review of Finance, The Accounting Review, Journal of Corporate Finance, Journal of Banking and Finance, and Journal of Business Ethics, etc. Dr. Gao has delivered many presentations and talks at academic conferences, University seminars, Governments, and research institutions.

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