Research

[Abstract to be added]

This study examines how tenant concentration risk influences CEO compensation design. We find that boards of listed equity Real Estate Investment Trusts (REITs) with concentrated property portfolios design CEO pay packages to encourage risk-taking. These incentives help mitigate moral hazard concerns between risk-averse CEOs and diversified shareholders. The positive relationship between tenant concentration and risk-taking incentives awarded to CEOs holds after accounting for potential reverse causality. The effect is amplified when the concentrated tenant base comprises smaller and less profitable firms. The findings are attenuated when REITs have poor growth prospects. These incentives are followed by greater firm risk-taking: CEOs with higher Vega subsequently exhibit higher systematic risk and leverage and steer their portfolios toward greater concentration. Our findings suggest that REIT boards account for moral hazard and risk alignment in compensation design, moving beyond generic market-based risks to firm- and tenant-specific considerations.

We investigate the free dividends fallacy in equity Real Estate Investment Trusts (REITs). The mandatory REIT payout requirement renders the propensity to pay dividends exogenous to firm quality, isolating behavioral preferences from rational quality signaling. Using a comprehensive panel of REIT dividend events from 1980 to 2023, we find that REIT returns are elevated in predicted dividend months, consistent with price pressure from dividend-seeking investors. Dividend-window returns are positively related to dividend yield, negatively related to interest rates, and negatively related to past market performance. These price patterns subsequently reverse, and insiders trade strategically to exploit the predictable mispricing. These results hold among REITs that would be least likely to pay dividends absent regulatory requirements, consistent with the presence of a free dividends fallacy.

We introduce the Commercial Real Estate AI Text-Evaluation (CREATE) score, a sector-level trading signal extracted from Wall Street Journal articles using large language models (LLMs). Unlike traditional natural language processing (NLP) methods based on dictionaries or supervised classifiers, CREATE leverages the contextual reasoning of LLMs to identify relevant information from unstructured text. We apply a filtering technique to mitigate forward-looking bias that afflicts LLMs (Engelberg et al., 2025). A sector-rotation strategy that goes long (short) REIT sectors with high (low) CREATE scores generates an annualized alpha of 6 percent and performs especially well during recessions. Comparing three models, we find that models with more advanced contextual reasoning yield much stronger predictive signals. The results highlight the value of LLM-based text analysis for real estate investment and asset pricing.

[Abstract to be added]

Given the implicit management responsibilities inherent in the duties of loyalty, care, and good faith charged to directors, we use the leadership literature to develop a new measure of director quality. With our integrated leadership model of director quality, we explore the relation between board quality and a firm's success with government subsidies. We find that firms with higher-quality boards secure more subsidies, receive subsidies more consistently, and more efficiently use subsidies to enhance financial performance. We confirm the causal relation between board quality and subsidies using the launch of two federal subsidy programs as exogenous shocks.

We examine how retail and institutional real estate investors benchmark fund performance across a comprehensive set of performance metrics. Our analysis focuses on a subset of real estate funds for which fund flows, investor type (retail vs. institutional), and risk-adjusted performance are observable. We find that benchmarking practices differ systematically by investor type. Retail investors respond primarily to raw, unadjusted returns, whereas institutional investors are most sensitive to risk-adjusted performance, particularly CAPM alphas estimated using a real estate index as the market benchmark. Although multifactor models most accurately explain historical fund performance, they exert limited influence on the investment decisions or benchmarking practices of either investor group. Ultimately, what drives performance may not be what drives capital.

Based on the leadership responsibilities embedded in the legal duties of all directors, we construct a new model of director quality. Averaging across the quality of individual directors, we estimate the quality of the board itself and explore how it affects a firm's accounting practices. We find that higher-quality boards manage their earnings less, restate their financials less frequently, and hire higher-quality auditors. Additionally, these boards are more transparent, voluntarily disclose business risks, limit non-audit services, and are associated with higher levels of performance. We confirm causality using director death as an exogenous shock.

We investigate the motivations behind corporate political contributions using a new survey methodology employing AI-generated agents (“Digital Executives”) representing S&P 500 CEOs. Surveying 4,600 AI-generated agents, we find that executives primarily view political contributions as strategic investments that extract economic value and secure critical information to navigate policy landscapes. These motivations dominate rationales related to institutional legitimacy or agency considerations, particularly in the high political uncertainty environments perceived by the agents. Our results provide direct evidence of the drivers of corporate political strategy under uncertainty, highlighting the critical roles of value capture and information acquisition.

The job openings-to-employment ratio (JOE), defined as the number of job postings divided by the employment level, is among the strongest known predictors of the equity premium. We find that JOE outperforms a broad set of over two dozen popular predictor variables in both in-sample and out-of-sample forecasting tests. Forecasts based on JOE also produce gains of 2.91% in annualized certainty equivalent return and 0.20 in annualized Sharpe ratio relative to forecasts based on the historical mean equity premium. The empirical results are consistent with a standard production-based asset pricing model with labor inputs and search frictions.

This paper investigates the role of scale in Real Estate Mutual Fund (REMF) performance. We test the impact of both fund-level and industry-level economies of scale on fund performance. We provide consistent evidence that industry size erodes REMF performance. After controlling for endogeneity concerns, we document an insignificant relation between fund size and performance. Taken together, these findings suggest that the rapid growth of the REMF industry over the past few decades has materially impacted active managers' ability to consistently outperform their passive benchmarks. As more capital flows into the industry, competition for alpha increases, and investment opportunities dwindle. This effect is stronger in funds who are especially active in seeking out those increasingly elusive opportunities. Specifically, the effect of industry size on alpha is particularly negative for funds with higher turnover ratios, expense ratios, and volatility of returns.

We examine the effect of investor attention on value loss due to securities class action lawsuits and litigation-based fraud discovery. We find that investor attention is positively associated with damage to corporate reputation and the magnitude of the value losses suffered by defendant firms. The reputational damage to defendant firms with higher investor attention is evident from poor operational performance and lower institutional ownership after filing. Investor attention is positively associated with the diffusion of information regarding fraud and it accelerates lawsuit filing. The effects of investor attention, however, are not subsumed by the severity of the fraud. Our results are robust to a battery of tests that addresses selection and endogeneity concerns.

We examine S&P 500 firms over 1999–2014 that characterize their annual performance with extreme positive language. Only 18% of such firms increase shareholder value, while over 80% have either negative or insignificant abnormal returns. Our evidence suggests that firms often base their claims of extreme positive performance on high raw returns or strong relative accounting performance. In comparison to firms that generate positive abnormal returns without boasting, our sample firms tend to have superior accounting performance. We conclude that boasting about performance is rarely associated with value creation and is more consistent with an emphasis on accounting metrics.