Knowledge that Transforms

We examine how corporate misconduct affects merger and acquisition (M&A) activity of non-prosecuted peer firms. We find that exposure to peer misconduct increases the propensity to participate in M&A transactions, both as an acquirer and as a target. Firms exposed to peer misconduct experience adverse financial and valuation pressures, creating opportunities for financially stronger firms to acquire distressed rivals at discounted prices. We show that acquisitions involving targets exposed to peer misconduct are characterized by lower takeover premiums, a higher fraction of stock payment, higher acquirer announcement returns, and greater deal synergies. Overall, the evidence supports the view that misconduct spillovers disproportionately affect targets through heightened regulatory pressures and compliance costs, shifting bargaining power toward acquirers in M&A transactions.

Firms’ green technology investments are increasingly important for competitive positioning, yet their impact on long-run performance remains unclear. Using electricity capacity data for global utility firms, we construct a unique structural measure of technological greenness based on renewable versus fossil fuel physical infrastructure. We find that adopting sustainable technologies is followed by a long-run improvement in corporate fundamentals that is only partially reflected in stock prices, yielding superior returns over a multi-year horizon. These results partly reflect higher revenue growth in liberalized retail markets rather than investor sentiment, revealing a consumer-based mechanism that likely extends to competitive downstream sectors.

We survey 153 empirical studies of family firms and document 192 operational definitions representing 25 distinct definition types. These definitions can be decomposed into five recurring, codable dimensions: ownership, management, board representation, embeddedness, and succession. We relate these dimensions to economic mechanisms including agency conflicts, residual control rights, transaction costs, and dynastic control. Alternative definitions select systematically different populations and yield materially different estimates of firm performance and innovation. Definition choice is largely unrelated to the research question, except in succession studies. Ownership thresholds track private enforcement of self-dealing rules, but not statutory shareholder rights or rule of law. We conclude that the family firm is a family of related constructs rather than a single latent construct. Definitions should therefore match the family-firm construct implied by the research question, and results should be reported across alternative classification rules.

We reinvestigate Anderson, Reeb, and Zhao's findings that informed short selling is unique to family firms and driven by information leakage from internal disputes. Using the same firm sample and more comprehensive short‐selling data, we find that short selling predicts future returns in both family and nonfamily firms. We also find no significant difference in abnormal short selling before negative earnings announcements. In extended sample periods, short selling continues to predict returns for nonfamily firms under both ownership‐based and familial‐link definitions. Overall, our evidence suggests that short sellers are broadly informed and that family firms are not uniquely vulnerable.

We build a granular data set of residential property yields using rental and sale listings from a major German real estate platform. With more than 1.5 million property-level rent-to-price ratios, we document a novel heterogeneity puzzle. About two-fifths of yield dispersion remains unexplained after controlling for extensive observable property characteristics and postal code-level time-varying factors using fixed effects. When we absorb finer neighborhood amenities through richer fixed effects, the unexplained share remains close to one-third. This evidence points to the importance of investors’ beliefs and preferences—rather than several alternative explanations we test—as sources of heterogeneity in risk premia.

The exchange rate predictability puzzle—that fundamentals fail to forecast short-horizon exchange rate movements out of sample—has long resisted resolution. We show that fundamentals do matter, but their effects vary with global financial conditions. Using a rich set of country characteristics interacted with global state variables and machine-learning techniques to handle the high-dimensional data, we document that interactions between country characteristics and foreign exchange market volatility are particularly important, consistent with a “flight to fundamentals” during periods of financial stress. Our forecasts deliver substantial economic value and offer new insight into the carry trade.