Alexander F. Wagner

This paper provides archival and experimental evidence that equity market feedback influences firms' environmental behavior. Following the publication of U.S. Reports on Carcinogens, firms using newly identified carcinogens that experience particularly negative stock-price reactions reduce toxic waste more, especially when their worker exposure is high. Cross-sectional tests show stronger effects where market signals are likely to be more informative, and peer-firm evidence suggests that firms also learn from affected firms' stock-price reactions. We complement the archival evidence with an information provision experiment using participants with managerial experience in TRI-reporting industries. Participants assigned randomly to a negative stock-market signal are more likely to state that they would undertake costly toxic-release reductions and abatement. Overall, while existing research emphasizes divestment and engagement, this paper highlights an additional mechanism through which financial markets shape corporate responsibility: prices convey information that managers use to adjust environmental practices.

Who bears the losses if the demand for AI infrastructure falls short? Reported debt gives an incomplete answer: the firms building the infrastructure have also signed leases, purchase commitments, and guarantees. From the filings of every listed firm with a major role in the build-out, 37 in all, I code 155 arrangements whose lease and purchase payments due within five years are 5.0 times the firms' debt service. A financing model explains why a supplier that can redeploy a failed customer's asset supports the customer and takes rights to the asset. In a stress test that halves demand and capacity values, the guarantees and backstops cut other counterparties' losses from $23.1bn to $1.5bn by shifting them onto the supporting firms' shareholders, who already bear almost all of the $1.2tn the shock costs. The build-out's credit risk lies in these contracts and in the cash of the firms that write them.

How costly is uniform congestion pricing when locations differ in value? I study geostationary orbit, where satellites serve different markets from recorded positions and supported $77 billion in satellite television revenues in 2023. I estimate a spatial model of commercial entry in which efficient charges rise with demand. In the baseline estimates, the optimal uniform charge captures 66 percent of the attainable welfare gain, or 79 percent when income replaces population as the demand measure. It reduces congestion but ends entry at positions accounting for less than a tenth of modeled efficient surplus. Longitude-specific charges recover the rest while preserving entry at marginal positions. Most additional gains arise at positions the uniform charge keeps active. Correcting underpricing at high-demand positions contributes the largest share. Substantial spatial heterogeneity can therefore coexist with large gains from a common price, whose cost depends on the surplus exposed to its pricing errors.

SpaceX came to market in June 2026 at $1.77 trillion, the largest initial public offering on record. I value it with a multi-segment cash-flow model calibrated to disclosed financials, forecasts, and comparables, and price the real options that other valuations leave unmodeled. Inverting the model, I find an asymmetry: every operating input must sit at or beyond the top of its supported range to justify the price, whereas a discount-rate cut well inside estimation error suffices. The price is therefore a statement about the price of risk, not the business: paying it means accepting a low expected return, hard to reconcile with the high option-implied uncertainty, since systematic risk would warrant a higher one. Index flows and portfolio motives are temporary or capped; beliefs are not, and surveys suggest buyers expect the cash-flow story plus an above-market return, not the low one the arithmetic implies.

As artificial intelligence advances, must support for the technology come at the welfare state's expense? In a 14-wave Japanese panel spanning ChatGPT's arrival, we find no such trade-off, on two margins: beliefs and jobs. Within person, support for AI and support for redistribution move together, a link that weakens where success is read as earned, not lucky. Across occupations, the most exposed workers --- educated and higher-income, whom income-based self-interest predicts to resist redistribution --- moved toward redistribution relative to the least exposed as AI diffused, while their AI attitudes moved like everyone else's. Overall, these results suggest that voters bundle support for the technology with demand for compensation.

AI decision assistants are entering domains where moral judgments matter, yet their effects on ethical choices remain poorly understood. In a preregistered multi-wave experiment, participants faced repeated ethical dilemmas with or without an AI assistant that scaffolded reflection without recommending actions. AI assistance increased decision confidence (Cohen's d = 0.40) more strongly than it increased ethical choices (d = 0.21), creating a confidence trap. The pattern persisted when controlling for choice improvements (residualized d = 0.36), and deeper reflection predicted choices but not confidence, consistent with confidence responding to the procedure rather than its content. Effects were strongest among morally motivated participants. These findings indicate an AI governance risk: decision support may inflate users' confidence more reliably than it improves stated-choice quality, and evaluations should not treat user confidence as evidence of effectiveness.

Unethical behavior, deception, and fraud are major concerns in corporate governance. This paper examines the effectiveness of contemplation questions (CQs) as ethical decision aids intended to activate moral agency and prompt employees to consider their actions from various perspectives (e.g., self, peers, company). Although we find that 44% of S&P 200 and Fortune Global 200 companies use CQs, their behavioral impact is not well understood. Using two preregistered, incentivized vignette experiments, we show that the effects of CQs depend critically on the level of engagement they require. In Study 1 (N = 1,986), where participants were only passively presented with CQs, we find no impact on ethical decisions, either in the aggregate or by reference group. In Study 2 (N = 1,322), where participants were actively engaged by answering CQs, we again find no overall effect, but uncover a striking heterogeneity: CQs marginally increase ethical decisions among individuals with high moral identity, yet significantly reduce such decisions among those with low moral identity. These findings align with a conceptual framework of motivated moral reasoning and suggest that while CQs can benefit some individuals, they may backfire precisely among those predisposed to unethical behavior.

During the COVID-19 stock market crash, U.S. stocks with higher institutional ownership (IO) performed worse than those with lower IO. By studying firm-level changes, we identify two mechanisms behind this effect: a sudden downscaling of institutional capital in the equity market and a collective attempt by institutions to reposition their equity portfolios toward more COVID-resilient stocks. The stock price effects of their “portfolio downscaling” trades quickly reversed in the market’s recovery phase, whereas those of their “portfolio repositioning” trades lingered. The institutional rush for firm resilience also caused price pressures, with retail investors providing liquidity to stocks sold by institutional investors, both during the crisis and afterward. Overall, our results indicate that when a tail risk is realized, institutional investors amplify price crashes. This paper was accepted by Lukas Schmid, finance. Funding: S. Glossner and P. Matos acknowledge financial support from the Richard A. Mayo Center for Asset Management at the Darden School of Business. S. Ramelli and A. F. Wagner acknowledge financial support from the University of Zurich Research Priority Program “Financial Market Regulation.” Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03411 .

Following the 2023--2024 Tokyo Stock Exchange (TSE) capital-efficiency initiative, investors favored low price-to-book (PBR) firms, particularly those with high return on equity (ROE). These effects are concentrated among persistently undervalued firms, increase smoothly with the degree of undervaluation rather than jumping at the regulatory threshold, and are robust to endogenous treatment assignment. Although firms' value-enhancing plans were already publicly available in corporate governance reports, the TSE's consolidated compliance list triggered strong market reactions, consistent with a salient informational event. We find no short-run improvements in realized profitability or upward revisions in analyst earnings forecasts, but significant declines in illiquidity and increases in valuation ratios among low-PBR firms. We also find little evidence of a persistent ``price-of-shame'' mechanism or strong industry-level spillovers, although spillovers through non-industry links cannot be fully ruled out. Overall, the evidence suggests that the reform primarily triggered investor-side repricing of chronic undervaluation rather than immediate changes in firm behavior.