Combining a randomized controlled trial with administrative and survey data, this paper shows that credit limit extensions significantly increase total spending and income expectations. By controlling for changes in personal income expectations, the spending response to credit limit extensions weakens by approximately 30%. For financially unconstrained consumers, expectation changes account for around two‐thirds of the spending responses to limit extensions. These findings are consistent with consumers inferring future income from credit supply.

This paper analyzes the impact of the Sarbanes–Oxley (SOX) Act on individuals’ decisions to invest their human capital in regulatory compliance. Exploiting geographic variation in SOX-induced growth in the demand for accounting labor and rich survey data on college students, we find that freshmen from regions with greater public company presence exhibit a more marked increase in the propensity to major in accounting after the enactment of SOX. Consistent with the financial incentives mechanism, we find that students respond more to SOX when they have stronger pecuniary preferences, when they are better positioned to seize the financial rewards of accounting, and when they have better access to information about SOX-induced changes in monetary returns to the accounting major. Finally, regions with greater public company presence exhibit larger increases in local wages and employment in the accounting industry.

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We examine how in-person and virtual interactions shape mutual fund investment decisions using a comprehensive dataset of corporate site visits. Before COVID-19, fund pairs jointly attending in-person visits trade more similarly (by 20% of a standard deviation) than matched controls. The effect holds for stocks unrelated to the hosting firm and appears in firm-level, industry, geographic, and asset allocation decisions; it is stronger among managers with prior familiarity, similar seniority, and mixed gender. Stocks purchased by jointly visiting funds earn higher subsequent returns, indicating that these exchanges convey valuable information. Exploiting the exogenous shift to virtual communication induced by COVID-19, we find that in-person visits remain associated with correlated trading during the pandemic, whereas virtual visits have substantially weaker effects. A survey of fund managers confirms that site visits prompt information exchange, follow-up research, and portfolio adjustments. In-person interactions appear central to information acquisition; and virtual interactions do not easily replicate this function.

We explore the factor structure in delta-hedged equity option returns. A sparse latent factor model generates a correlation of 0.90 or higher between average and predicted option returns. A comparable performance is achieved with a characteristic-based model containing four factors: the equally weighted option portfolio, a factor based on the difference between historical and implied volatilities, a factor based on the ratio of corporate cash holdings to the total value of the firm’s assets, and a factor based on volatility of volatility. Traditional stock return factors cannot explain these option factors.

We show that banks use industry knowledge acquired through corporate lending in mortgage lending, a phenomenon we refer to as the “industry expertise channel.” Specifically, banks that specialize in particular industries expand their mortgage lending activity in regions where those industries are concentrated. The impact of industry expertise increases with information asymmetry and borrower risk. In addition, mortgages originated from this channel contain more soft information and perform better. The effect of the channel increases after unexpected industry distress and the 2008 financial crisis, suggesting that the effect is likely causal.

We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behaviour and establish conditions under which all parts of the model can be recovered from a sequence of choices. We allow peers to affect preferences, consideration, or both. We show that these peer-effect mechanisms have different behavioural implications in the data. This allows us to recover the set and the type of connections between the agents in the network. We then use this information to recover each agent’s preferences and consideration mechanisms. These nonparametric identification results allow for general forms of heterogeneity across agents and do not rely on the variation of either exogenous covariates or the set of available options (menus). We apply our results to model expansion decisions by tea chains and find evidence of limited consideration. We simulate counterfactual predictions and show how limited consideration slows market penetration and competition.

We examine whether politicians affect local firms’ industrial pollution, and whether such effects are transmitted through plant-level networks to affect pollution in other regions. We first document that close Democrat wins in U.S. congressional races are associated with lower emissions and higher abatement at the plant level, especially when politicians have strong pro-environmental preferences. We also find evidence of reallocation: firms shift emissions away from areas represented by Democrats. However, reallocation is imperfect: firm-level costs are higher and market-to-book ratios lower if firms’ representation is more Democratic. Lower pollution-related illnesses around plants in Democratic districts suggest pass-through effects on local communities.