Knowledge that Transforms

We study opinion dynamics in a social network consisting of two groups. Agents update their opinions by conforming to members of their own group while rejecting the views of the opposing group (affective polarization), and by listening to a media outlet that may provide biased information. We characterize the long-run opinions and identify when affective polarization and media bias lead to ideological polarization, persistent disagreement, or failures of learning. We also derive when information interventions or censorship improve the accuracy of average opinions and reduce disagreement, and when they backfire: better information helps only under specific media bias configurations and when directed to the agents we identify as most effective at propagating it through the network.

This paper studies asset pricing under expectations‐based reference‐dependent preferences in a general equilibrium framework. We show that reference‐dependent preferences can generate self‐fulfilling risk panics, producing sentiment‐driven asset price fluctuations through a feedback loop between current prices and perceived future downside risk—dynamics impossible under standard expected utility. The model helps explain empirical puzzles including (i) excess volatility, (ii) asymmetric volatility, (iii) asymmetric sentiment over the business cycle, (iv) excess asset price comovement, and (v) weak correlations between stock returns and economic fundamentals, alongside a sizable equity premium. Additional empirical evidence based on closed‐end fund discounts and quantitative analysis support the theory.

We study a parsimonious model of a competitive labor market in which firms privately screen workers to identify talent. The equilibrium exhibits dispersion in wages and productivity; when talent is scarce, firms with superior screening skills post higher wages, attract better applicants, and recruit more talented workers. High-wage firms impose a compositional externality on low-wage firms, leading to equilibrium inefficiency: Welfare would be higher if low-skilled firms posted high wages and selected first. We also provide a micro-foundation for firms heterogeneous screening skills. When talented workers are better at screening (e.g. via superior referrals), a dynamic version of the economy converges to a unique steady state in which differences in talent, profits and screening skills persist forever.

How did #MeToo alter collaboration between women and men? I show junior female researchers start fewer projects after #MeToo. A decrease in collaborations with male coauthors—especially new senior male coauthors at the same institution—largely explains the decline. The decrease is larger at universities with higher perceived harassment accusation risk and smaller where both women and men publicly express greater awareness of gender issues. I find no evidence that reduced collaboration improves research outcomes for junior female researchers. The results suggest that #MeToo led to a breakdown in trust that came at a cost for junior women's career opportunities.

We study how firm-level carbon emissions affect bank lending and real outcomes in a sample of global firms with syndicated loans. We exploit bank-level climate commitments as firm-level shocks to lending relationships, using firms' prior credit exposures to identify credit supply effects. Firms with higher emissions that previously borrowed from committed banks receive less bank credit. Evidence from lending volumes, prices, and within-firm-time loan-level data indicates a supply-side shift away from high-emission firms, not explained by borrower risk. Affected firms reduce debt, leverage, size, and investment, yet we find no reduction in future emissions, instead documenting evidence consistent with greenwashing.

We propose a new framework to explain the factor structure in the full cross section of Treasury bond returns. Our method unifies non-parametric curve estimation with cross-sectional factor modeling. We identify smoothness as a fundamental principle of the term structure of returns. Our approach implies investable factors, which correspond to the optimal spanning basis functions in decreasing order of smoothness. Our factors explain the slope and curvature shapes frequently encountered in PCA. In a comprehensive empirical study, we show that the first four factors explain the time-series variation and risk premia of the term structure of excess returns. Cash flows are covariances as the exposure of bonds to factors is fully explained by cash flow information. We identify a state-dependent complexity premium. The fourth factor, which captures complex shapes of the term structure premium, substantially reduces pricing errors and pays off during recessions.