Knowledge that Transforms

We estimate price elasticities of housing supply for U.S. cities by examining the impact of foreign purchases on housing prices and quantities. After other countries introduced foreign-buyer taxes beginning in 2011, both house prices and quantities increased more in locations with high foreign-born populations. An increase in global capital inflows, instrumented with tax policy changes scaled by immigrant exposure, increased prices and quantities over 2011–2018. We combine these estimates to construct new local supply elasticities, which average 0.26 and range from 0.06 to 0.9. Compared to prior estimates, our elasticities are more inelastic and change cities’ relative rankings.

We estimate β-δ time preferences and relative risk aversion (RRA) using a lifecycle model including stochastic income, liquid and illiquid assets, credit cards, dependents, Social Security, mortality, and bequests. Preference parameters are identified by cross-tabulating four lifecycle age intervals and four balance sheet moments: the share of households carrying (ie, revolving) credit card debt, average carried credit card debt, average net wealth among households carrying credit card debt, and average net wealth among households not carrying credit card debt. The 16 moments are approximately matched by (MSM) parameter estimates β=0.53, δ=0.99, and RRA = 1.9.

During the COVID-19 pandemic (2020-2022), Chinese cities witnessed a paradox: residential land and new house prices surged while transaction volumes plummeted. We attribute this to local governments’ active price management through supply controls, land acquisitions by local government financing vehicles (LGFVs), and limits on new home sales permits. Cities more dependent on land sales and land-backed debt before the pandemic experienced greater price increases and price–volume divergence, with LGFVs buying more land at higher prices than other buyers. These interventions helped sustain fiscal financing but deepened developers’ financial distress, revealing unintended consequences of local governments’ fiscal strategies during downturns.

Environmental, social, and governance (ESG) funds have heterogeneous incentives to engage with portfolio firms. If funds view ESG as a value driver, then these incentives will affect funds’ behavior and thus their impact on firms. We compare ESG funds with similar levels of ESG investments but different incentives to engage. Funds with higher incentives to engage, that is, committed ESG funds, conduct more ESG-related information acquisition, pursue longer term investment strategies, engage more intensely on ESG issues, and have greater real impacts. Moreover, committed ESG funds have outperformed other ESG funds within subportfolios with higher and more effective ESG engagement.

We propose an equilibrium corporate bond pricing model that accommodates the heterogeneity in institutional investors’ preferences and mandates in an empirically tractable way. Our model, estimated on rich holdings data, quantifies investors’ preferences and demand elasticities, with inelastic insurers focusing on the investment-grade segment, and elastic mutual funds substituting across ratings groups. The model offers a novel quantitative perspective of the effect of recent trends in institutional ownership on equilibrium credit spreads and the funding costs of corporations. Overall, our model emphasizes the composition of institutional demand as an important state variable for corporate bond pricing.

This paper investigates the impact of introducing junior unsecured loans (i.e., FinTech loans) into the small business lending market. Using French administrative data, we find that firms experience a 13% increase in bank credit after receiving a FinTech loan. We use propensity score matching procedures and a shift-share instrument to account for credit demand. The credit increase only occurs when FinTech borrowers invest in new assets, and Fintech borrowers are subsequently more likely to pledge collateral to banks. This suggests that firms use FinTech loans to acquire assets that they then pledge to banks, thereby increasing total borrowing capacity.

We measure popular sentiment toward finance by applying a large language model to millions of books published in eight countries over hundreds of years. We extensively validate this measure both internally and externally. We document persistent differences in finance sentiment across countries despite ample time-series variation. Books written in the languages of more capitalist countries discuss finance in a more positive context. Finance sentiment is correlated with survey-based measures of financial market participation and income inequality. Finance sentiment declines one year before rather than after financial crises. Positive shocks to finance sentiment are followed by higher output and credit growth.

We conduct the first large-scale study of how different stakeholder groups assess corporate culture and quantify the economic implications of those differences. We employ generative AI to analyze analyst reports, call transcripts, and employee reviews, and organize the extracted information into a knowledge graph that links a culture type to its perceived causes and effects. We demonstrate that the divergence in different stakeholder groups' assessment of culture aligns with their distinct roles and economic incentives. Moreover, we show that analysts' culture analyses are incorporated into stock recommendations and target prices, and investors react to divergence in stakeholders' assessment of culture.