Financial Engineering

We exploit regional variations in exposure to heat stress to study if physical climate risk is priced in municipal and corporate bonds as well as in equity markets. We find that local exposure to damages related to heat stress equaling 1% of GDP is associated with municipal bond yield spreads that are higher by around 15 basis points per annum (bps), the effect being larger for longer-term, revenue-only and lower-rated bonds, and arising mainly from the expected increase in energy expenditures and decrease in labor productivity.

This paper recasts the consumption asset pricing model in terms of observable accounting outcomes by recognizing accounting principles that connect those outcomes to consumption and the risk to consumption. The model prompts the construction of a pricing factor from observed accounting information. The factor performs well relative to extant factors in explaining cross-sectional returns. Further, it delivers out-of-sample expected returns that forecast the actual returns and the forward betas that investors actually experience.

In modern asset markets, man and machine compete for profits. How does each fare? I build a learning model in which quantitative investors (reliant on computer models) have more learning capacity but less flexibility to adapt to market conditions than discretionary investors (reliant on human judgment). I use machine learning to categorize US active equity mutual funds as quantitative or discretionary. Consistent with the model's predictions, I find that quantitative funds hold more stocks, specialize in stock picking, and engage in more overcrowded trades.

Housing affordability has become the main policy challenge for most large cities in the world. Zoning, rent control, housing vouchers, and tax credits are the main levers employed by policy makers. We build a new dynamic stochastic spatial equilibrium model to evaluate the effect of these policies on house prices, rents, residential construction, labor supply, output, income and wealth inequality, as well as the location decision of households within the city. The analysis incorporates risk, wealth effects, and resident landlords.

We use supervisory loan-level data to document that small firms (SMEs) obtain shorter maturity credit lines than large firms, post more collateral, have higher utilization rates, and pay higher spreads. We rationalize these facts as the equilibrium outcome of a trade-off between lender commitment and discretion. Using the COVID recession, we test the prediction that SMEs are subject to greater lender discretion. Consistent with this hypothesis, SMEs did not draw down whereas large firms did, even in response to similar demand shocks.

We examine the optimal financing of infrastructure when governments have limited financial commitment and can expropriate rents from private sector firms that manage infrastructure. While private firms need incentives to implement projects well, governments need incentives to limit expropriation. This double moral hazard limits the willingness of outside investors to fund infrastructure projects.

We analyze the impact of the Second Avenue Subway (Q-train) construction on local real estate prices, which capitalize the benefits of transit spillovers. We find evidence of higher real estate prices in the vicinity of areas served by the new Q-train, relative to other areas in Manhattan's Upper East Side. Only 30% of the private value created by the subway leads is captured through property taxes, and is insufficient to cover the cost of the subway. Value capture through targeted property tax increases can help close the funding gap.