Milstein All Research

We develop a conceptual framework and an empirical methodology to analyze the effect of rising interest rates on the value of U.S. bank assets and bank stability. We mark-to-market the value of banks' assets due to interest rate increases from Q1 2022 to Q1 2023, revealing an average decline of 10%, totaling about $2 trillion in aggregate. We present a model illustrating how asset value declines due to higher rates can lead to self-fulfilling solvency runs even when banks' assets are fully liquid.

Professional house price forecast data are consistent with a rational model where agents must learn about the parameters of the house price growth process and the underlying state of the housing market. Slow learning about the long-run mean generates overreaction to forecast revisions and a modest response of forecasts to lagged realizations. Heterogeneity in signals and priors about the long-run mean helps the model account for cross-sectional dispersion in forecasts. Introducing behavioral biases helps improve the model's predictions for short-horizon overreaction and dispersion.

Recent decades have seen house prices grow strongly relative to incomes, making housing ever less affordable. We develop and quantify a model of segmented housing markets to study the drivers of rising housing costs and to evaluate policies aimed at curbing these costs. We show that rising wealth dispersion, together with stagnating housing supply, can explain the observed increase in housing costs. Demand side policies such as down payment assistance and mortgage interest deductions inadvertently cause upward pressure on house prices and exacerbate unaffordability.

We develop a new approach to understand the joint dynamics of transaction prices and trading volume in the market for commercial real estate. We start from a micro-founded model in which buyers and sellers differ in their private valuation of building characteristics, such as size, location, and quality. Consistent with the decentralized nature of the commercial real estate market, we model the probability that a seller meets a particular buyer, where the meeting probability depends on the characteristics of the buyer, the seller, and the building.

We show remote work led to large drops in lease revenues, occupancy, and market rents in the commercial office sector. We revalue New York City office buildings taking into account both the cash flow and discount rate implications of these shocks, and find a 46% decline in long run value. For all U.S. office markets combined, we find a $556.8 billion value destruction. Higher quality buildings were buffered against these trends due to a flight to quality, while lower quality office is at risk of becoming a stranded asset.

Residential properties with the lowest rent levels provide the highest investment returns to their owners. Using detailed rent, cost, and price data from the United States, Belgium, and The Netherlands, we show that this phenomenon holds across housing markets and time. If anything, low-rent units hedge business cycle risk. We also find no evidence for differential regulatory risk exposure. We document segmentation of investors, with large corporate landlords shying away from the low-tier segment possibly for reputational reasons.