A rapidly expanding universe of technology-focused startups is trying to change and improve the way real estate markets operate. The undisputed predictive power of machine learning (ML) models often plays a crucial role in the ‘disruption’ of traditional processes. However, an accountability...

We study the micro-level evolution of residential house prices using data on repeat sales on Manhattan Island from 2004 to 2015. We document that excess price comovement is a highly local and persistent phenomenon. The strength of such excess comovements vanishes with both spatial and temporal...

Accession of Bulgaria to the European Union is expected to result in increases in the prices of all types of real estate, these changes are expected to differ across the segments of the national real estate market. Real estate prices have been inXuenced primarily by local demand, government...

The optimal investment to mitigate climate change crucially depends on the discount rate used to evaluate the investment's uncertain future benefits. The appropriate discount rate is a function of the horizon over which these benefits accrue and the riskiness of the investment. In this paper, we...

This paper identifies which investments in school facilities help students and are valued by homeowners. Using novel data on school district bonds, test scores, and house prices for 29 U.S. states and a research design that exploits close elections with staggered timing, we show that increased...

We study whether floods can affect financial stability through a credit risk channel. Our focus is on the Netherlands, a country situated partly below sea level, where insurance policies exclude property damages caused by some types of floods. Using geocoded data for close to EUR 650 billion in...

This paper identifies which investments in school facilities help students and are valued by homeowners. Using novel data on school district bonds, test scores, and house prices for 29 U.S. states and a research design that exploits close elections with staggered timing, we show that increased...

The Case-Shiller is the reference repeat-sales index for the U.S. residential real estate market, yet it is released with a two-month delay. We find that incorporating recent information from 71 financial and macro predictors improves backcasts, now-casts, and short-term forecasts of the index...

We examine the profitability of personalized pricing policies that are derived using different specifications of demand in a typical retail setting with consumer-level panel data. We generate pricing policies from a variety of models, including Bayesian hierarchical choice models, regularized...