We develop a method that identifies the attention paid by earnings call participants to firms'
climate change exposures. The method adapts a machine learning keyword discovery …

This article reviews research on the economics of information in real estate. It covers equity
investment in private and public markets and intermediation by brokers. The review shows …

Automated and accurate real estate valuation benefits buyers and sellers in real estate
markets. So far, the literature on expert systems for real estate valuation has primarily …

Navigating the complex landscape of corporate climate disclosures and their real impacts is
crucial for managing climate-related financial risks. However, current disclosures oftentimes …

Real and private-value assets—defined here as the sum of real estate, infrastructure,
collectibles, and noncorporate business equity—compose an investment class worth an …

This paper employs machine learning to quantify the value of “soft” information contained in
real estate property descriptions. Textual descriptions contain information that traditional …

Corporate climate disclosures are considered an essential prerequisite to managing climate-
related financial risks. At the same time, current disclosures are imprecise, inaccurate, and …

The constant-quality assumption in repeat-sales house price indexes (HPIs) introduces a
significant time-varying attribute bias. The direction, magnitude, and source of the bias …

Drawing on real options and resource dependence theories, this study examines how firms
adjust their innovation investments to address trade policy effect uncertainty (TPEU), a type …

Bitcoin halvings are associated with two potential phenomena:(1) they limit Bitcoin supply,
potentially boosting prices, and (2) they reduce miners' revenue, which might undermine …