Abstract:In this article, we propose a novel estimator that builds on recent advances in heterogenous estimators to introduce the concepts of cross‐sectional heterogeneity and cross‐sectional dependency in the machine learning (ML) literature. The performance of the proposed method is evaluated in forecasting house prices at the county level for the 56 most populated Metropolitan Statistical Areas in the U.S., identifying bubbles in local house markets as they form and measuring the returns on a trading strategy based … Show more
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