Understanding Price-To-Rent Ratios Through Simulation-Based Distributions And Explainable Machine Learning

Vogt Jonas ()
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Vogt Jonas: Finance and Data-Science, Duale Hochschule Baden Wurttemberg Mannheim, Coblitzallee 1-9, 68163 Mannheim; Germany

Real Estate Management and Valuation, 2025, vol. 33, issue 3, 36-48

Abstract: Index-level price-to-rent (PTR) ratios are a widely used metric for analyzing housing markets, employed by both real estate practitioners and policymakers. This article seeks to improve the contextualization of observed PTR values by examining the interplay between these ratios and macroeconomic and housing-market developments in a non-linear framework. We analyze historical data on housing prices, rents and macroeconomic developments from 18 advanced economies, spanning from 1870, using Boosted Regression Trees and explainable machine learning techniques. As a precursor to this analysis, we also present the empirical distribution of the price-to-rent ratio and the implied housing risk premia across all years and countries.

Keywords: real estate finance; property valuation; price rent ratio; explainable machine learning; property investment (search for similar items in EconPapers)
JEL-codes: G10 R31 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:remava:v:33:y:2025:i:3:p:36-48:n:1004

DOI: 10.2478/remav-2025-0024

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