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Bibliographic Details
Main Authors: Chwila, Adam, Hadaś-Dyduch, Monika, Krzciuk, Małgorzata, Stachurski, Tomasz, Wolny-Dominiak, Alicja, Żądło, Tomasz
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2502.15905
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author Chwila, Adam
Hadaś-Dyduch, Monika
Krzciuk, Małgorzata
Stachurski, Tomasz
Wolny-Dominiak, Alicja
Żądło, Tomasz
author_facet Chwila, Adam
Hadaś-Dyduch, Monika
Krzciuk, Małgorzata
Stachurski, Tomasz
Wolny-Dominiak, Alicja
Żądło, Tomasz
contents The study focuses on improving the ex ante prediction accuracy assessment in the case of forecasting various house price dispersion measures in the USA. It addresses a critical gap in real estate market forecasting by proposing a novel method for assessing ex ante prediction accuracy under unanticipated shocks. The proposal is based on a parametric bootstrap approach under a misspecified model, allowing for the simulation of future values and estimation of prediction errors in case of unexpected price changes. The study highlights the limitations of the traditional approach that fails to account for unforeseen market events and provides a more in-depth understanding of how prediction accuracy changes under unexpected scenarios. The proposed methods offers valuable insights for real estate market management by enabling more robust risk assessment and decision-making in the face of unexpected market fluctuations. Real data application is based on longitudinal U.S. data on real estate transactions.
format Preprint
id arxiv_https___arxiv_org_abs_2502_15905
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Improving ex ante accuracy assessment in predicting house price dispersion: evidence from the USA
Chwila, Adam
Hadaś-Dyduch, Monika
Krzciuk, Małgorzata
Stachurski, Tomasz
Wolny-Dominiak, Alicja
Żądło, Tomasz
Methodology
Applications
The study focuses on improving the ex ante prediction accuracy assessment in the case of forecasting various house price dispersion measures in the USA. It addresses a critical gap in real estate market forecasting by proposing a novel method for assessing ex ante prediction accuracy under unanticipated shocks. The proposal is based on a parametric bootstrap approach under a misspecified model, allowing for the simulation of future values and estimation of prediction errors in case of unexpected price changes. The study highlights the limitations of the traditional approach that fails to account for unforeseen market events and provides a more in-depth understanding of how prediction accuracy changes under unexpected scenarios. The proposed methods offers valuable insights for real estate market management by enabling more robust risk assessment and decision-making in the face of unexpected market fluctuations. Real data application is based on longitudinal U.S. data on real estate transactions.
title Improving ex ante accuracy assessment in predicting house price dispersion: evidence from the USA
topic Methodology
Applications
url https://arxiv.org/abs/2502.15905