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Predicting Housing Market Sentiment: The Role of Financial, Macroeconomic and Real Estate Uncertainties

Hardik Marfatia (), Christophe André () and Rangan Gupta ()
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Hardik Marfatia: Department of Economics, Northeastern Illinois University, 5500 N St Louis Ave, BBH 344G, Chicago, IL 60625, USA

No 202061, Working Papers from University of Pretoria, Department of Economics

Abstract: Sentiment indicators have long been closely monitored by economic forecasters, notably to predict short-term moves in consumption and investment. Recently, housing sentiment indices have been developed to forecast housing market developments. Sentiment indices partly reflect economic determinants, but also more subjective factors, thereby adding information, particularly in periods of uncertainty, when economic relations are less stable than usual. While many studies have investigated the relevance of sentiment indicators for forecasting, few have looked at the factors which shape sentiment. In this paper, we investigate the role of different types of uncertainty in predicting housing sentiment, controlling for a wide set of economic and financial factors. We use a dynamic model averaging/selection (DMA/DMS) approach to assess the relevance of uncertainty and other factors in forecasting housing sentiment at different points in time. We find that housing sentiment forecast errors from models incorporating uncertainty measures are up to 40% lower at a two-year horizon, compared with models ignoring uncertainty. We also show, by examining DMS posterior inclusion probabilities, that uncertainty has become more relevant since the 2008 global financial crisis, especially at longer forecast horizons.

Keywords: Housing sentiments; Uncertainty; DMA; DMS (search for similar items in EconPapers)
JEL-codes: C53 E44 R31 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2020-06
New Economics Papers: this item is included in nep-for, nep-mac and nep-ure
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