A regional decomposition of US housing prices and volume: market dynamics and Portfolio diversification
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A regional decomposition of US housing prices and volume: market dynamics and Portfolio diversification Nikolaos Antonakakis1,2 · Ioannis Chatziantoniou2 · David Gabauer3,4 Received: 3 December 2019 / Accepted: 3 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In this study, we investigate the lead–lag relationship between housing prices and sales volume across four US regional housing markets, namely Midwest, Northeast, South, and West. To achieve this, we employ a time-varying parameter vector autoregressive framework of analysis that focuses on dynamic connectedness. We not only investigate how either prices or volumes independently co-move across regions but also, we provide evidence on how prices and volumes combined interact with each other across regions over time. In addition, considering the fact that the relevant connectedness index that emerges from our analysis can be used as a measure of risk, we proceed with the development of portfolios aiming to identify opportunities for reducing investment risk in the housing market. Main findings indicate that (i) all four regions can either transmit or receive shocks in the housing market with regard to prices and volume, (ii) during turbulent economic periods, it is sales volume shocks that drive developments in the US housing market, and (iii) there is potential for effective portfolio diversification. Results have policy implications particularly considering the negative outcomes of overheated housing markets and are also relevant to investors and finance professionals for formulating effective portfolio diversification strategies. Keywords US real estate market · Transaction volume · TVP-VAR · Dynamic connectedness · Regional connectedness decomposition · Portfolio management JEL Classification C32 · G10 · G20 * Ioannis Chatziantoniou [email protected] 1
Department of Business and Management, Webster Vienna Private University, Praterstrasse 23, 1020 Vienna, Austria
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Economics and Finance Subject Group, Portsmouth Business School, University of Portsmouth, Portland Street, Portsmouth PO1 3DE, UK
3
Software Competence Center Hagenberg GmbH, Softwarepark 21, 4232 Hagenberg, Austria
4
Institute of Applied Statistics, Johannes Kepler University, Altenbergerstrasse 69, 4040 Linz, Austria
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1 Introduction Investigating housing market conditions has gained much prominence over time, especially in the years that followed the global financial crisis (GFC). To a certain extent, the housing market (i) is closely related to developments in the business cycle (Leamer 2007), (ii) provides a channel for monetary policy (Mishkin 2007), and (iii) lies at the epicenter of research in relation to asset bubbles (Shiller 2014). In this regard, a thorough investigation of the factors that fashion developments within the housing market not only facilitates our understanding of the broader economy, but also contributes to effective policy decision making. In light of
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