Housing Price Cycle Interdependencies and Comovement: A Markov-Switching Approach

References

• Álvarez, L.-J., Bulligan, G., Cabrero, A., Ferrara, L., & Stahl, H. (2009). “Housing Cycles in the Major Euro Area Countries,” Banque de France Working Paper No. 269.
   Google Scholar
• Anderson, R., Boney, V., & Guirguis, H. (2012). The impact of switching regimes and monetary shocks: An empirical analysis of REITs. Journal of Real Estate Research, 34(2), 157–182. https://doi.org/10.1080/10835547.2012.12091332
   Web of Science ®Google Scholar
• Arias, M. A., Gascon, C. S., & Rapach, D. E. (2016). Metro business cycles. Journal of Urban Economics, 94, 90–108. https://doi.org/10.1016/j.jue.2016.05.005
   Web of Science ®Google Scholar
• Apergis, N., & Payne, J. E. (2012). Convergence in U.S. house prices by state: Evidence from the club convergence and clustering procedure. Letters in Spatial and Resource Sciences, 5(2), 103–111. https://doi.org/10.1007/s12076-011-0075-7
   Google Scholar
• Baltagi, B. H., Fingleton, B., & Pirotte, A. (2014). Spatial lag models with nested random effects: An instrumental variable procedure with an application to english house prices. Journal of Urban Economics, 80, 76–86. https://doi.org/10.1016/j.jue.2013.10.006
   Web of Science ®Google Scholar
• Baltagi, B. H., & Bresson, G. (2011). Maximum likelihood estimation and Lagrange multiplier tests for panel seemingly unrelated regressions with spatial lag and spatial errors: An application to hedonic housing prices in Paris. Journal of Urban Economics, 69, 24–42. https://doi.org/10.1016/j.jue.2010.08.007
   Web of Science ®Google Scholar
• Barros, C. P., Gil-Alana, L. A., & Payne, J. E. (2012). Comovements among U.S. state housing prices: Evidence from fractional cointegration. Economic Modelling, 29(3), 936–942. https://doi.org/10.1016/j.econmod.2012.02.006
   Web of Science ®Google Scholar
• Basu, S., & Thibodeau, T. G. (1998). Analysis of spatial autocorrelation in house prices. Journal of Real Estate Finance and Economics, 17(1), 61–85. https://doi.org/10.1023/A:1007703229507
   Web of Science ®Google Scholar
• Beracha, E., Freybote, J., & Lin, Z. (2019). The determinants of the ex ante risk premium in commercial real estate. Journal of Real Estate Research, 41(3), 411–442. https://doi.org/10.22300/0896-5803.41.3.411
   Web of Science ®Google Scholar
• Besner, C. (2002). A spatial autoregressive specification with a comparable sales weighting scheme. Journal of Real Estate Research, 24(2), 193–211. https://doi.org/10.1080/10835547.2002.12091092
   Google Scholar
• Carriero, A., Clark, T. E., & Marcellino, M. (2019). Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors. Journal of Econometrics, 212(1), 137–154. https://doi.org/10.1016/j.jeconom.2019.04.024
   Web of Science ®Google Scholar
• Carstens, R., & Freybote, J. (2021). Can the textual tone in REIT financial statements improve the information environment for commercial real estate investors? An investigation. Journal of Real Estate Research, 43(3), 335–354. https://doi.org/10.1080/08965803.2021.1985923
   Web of Science ®Google Scholar
• Case, A. C., Rosen, H. S., & Hines, Jr J. (1993). Budget spillovers and fiscal policy interdependence: Evidence from the states. Journal of Public Economics, 52(3), 285–307. https://doi.org/10.1016/0047-2727(93)90036-S
   Web of Science ®Google Scholar
• Choi, C. Y., & Hansz, J. A. (2021). From banking integration to housing market integration-evidence from the comovement of US metropolitan house prices. Journal of Financial Stability, 54, 100883. https://doi.org/10.1016/j.jfs.2021.100883
   Web of Science ®Google Scholar
• Chou, Y., & Chen, Y. (2014). Is the response of REIT returns to monetary policy asymmetric? Journal of Real Estate Research, 36(1), 109–136. https://doi.org/10.1080/10835547.2014.12091381
   Web of Science ®Google Scholar
• Clauretie, T. M., & Daneshvary, N. (2009). Estimating the house foreclosure discount corrected for spatial price interdependence and endogeneity of marketing time. Real Estate Economics, 37(1), 43–67. https://doi.org/10.1111/j.1540-6229.2009.00234.x
   Web of Science ®Google Scholar
• Clark, S. P., & Coggin, T. D. (2009). Trends, cycles and convergence in U.S. regional house prices. Journal of Real Estate Finance and Economics, 39(3), 264–283. https://doi.org/10.1007/s11146-009-9183-1
   Web of Science ®Google Scholar
• Cohen, J. P. (2010). The broader effects of transportation infrastructure: Spatial econometrics and productivity approaches. Transportation Research Part E: Logistics and Transportation Review, 46(3), 317–326. https://doi.org/10.1016/j.tre.2009.11.003
   Web of Science ®Google Scholar
• Cohen, J. P., Coughlin, C. C., & Yao, V. W, Federal Reserve Bank of St. Louis. (2016). Sales of distressed residential property: What have we learned from recent research? Review, 98(3), 159–188. https://doi.org/10.20955/r.2016.159-188
   Google Scholar
• Cohen, J. P., & Zabel, J. (2020). Local house price diffusion. Real Estate Economics, 48(3), 710–743. https://doi.org/10.1111/1540-6229.12241
   Web of Science ®Google Scholar
• Fischer, M., Füss, R., & Stehle, S. (2021). Local house price comovements. Real Estate Economics, 49(S1), 169–198. https://doi.org/10.1111/1540-6229.12331
   Google Scholar
• Francis, N., Owyang, M. T., and., & Soques, D. (2022). Business cycles across space and time. Journal of Money, Credit and Banking, 54(2), 921–952. https://doi.org/10.1111/jmcb.12860
   Google Scholar
• Freybote, J., & Seagraves, P. (2018). The impact of investor sentiment on commercial real estate market liquidity. Journal of Real Estate Research, 40(4), 597–628. https://doi.org/10.1080/10835547.2018.12091513
   Web of Science ®Google Scholar
• Frühwirth-Schnatter, S., & Kaufmann, S. (2008). Model-based clustering of multiple time series. Journal of Business & Economic Statistics, 26(1), 78–89. https://doi.org/10.1198/073500107000000106
   Web of Science ®Google Scholar
• Groshen, E. L., & Potter, S. M. (2003). Has structural change contributed to a jobless recovery? Federal Reserve Bank of New York Current Issues in Economics and Finance, 9(8), 1–7.
   Google Scholar
• Gyourko, J., Saiz, A., & Summers, A. (2008). A new measure of the local regulatory environment for housing markets: The Wharton residential land use regulatory index. Urban Studies, 45(3), 693–729. https://doi.org/10.1177/0042098007087341
   Web of Science ®Google Scholar
• Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57(2), 357–384. https://doi.org/10.2307/1912559
   Web of Science ®Google Scholar
• Hamilton, J. D., & Owyang, M. T. (2012). The propagation of regional recessions. Review of Economics and Statistics, 94(4), 935–947. https://doi.org/10.1162/REST_a_00197
   Web of Science ®Google Scholar
• Hernández-Murillo, R., Owyang, M. T., & Rubio, M. (2017). Clustered housing cycles. Regional Science and Urban Economics, 66, 185–197. https://doi.org/10.1016/j.regsciurbeco.2017.06.003
   Web of Science ®Google Scholar
• Holmes, M. J., Otero, J., & Panagiotidis, T. (2011). Investigating regional house price convergence in the United States: Evidence from a pair-wise approach. Economic Modelling, 28(6), 2369–2376. https://doi.org/10.1016/j.econmod.2011.06.015
   Web of Science ®Google Scholar
• Huang, H., Peng, L., & Yao, V. W. (2019). Comovements and asymmetric tail dependence in state housing prices in the USA: A nonparametric approach. Journal of Applied Econometrics, 34(5), 843–849. https://doi.org/10.1002/jae.2703
   Web of Science ®Google Scholar
• Hyun, D., & Milcheva, S. (2018). Spatial dependence in apartment transaction prices during boom and bust. Regional Science and Urban Economics, 68, 36–45. https://doi.org/10.1016/j.regsciurbeco.2017.11.001
   Web of Science ®Google Scholar
• Jaimovich, N., & Siu, H. E. (2020). Job polarization and jobless recoveries. Review of Economics and Statistics, 102(1), 129–147. https://doi.org/10.1162/rest_a_00875
   Web of Science ®Google Scholar
• Kallberg, J. G., Liu, C. H., & Pasquariello, P. (2014). On the price comovement of US residential real estate markets. Real Estate Economics, 42(1), 71–108. https://doi.org/10.1111/1540-6229.12022
   Web of Science ®Google Scholar
• Klyuev, V. (2008). What goes up must come down? House price dynamics in the United States. IMF Working Papers (08/187). https://doi.org/10.5089/9781451870459.001
   Google Scholar
• Leamer, E. E. (2007). “Housing Is the Business Cycle,” Proceedings – Economic Policy Symposium (pp. 149–233) – Jackson Hole, Federal Reserve Bank of Kansas City.
   Google Scholar
• Leamer, E. E. (2015). Housing really is the business cycle: What survives the lessons of 2008–09? Journal of Money, Credit and Banking, 47(S1), 43–50. https://doi.org/10.1111/jmcb.12189
   Web of Science ®Google Scholar
• LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC.
   Google Scholar
• Liow, K. H., & Ye, Q. (2017). Switching regime beta analysis of global financial crisis: Evidence from international public real estate markets. Journal of Real Estate Research, 39(1), 127–164. https://doi.org/10.1080/10835547.2017.12091462
   Web of Science ®Google Scholar
• Merikas, A., Merika, A., Laopodis, N., & Triantafyllou, A. (2012). House price comovements in the Eurozone economies. European Research Studies Journal, 15(1), 71–98. https://doi.org/10.35808/ersj/345
   Google Scholar
• Nneji, O., Brooks, C., & Ward, C. (2013). Intrinsic and rational speculative bubbles in the U.S. housing market: 1960-2011. Journal of Real Estate Research, 35(2), 121–152. https://doi.org/10.1080/10835547.2013.12091360
   Web of Science ®Google Scholar
• Oikarinen, E., Bourassa, S. C., Hoesli, M., & Engblom, J. (2018). U.S. metropolitan house price dynamics. Journal of Urban Economics, 105, 54–69. https://doi.org/10.1016/j.jue.2018.03.001
   Web of Science ®Google Scholar
• Osland, L. (2010). An application of spatial econometrics in relation to hedonic house price modeling. Journal of Real Estate Research, 32(3), 289–320. https://doi.org/10.1080/10835547.2010.12091282
   Web of Science ®Google Scholar
• Owyang, M. T., Piger, J., & Wall, H. J. (2013). Discordant city employment cycles. Regional Science and Urban Economics, 43(2), 367–384. https://doi.org/10.1016/j.regsciurbeco.2012.09.004
   Web of Science ®Google Scholar
• Owyang, M. T., Piger, J., Wall, H. J., & Wheeler, C. H. (2008). The economic performance of cities: A Markov-switching approach. Journal of Urban Economics, 64(3), 538–550. https://doi.org/10.1016/j.jue.2008.05.006
   Web of Science ®Google Scholar
• Phillips, P. C. B., & Sul, D. (2007). Transition modeling and econometric convergence tests. Econometrica, 75(6), 1771–1855. https://doi.org/10.1111/j.1468-0262.2007.00811.x
   Web of Science ®Google Scholar
• Prüser, J., & Schmidt, T. (2021). Regional composition of national house price cycles in the US. Regional Science and Urban Economics, 87, Article 103645. https://doi.org/10.1016/j.regsciurbeco.2021.103645
   Web of Science ®Google Scholar
• Saiz, A. (2010). The geographic determinants of housing supply. Quarterly Journal of Economics, 125(3), 1253–1296. https://doi.org/10.1162/qjec.2010.125.3.1253
   Web of Science ®Google Scholar
• Wong, S. K., Yiu, C. Y., & Chau, K. W. (2013). Trading volume-induced spatial autocorrelation in real estate prices. Journal of Real Estate Finance and Economics, 46, 596–608. https://doi.org/10.1007/s11146-012-9375-y
   Web of Science ®Google Scholar
• Zhu, B., Füss, R., & Rottke, N. B. (2013). Spatial linkages in returns and volatilities among US regional housing markets. Real Estate Economics, 41(1), 29–64. https://doi.org/10.1111/j.1540-6229.2012.00337.x
   Web of Science ®Google Scholar
• Zimmer, D. M. (2015). Analyzing comovements in housing prices using Vine Copulas. Economic Inquiry, 53(2), 1156–1169. https://doi.org/10.1111/ecin.12156
   Web of Science ®Google Scholar