TECHNICAL PAPERS
Jul 16, 2011

Trends and Prospects of the U.S. Housing Market Using the Markov Switching Model

Publication: Journal of Urban Planning and Development
Volume 138, Issue 1

Abstract

Accurate projection of the economic conditions in a country can enable the government to establish appropriate policies in a timely manner. This also applies to enterprises and individuals in terms of decision-making processes, such as investing and production planning and household consumption and saving. The U.S. housing market is no exception to this practice. The prompt and accurate assessment of the trends in the U.S. housing market enables consumers to make quick decisions and to come up with the corresponding measures, thus minimizing risks associated with market uncertainty. The monthly indices of the U.S. housing market indicators are released at the end of the following month, creating a month-long standstill in making a judgment regarding the housing market. Consequently, it is not possible to predict the current month’s market status. Therefore, in this study, various “U.S. housing market-related” indicators were calculated as average month-to-month changes using the composite index methodology of the National Bureau of Economic Research (NBER). The trends in the U.S. housing market were analyzed using the Markov switching models: the Markov switching random walk (MS-RW) model and the Markov switching autoregressive (MS-AR) model. Results showed that the methods can accurately determine the trends in the U.S. housing market. Findings from the forecasting performance test made it possible to predict or forecast the prospects of the U.S. housing market within the month-long standstill period.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (UNSPECIFIED2010-00027246).

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Go to Journal of Urban Planning and Development
Journal of Urban Planning and Development
Volume 138Issue 1March 2012
Pages: 10 - 17

History

Received: Jul 23, 2010
Accepted: Jul 15, 2011
Published online: Jul 16, 2011
Published in print: Mar 1, 2012

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Authors

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JaeHyun Park [email protected]
Junior Researcher, Construction Information Technology Institute, Doalltech Co., Ltd., Seoul, Korea. E-mail: [email protected]
TaeHoon Hong, A.M.ASCE [email protected]
Assistant Professor, Dept. of Architectural Engineering, Yonsei Univ., Seoul, Korea (corresponding author). E-mail: [email protected]

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