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The Time-Series Properties of House Prices: A Case Study of the Southern California Market

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  • Rangan Gupta
  • Stephen Miller

    ()

Abstract

We examine the time-series relationship between house prices in eight Southern California metropolitan statistical areas (MSAs). First, we perform cointegration tests of the house price indexes for the MSAs, finding seven cointegrating vectors. Thus, the evidence suggests that one common trend links the house prices in these eight MSAs, a purchasing power parity finding for the house prices in Southern California. Second, we perform temporal Granger causality tests revealing intertwined temporal relationships. The Santa Anna MSA leads the pack in temporally causing house prices in six of the other seven MSAs, excluding only the San Luis Obispo MSA. The Oxnard MSA experienced the largest number of temporal effects from other MSAs, six of the seven, excluding only Los Angeles. The Santa Barbara MSA proved the most isolated in that it temporally caused house prices in only two other MSAs (Los Angeles and Oxnard) and house prices in the Santa Anna MSA temporally caused prices in Santa Barbara. Third, we calculate out-of-sample forecasts in each MSA, using various vector autoregressive (VAR) and vector error-correction (VEC) models, as well as Bayesian, spatial, and causality versions of these models with various priors. Different specifications provide superior forecasts in the different MSAs. Finally, we consider the ability of theses time-series models to provide accurate out-of-sample predictions of the decline in the house prices after their peaks in 2005 and 2006. Recursive forecasts, where the sample is updated each quarter, provide reasonably good forecasts of timing of the peak and decline if the house prices.

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File URL: http://hdl.handle.net/10.1007/s11146-010-9234-7
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Bibliographic Info

Article provided by Springer in its journal The Journal of Real Estate Finance and Economics.

Volume (Year): 44 (2012)
Issue (Month): 3 (April)
Pages: 339-361

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Handle: RePEc:kap:jrefec:v:44:y:2012:i:3:p:339-361

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Web page: http://www.springerlink.com/link.asp?id=102945

Related research

Keywords: House prices; Cointegration; Temporal causality; Forecasting;

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References

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  1. Rapach, David E. & Strauss, Jack K., 2009. "Differences in housing price forecastability across US states," International Journal of Forecasting, Elsevier, vol. 25(2), pages 351-372.
  2. Rangan Gupta & Moses m. Sichei, 2006. "A Bvar Model For The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 74(3), pages 391-409, 09.
  3. Karl E. Case & Robert J. Shiller, 2003. "Is There a Bubble in the Housing Market?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(2), pages 299-362.
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  6. Rangan Gupta, 2006. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH VARs AND VECMs," South African Journal of Economics, Economic Society of South Africa, vol. 74(4), pages 611-628, December.
  7. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer, vol. 48(3), pages 763-782, June.
  8. Mark J. Holmes & Arthur Grimes, 2005. "Is there long-run convergence of regional house prices in the UK?," Working Papers 05_11, Motu Economic and Public Policy Research.
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  10. Pami Dua & Stephen M. Miller & David J. Smyth, 1996. "Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework," Working papers 1996-08, University of Connecticut, Department of Economics.
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  17. Jonathan McCarthy & Richard W. Peach, 2004. "Are home prices the next "bubble"?," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 1-17.
  18. Stuart A. Gabriel & Joe P. Mattey & William L. Wascher, 1999. "House price differentials and dynamics: evidence from the Los Angeles and San Francisco metropolitan areas," Economic Review, Federal Reserve Bank of San Francisco, pages 3-22.
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Citations

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Cited by:
  1. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working papers 2009-42, University of Connecticut, Department of Economics.
  2. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta, 2013. "Convergence in Provincial-Level South African House Prices: Evidence from the Club Convergence and Clustering Procedure," Working Papers 201322, University of Pretoria, Department of Economics.
  3. Christophe Andre & Luis A. Gil-Alana & Rangan Gupta, 2013. "Comovement in Euro Area Housing Prices: A Fractional Cointegration Approach," Working Papers 201359, University of Pretoria, Department of Economics.
  4. Payne, James E., 2012. "The Long-Run Relationship among Regional Housing Prices: An Empirical Analysis of the U.S," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 42(1).
  5. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2010. "Unit Roots and Structural Change: An Application to US House-Price Indices," Working papers 2010-04, University of Connecticut, Department of Economics, revised Dec 2010.
  6. Francisca G-C Richter & Youngme Seo, 2011. "Inter-regional home price dynamics through the foreclosure crisis," Working Paper 1119, Federal Reserve Bank of Cleveland.
  7. Barros, Carlos Pestana & Gil-Alana, Luis A. & Payne, James E., 2012. "Comovements among U.S. state housing prices: Evidence from fractional cointegration," Economic Modelling, Elsevier, vol. 29(3), pages 936-942.
  8. Rangan Gupta & Alain Kabundi & Stephen M. Miller, 2009. "Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States," Working papers 2009-13, University of Connecticut, Department of Economics.
  9. repec:asi:ajoerj:2013:p:785-807 is not listed on IDEAS

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