IDEAS home Printed from https://ideas.repec.org/a/kap/jrefec/v44y2012i3p339-361.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Rangan Gupta & Stephen Miller, 2012. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 339-361, April.
  • Handle: RePEc:kap:jrefec:v:44:y:2012:i:3:p:339-361
    DOI: 10.1007/s11146-010-9234-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11146-010-9234-7
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Charles Himmelberg & Christopher Mayer & Todd Sinai, 2005. "Assessing High House Prices: Bubbles, Fundamentals and Misperceptions," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 67-92, Fall.
    2. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
    3. 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.
    4. MacKinnon, James G & Haug, Alfred A & Michelis, Leo, 1999. "Numerical Distribution Functions of Likelihood Ratio Tests for Cointegration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 563-577, Sept.-Oct.
    5. Rangan Gupta & Stephen Miller, 2012. "“Ripple effects” and forecasting home prices in Los Angeles, Las Vegas, and Phoenix," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 48(3), pages 763-782, June.
    6. 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, September.
    7. Clapp, John M. & Tirtiroglu, Dogan, 1994. "Positive feedback trading and diffusion of asset price changes: Evidence from housing transactions," Journal of Economic Behavior & Organization, Elsevier, vol. 24(3), pages 337-355, August.
    8. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    9. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    10. Stiglitz, Joseph E, 1990. "Symposium on Bubbles," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 13-18, Spring.
    11. 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.
    12. Tirtiroglu, Dogan, 1992. "Efficiency in housing markets: Temporal and spatial dimensions," Journal of Housing Economics, Elsevier, vol. 2(3), pages 276-292, September.
    13. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    14. Steven Cook, 2005. "Detecting long-run relationships in regional house prices in the UK," International Review of Applied Economics, Taylor & Francis Journals, vol. 19(1), pages 107-118.
    15. 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.
    16. 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.
    17. David A. Dickey & Dennis W. Jansen & Daniel L. Thornton, 1991. "A primer on cointegration with an application to money and income," Review, Federal Reserve Bank of St. Louis, issue Mar, pages 58-78.
    18. 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.
    19. Jonathan McCarthy & Richard Peach, 2004. "Are home prices the next "bubble"?," Economic Policy Review, Federal Reserve Bank of New York, issue Dec, pages 1-17.
    20. 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.
    21. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    22. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    23. Todd H. Kuethe & Valerien Pede, 2009. "Regional Housing Price Cycles: A Spatio-Temporal Analysis Using Us State Level," Working Papers 09-04, Purdue University, College of Agriculture, Department of Agricultural Economics.
    24. Dua, Pami & Miller, Stephen M, 1996. "Forecasting Connecticut Home Sales in a BVAR Framework Using Coincident and Leading Indexes," The Journal of Real Estate Finance and Economics, Springer, vol. 13(3), pages 219-235, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Montagnoli, Alberto & Nagayasu, Jun, 2015. "UK house price convergence clubs and spillovers," Journal of Housing Economics, Elsevier, vol. 30(C), pages 50-58.
    2. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Floros, Christos, 2015. "Dynamic Connectedness of UK Regional Property Prices," MPRA Paper 68421, University Library of Munich, Germany.
    3. Rangan Gupta & Christophe André & Luis Gil-Alana, 2015. "Comovement in Euro area housing prices: A fractional cointegration approach," Urban Studies, Urban Studies Journal Limited, vol. 52(16), pages 3123-3143, December.
    4. Li, Yuming, 2015. "The asymmetric house price dynamics: Evidence from the California market," Regional Science and Urban Economics, Elsevier, vol. 52(C), pages 1-12.
    5. Geoffrey M. Ngene & Daniel P. Sohn & M. Kabir Hassan, 2017. "Time-Varying and Spatial Herding Behavior in the US Housing Market: Evidence from Direct Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 54(4), pages 482-514, May.
    6. 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.
    7. Gupta, Rangan & Kabundi, Alain & Miller, Stephen M., 2011. "Forecasting the US real house price index: Structural and non-structural models with and without fundamentals," Economic Modelling, Elsevier, vol. 28(4), pages 2013-2021, July.
    8. 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.
    9. Marcelo M. de Oliveira & Alexandre C. L. Almeida, 2014. "Testing for rational speculative bubbles in the Brazilian residential real-estate market," Papers 1401.7615, arXiv.org.
    10. Nicholas Apergis & Beatrice D. Simo-Kengne & Rangan Gupta, 2015. "Convergence In Provincial-Level South African House Prices: Evidence From The Club Convergence And Clustering Procedure," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 27(1), pages 2-17, March.
    11. Carlos Pestana BARROS & Zhongfei CHEN & Luis A. GIL-ALANA, 2013. "Long Memory in the Housing Price Indices in China," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 3(7), pages 785-807, July.
    12. 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.
    13. I-Chun Tsai, 2015. "Spillover Effect between the Regional and the National Housing Markets in the UK," Regional Studies, Taylor & Francis Journals, vol. 49(12), pages 1957-1976, December.
    14. Yang Hu & Les Oxley, 2016. "Bubbles in US Regional House Prices: Evidence from House Price/Income Ratios at the State Level," Working Papers in Economics 16/06, University of Waikato.
    15. Valadkhani, Abbas & Costello, Greg & Ratti, Ronald, 2016. "House price cycles in Australia’s four largest capital cities," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 11-22.
    16. 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).
    17. Nissan, Edward & Payne, James E., 2013. "A Simple Test of σ-Convergence in U.S. Housing Prices across BEA Regions," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 43(2).
    18. Francisca Richter & Youngme Seo, 2011. "Inter-regional home price dynamics through the foreclosure crisis," Working Paper 1119, Federal Reserve Bank of Cleveland.

    More about this item

    Keywords

    House prices; Cointegration; Temporal causality; Forecasting;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:jrefec:v:44:y:2012:i:3:p:339-361. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: http://www.springer.com .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.