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

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Author Info

  • Rangan Gupta

    (University of Pretoria)

  • Stephen M. Miller

    (University of Connecticut and University of Nevada, Las Vegas)

Abstract

We examine the time-series relationship between housing prices in eight Southern California metropolitan statistical areas (MSAs). First, we perform cointegration tests of the housing price indexes for the MSAs, finding seven cointegrating vectors. Thus, the evidence suggests that one common trend links the housing prices in these eight MSAs, a purchasing power parity finding for the housing 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 housing 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 housing prices in only two other MSAs (Los Angels and Oxnard) and housing 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 turning points in housing prices that occurred in 2006:Q4. Recursive forecasts, where the sample is updated each quarter, provide reasonably good forecasts of turning points.

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Bibliographic Info

Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2009-10.

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Length: 49 pages
Date of creation: Mar 2009
Date of revision: Dec 2009
Publication status: Published in Journal of Real Estate Finance and Economics, April 2012
Handle: RePEc:uct:uconnp:2009-10

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Postal: University of Connecticut 341 Mansfield Road, Unit 1063 Storrs, CT 06269-1063
Phone: (860) 486-4889
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Web page: http://www.econ.uconn.edu/
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Keywords: Housing prices; Forecasting;

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Cited by:
  1. 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 0916, University of Nevada, Las Vegas , Department of Economics.
  2. 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 200927, University of Pretoria, Department of Economics.
  3. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.

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