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Using Large Data Sets to Forecast Housing Prices: A Case Study of Twenty US States

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Author Info
Rangan Gupta (University of Pretoria)
Alain Kabundi (University of Johannesburg)
Stephen M. Miller (University of Connecticut and University of Nevada, Las Vegas)

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Abstract

We implement several Bayesian and classical models to forecast housing prices in 20 US states. In addition to standard vector-autoregressive (VAR) and Bayesian vector autoregressive (BVAR) models, we also include the information content of 308 additional quarterly series in some models. Several approaches exist for incorporating information from a large number of series. We consider two approaches -- extracting common factors (principle components) in a Factor-Augmented Vector Autoregressive (FAVAR) or Factor-Augmented Bayesian Vector Autoregressive (FABVAR) models or Bayesian shrinkage in a large-scale Bayesian Vector Autoregressive (LBVAR) models. In addition, we also introduce spatial or causality priors to augment the forecasting models. Using the period of 1976:Q1 to 1994:Q4 as the in-sample period and 1995:Q1 to 2003:Q4 as the out-of-sample horizon, we compare the forecast performance of the alternative models. Based on the average root mean squared error (RMSE) for the one-, two-, three-, and four--quarters-ahead forecasts, we find that one of the factor-augmented models generally outperform the large-scale models in the 20 US states examined in this paper.

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Publisher Info
Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2009-13.

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Length: 34 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:uct:uconnp:2009-13

Note: We acknowledge the assistance of D. Liu and D. W. Jansen, who provided the data on the 308 macroeconomic indicators, as well as for clarifying all the data related issues.
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Postal: University of Connecticut 341 Mansfield Road, Unit 1063 Storrs, CT 06269-1063
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Web page: http://www.econ.uconn.edu/
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Related research
Keywords: Housing prices; Forecasting; Factor Augmented Models; Large-Scale BVAR models;

Other versions of this item:

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
R31 - Urban, Rural, and Regional Economics - - Production Analysis and Firm Location - - - Housing Supply and Markets

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  1. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall. [Downloadable!]
  2. Rangan Gupta & Alain Kabundi, 2008. "Forecasting Macroeconomic Variables in a Small Open Economy: A Comparison between Small- and Large-Scale Models," Working Papers 200830, University of Pretoria, Department of Economics.
  3. Rangan Gupta & Stephen M. Miller, 2009. "The Time-Series Properties on Housing Prices: A Case Study of the Southern California Market," Working Papers 0912, University of Nevada, Las Vegas , Department of Economics. [Downloadable!]
    Other versions:
  4. Rangan Gupta & Alain Kabundi, 2008. "Forecasting Macroeconomic Variables Using Large Datasets: Dynamic Factor Model versus Large-Scale BVARs," Working Papers 200816, University of Pretoria, Department of Economics. [Downloadable!]
  5. Matteo Iacoviello & Stefano Neri, 2007. "Housing Market Spillovers: Evidence from an Estimated DSGE Model," Boston College Working Papers in Economics 659, Boston College Department of Economics, revised 23 Oct 2009. [Downloadable!]
    Other versions:
  6. Sonali Das & Rangan Gupta & Alain Kabundi, 2009. "The Blessing Of Dimensionality In Forecasting Real House Price Growth In The Nine Census Divisions Of The Us," Working Papers 200902, University of Pretoria, Department of Economics.
  7. Tirtiroglu, Dogan, 1992. "Efficiency in housing markets: Temporal and spatial dimensions," Journal of Housing Economics, Elsevier, vol. 2(3), pages 276-292, September. [Downloadable!] (restricted)
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  9. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December. [Downloadable!] (restricted)
  10. Dua, Pami & Miller, Stephen M & Smyth, David J, 1999. "Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework," The Journal of Real Estate Finance and Economics, Springer, vol. 18(2), pages 191-205, March. [Downloadable!] (restricted)
  11. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September. [Downloadable!] (restricted)
    Other versions:
  12. Meen, Geoffrey, 2002. "The Time-Series Behavior of House Prices: A Transatlantic Divide?," Journal of Housing Economics, Elsevier, vol. 11(1), pages 1-23, March. [Downloadable!] (restricted)
  13. 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. [Downloadable!] (restricted)
  14. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October. [Downloadable!] (restricted)
    Other versions:
  15. 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. [Downloadable!] (restricted)
    Other versions:
  16. Bernanke, Ben & Gertler, Mark, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Working Papers 95-15, C.V. Starr Center for Applied Economics, New York University. [Downloadable!]
    Other versions:
  17. 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 219-35, November.
  18. David E. Rapach & Jack K. Strauss, 2007. "Forecasting real housing price growth in the Eighth District states," Regional Economic Development, Federal Reserve Bank of St. Louis, issue Nov, pages 33-42. [Downloadable!]
  19. Topel, Robert H & Rosen, Sherwin, 1988. "Housing Investment in the United States," Journal of Political Economy, University of Chicago Press, vol. 96(4), pages 718-40, August. [Downloadable!] (restricted)
  20. 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. [Downloadable!] (restricted)
    Other versions:
  21. James H. Stock & Mark W. Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    Other versions:
  22. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  23. 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. [Downloadable!] (restricted)
    Other versions:
  24. Sonali Das & Rangan Gupta & Alain Kabundi, 2008. "Could We Have Predicted The Recent Downturn In The South African Housing Market?," Working Papers 200831, University of Pretoria, Department of Economics.
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This page was last updated on 2009-11-24.

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