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Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals

  • Rangan Gupta

    (University of Pretoria)

  • Alain Kabundi

    (University of Johannesburgh)

  • Stephen M. Miller

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

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its turning point in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets -- extracting common factors (principle components) in a Factor-Augmented Vector Autoregressive or Factor-Augmented Bayesian Vector Autoregressive models or Bayesian shrinkage in a large-scale Bayesian Vector Autoregressive models. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). Finally, we use each model to forecast the turning point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a turning point with any accuracy, suggesting that attention to developing forward-looking microfounded dynamic stochastic general equilibrium models of the housing market, over and above fundamentals, proves crucial in forecasting turning points.

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Paper provided by University of Connecticut, Department of Economics in its series Working papers with number 2009-42.

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Length: 37 pages
Date of creation: Dec 2009
Date of revision:
Publication status: Published in Economic Modelling, July 2011
Handle: RePEc:uct:uconnp:2009-42
Note: We gratefully acknowledge Matteo Iacoviello and Stefano Neri for many helpful comments. All remaining errors are ours.
Contact details of provider: Postal: University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063
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Web page: http://www.econ.uconn.edu/

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  1. 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.
  2. Gupta, Rangan & Kabundi, Alain, 2011. "A large factor model for forecasting macroeconomic variables in South Africa," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1076-1088, October.
  3. Rangan Gupta & Stephen M. Miller, 2009. "The Time-Series Properties of Housing Prices: A Case Study of the Southern California Market," Working Papers 200908, University of Pretoria, Department of Economics.
  4. 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.
  5. Geetesh Bhardwaj & Norman Swanson, 2004. "An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series," Departmental Working Papers 200422, Rutgers University, Department of Economics.
  6. Jean Boivin & Serena Ng, 2005. "Understanding and Comparing Factor-Based Forecasts," NBER Working Papers 11285, National Bureau of Economic Research, Inc.
  7. Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
  8. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: Is Bayesian regression a valid alternative to principal components?," Working Paper Series 0700, European Central Bank.
  9. 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 200912, University of Pretoria, Department of Economics.
  10. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  11. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2003. "Do financial variables help forecasting inflation and real activity in the euro area?," Journal of Monetary Economics, Elsevier, vol. 50(6), pages 1243-1255, September.
  12. John M. Quigley, 1999. "Real Estate Prices and Economic Cycles," International Real Estate Review, Asian Real Estate Society, vol. 2(1), pages 1-20.
  13. Gary Chamberlain & Michael Rothschild, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," NBER Working Papers 0996, National Bureau of Economic Research, Inc.
  14. Riccardo Cristadoro & Mario Forni & Lucrezia Reichlin & Giovanni Veronese, 2005. "A core inflation indicator for the Euro area," ULB Institutional Repository 2013/10131, ULB -- Universite Libre de Bruxelles.
  15. Chris Bloor & Troy Matheson, 2008. "Analysing shock transmission in a data-rich environment: A large BVAR for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2008/09, Reserve Bank of New Zealand.
  16. Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
  17. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  18. Das, Sonali & Gupta, Rangan & Kabundi, Alain, 2009. "Could we have predicted the recent downturn in the South African housing market?," Journal of Housing Economics, Elsevier, vol. 18(4), pages 325-335, December.
  19. Matteo Iacoviello & Stefano Neri, 2010. "Housing Market Spillovers: Evidence from an Estimated DSGE Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 125-64, April.
  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.
  21. 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.
  22. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  23. Rangan Gupta & Stephen M. Miller, 2009. ""Ripple Effects" and Forecasting Home Prices in Los Angeles, Las Vegas, and Phoenix," Working papers 2009-05, University of Connecticut, Department of Economics, revised Jun 2009.
  24. James H. Stock & Mark W. Watson, 2001. "Forecasting output and inflation: the role of asset prices," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
  25. Lucrezia Reichlin & Mario Forni & Marc Hallin & Marco Lippi, 2001. "Coincident and leading indicators for the Euro area," ULB Institutional Repository 2013/10137, ULB -- Universite Libre de Bruxelles.
  26. 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.
  27. 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.
  28. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
  29. George Kapetanios & Massimiliano Marcellino, 2009. "A parametric estimation method for dynamic factor models of large dimensions," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(2), pages 208-238, 03.
  30. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
  31. Rangan Gupta & Stephen M. Miller, 2009. "The Time-Series Properties of House Prices: A Case Study of the Southern California Market," Working Papers 0912, University of Nevada, Las Vegas , Department of Economics, revised Dec 2009.
  32. Rangan Gupta & Sonali Das, 2008. "Predicting Downturns in the US Housing Market: A Bayesian Approach," Working Papers 200821, University of Pretoria, Department of Economics.
  33. Sonali Das & Rangan Gupta & Alain Kabundi, 2011. "Forecasting regional house price inflation: a comparison between dynamic factor models and vector autoregressive models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(2), pages 288-302, March.
  34. Boivin, Jean & Giannoni, Marc P. & Mihov, Ilian, 2006. "Sticky prices and monetary policy: Evidence from disaggregated US data," CFS Working Paper Series 2007/14, Center for Financial Studies (CFS).
  35. Bernanke, Ben S. & Boivin, Jean, 2003. "Monetary policy in a data-rich environment," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 525-546, April.
  36. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc.
  37. Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Working Papers 01-18, Bank of Canada.
  38. Mu-Chun Wang, 2009. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 167-182.
  39. Giannone, Domenico & Matheson, Troy, 2007. "A New Core Inflation Indicator for New Zealand," CEPR Discussion Papers 6469, C.E.P.R. Discussion Papers.
  40. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  41. Rangan Gupta & Alain Kabundi, 2009. "Forecasting Real Us House Price: Principal Components Versus Bayesian Regressions," Working Papers 200907, University of Pretoria, Department of Economics.
  42. Angelini, Elena & Henry, Jérôme & Mestre, Ricardo, 2001. "Diffusion index-based inflation forecasts for the euro area," Working Paper Series 0061, European Central Bank.
  43. Rangan Gupta & Moses M. Sichei, 2006. "A BVAR Model for the South African Economy," Working Papers 200612, University of Pretoria, Department of Economics.
  44. Geraint Johnes & Thomas Hyclak, . "House Prices and Regional Labor Markets," Working Papers ec15/93, Department of Economics, University of Lancaster.
  45. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
  46. Christian Schumacher & Christian Dreger, 2004. "Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 224(6), pages 731-750, November.
  47. Ben S. Bernanke & Mark Gertler, 1995. "Inside the Black Box: The Credit Channel of Monetary Policy Transmission," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 27-48, Fall.
  48. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2005. "Leading Indicators for Euro-area Inflation and GDP Growth," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 785-813, December.
  49. Robert Barsky & Christopher L. House & Miles Kimball, 2005. "Sticky Price Models and Durable Goods," Macroeconomics 0501031, EconWPA.
  50. Alain N. Kabundi, 2004. "Estimation of Economic Growth in France Using Business Survey Data," IMF Working Papers 04/69, International Monetary Fund.
  51. Chamberlain, Gary, 1983. "Funds, Factors, and Diversification in Arbitrage Pricing Models," Econometrica, Econometric Society, vol. 51(5), pages 1305-23, September.
  52. Thomas Hyclak & Geraint Johnes, 1999. "original: House prices and regional labor markets," The Annals of Regional Science, Springer, vol. 33(1), pages 33-49.
  53. Spencer, David E., 1993. "Developing a Bayesian vector autoregression forecasting model," International Journal of Forecasting, Elsevier, vol. 9(3), pages 407-421, November.
  54. Zellner, Arnold, 1986. "A tale of forecasting 1001 series : The Bayesian knight strikes again," International Journal of Forecasting, Elsevier, vol. 2(4), pages 491-494.
  55. 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.
  56. 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.
  57. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre.
  58. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  59. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  60. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods Of Forecasting House Prices In Six Metropolitan Areas Of South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 76(2), pages 298-313, 06.
  61. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  62. 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.
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