IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

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

  • Rangan Gupta

    ()

    (Department of Economics, University of Pretoria)

  • Alan Kabundi

    ()

    (Department of Economics and Econometrics, University of Johannesburg)

  • Stephen M. Miller

    ()

    (Department of Economics, 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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://web.unlv.edu/projects/RePEc/pdf/1001.pdf
File Function: First version, 2010
Download Restriction: no

Paper provided by University of Nevada, Las Vegas , Department of Economics in its series Working Papers with number 1001.

as
in new window

Length: 36 pages
Date of creation: Dec 2010
Date of revision:
Handle: RePEc:nlv:wpaper:1001
Contact details of provider: Phone: (702) 895-3776
Fax: (702) 895-1354
Web page: http://business.unlv.edu/econ/
More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. 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.
  2. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
  3. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank, Research Centre.
  4. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
  5. 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.
  6. Matteo Iacoviello & Stefano Neri, 2008. "Housing market spillovers: Evidence from an estimated DSGE model," Temi di discussione (Economic working papers) 659, Bank of Italy, Economic Research and International Relations Area.
  7. Chamberlain, Gary & Rothschild, Michael, 1983. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Econometrica, Econometric Society, vol. 51(5), pages 1281-304, September.
  8. 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.
  9. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  10. Marc Hallin & Mario Forni & Marco Lippi & Lucrezia Reichlin, 2003. "Do financial variables help forecasting inflation and real activity in the Euro area ?," ULB Institutional Repository 2013/2123, ULB -- Universite Libre de Bruxelles.
  11. Rangan Gupta & Stephen M. Miller, 2009. "“Ripple Effects” and Forecasting Home Prices In Los Angeles, Las Vegas, and Phoenix," Working Papers 200901, University of Pretoria, Department of Economics.
  12. Domenico Giannone & Troy Matheson, 2006. "A new core inflation indicator for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2006/02, Reserve Bank of New Zealand.
  13. Chris Bloor & Troy Matheson, 2010. "Analysing shock transmission in a data-rich environment: a large BVAR for New Zealand," Empirical Economics, Springer, vol. 39(2), pages 537-558, October.
  14. 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.
  15. 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.
  16. 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.
  17. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
  18. Domenico Giannone & Martha Banbura & Lucrezia Reichlin, 2008. "Bayesian VARs with large panels," ULB Institutional Repository 2013/13388, ULB -- Universite Libre de Bruxelles.
  19. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  20. 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.
  21. 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.
  22. John M. Quigley, 1999. "Real Estate Prices and Economic Cycles," International Real Estate Review, Asian Real Estate Society, vol. 2(1), pages 1-20.
  23. Wang, Mu-Chun, 2008. "Comparing the DSGE model with the factor model: an out-of-sample forecasting experiment," Discussion Paper Series 1: Economic Studies 2008,04, Deutsche Bundesbank, Research Centre.
  24. 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.
  25. 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).
  26. 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.
  27. Alain N. Kabundi, 2004. "Estimation of Economic Growth in France Using Business Survey Data," IMF Working Papers 04/69, International Monetary Fund.
  28. 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.
  29. 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.
  30. 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.
  31. Sonali Das & Rangan Gupta & Alain Kabundi, 2009. "Could we have predicted the recent downturn in the South African Housing Market?," Working Papers 149, Economic Research Southern Africa.
  32. 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.
  33. Anindya Banerjee & Massimiliano Marcellino & Igor Masten, 2003. "Leading Indicators for Euro-area Inflation and GDP Growth," Working Papers 235, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  34. Clark, Todd E. & McCracken, Michael W., 2001. "Tests of equal forecast accuracy and encompassing for nested models," Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
  35. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
  36. 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.
  37. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  38. Robert Barsky & Christopher L. House & Miles Kimball, 2005. "Sticky Price Models and Durable Goods," Macroeconomics 0501031, EconWPA.
  39. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  40. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
  41. 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.
  42. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  43. James H. Stock & Mark W. Watson, 1999. "Forecasting Inflation," NBER Working Papers 7023, National Bureau of Economic Research, Inc.
  44. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May.
  45. 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.
  46. Spencer, David E., 1993. "Developing a Bayesian vector autoregression forecasting model," International Journal of Forecasting, Elsevier, vol. 9(3), pages 407-421, November.
  47. Angelini, Elena & Henry, Jérôme & Mestre, Ricardo, 2001. "Diffusion index-based inflation forecasts for the euro area," Working Paper Series 0061, European Central Bank.
  48. Boivin, Jean & Ng, Serena, 2005. "Understanding and Comparing Factor-Based Forecasts," MPRA Paper 836, University Library of Munich, Germany.
  49. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
  50. Marc-André Gosselin & Greg Tkacz, 2001. "Evaluating Factor Models: An Application to Forecasting Inflation in Canada," Working Papers 01-18, Bank of Canada.
  51. Rangan Gupta & Sonali Das, 2008. "Predicting Downturns in the US Housing Market: A Bayesian Approach," Working Papers 200821, University of Pretoria, Department of Economics.
  52. 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.
  53. Thomas Hyclak & Geraint Johnes, 1999. "original: House prices and regional labor markets," The Annals of Regional Science, Springer, vol. 33(1), pages 33-49.
  54. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
  55. 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.
  56. Rangan Gupta & Moses M. Sichei, 2006. "A BVAR Model for the South African Economy," Working Papers 200612, University of Pretoria, Department of Economics.
  57. 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.
  58. Chamberlain, Gary, 1983. "Funds, Factors, and Diversification in Arbitrage Pricing Models," Econometrica, Econometric Society, vol. 51(5), pages 1305-23, September.
  59. Geraint Johnes & Thomas Hyclak, . "House Prices and Regional Labor Markets," Working Papers ec15/93, Department of Economics, University of Lancaster.
  60. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  61. Rangan Gupta & Alain Kabundi, 2009. "Forecasting Real Us House Price: Principal Components Versus Bayesian Regressions," Working Papers 200907, University of Pretoria, Department of Economics.
  62. 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.
  63. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nlv:wpaper:1001. 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: (Bill Robinson)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.