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Predicting Downturns in the US Housing Market: A Bayesian Approach

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  • Rangan Gupta

    ()
    (Department of Economics, University of Pretoria)

  • Sonali Das

    ()
    (LQM, CSIR, Pretoria)

Abstract

This paper estimates Bayesian Vector Autoregressive (BVAR) models, both spatial and non-spatial (univariate and multivariate), for the twenty largest states of the US economy, using quarterly data over the period 1976:Q1 to 1994:Q4; and then forecasts one-to-four quarters ahead real house price growth over the out-of-sample horizon of 1995:Q1 to 2006:Q4. The forecasts are then evaluated by comparing them with the ones generated from an unrestricted classical Vector Autoregressive (VAR) model and the corresponding univariate variant the same. Finally, the models that produce the minimum average Root Mean Square Errors (RMSEs), are used to predict the downturns in the real house price growth over the recent period of 2007:Q1 to 2008:Q1. The results show that the BVARs, in whatever form they might be, are the best performing models in 19 of the 20 states. Moreover, these models do a fair job in predicting the downturn in 18 of the 19 states, however, they always under-predict the size of the decline in the real house price growth rate – an indication of the need to incorporate the role of fundamentals in the models.

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Bibliographic Info

Paper provided by University of Pretoria, Department of Economics in its series Working Papers with number 200821.

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Length: 21 pages
Date of creation: Jun 2008
Date of revision:
Handle: RePEc:pre:wpaper:200821

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Keywords: BVAR Model; BVAR Forecasts; Forecast Accuracy; SBVAR Model; SBVAR Forecasts; VAR Model; VAR Forecasts;

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References

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  1. Guangling (dave Liu & Rangan Gupta, 2007. "A Small-Scale Dsge Model For Forecasting The South African Economy," South African Journal of Economics, Economic Society of South Africa, vol. 75(2), pages 179-193, 06.
  2. Samuel Zita & Rangan Gupta, 2007. "Modelling and Forecasting the Metical-Rand Exchange Rate," Working Papers 200702, University of Pretoria, Department of Economics.
  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. 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.
  5. Guangling 'Dave' Liu & Rangan Gupta & Eric Schaling, 2009. "A New-Keynesian DSGE model for forecasting the South African economy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 387-404.
  6. Anirvan Banerji & Pami Dua & Stephen M. Miller, 2003. "Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models," Working papers 114, Centre for Development Economics, Delhi School of Economics.
  7. Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
  8. Guangling ‘Dave’ Liu & Rangan Gupta & Eric Schaling, 2007. "Forecasting the South African Economy: A DSGE-VAR Approach," Working Papers 51, Economic Research Southern Africa.
  9. Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  10. Anatoli Kuprianov & William Lupoletti, 1984. "The economic outlook for the Fifth District states in 1984 : forecasts from vector autoregression models," Economic Review, Federal Reserve Bank of Richmond, issue Jan, pages 12-23.
  11. Rangan Gupta, 2007. "FORECASTING THE SOUTH AFRICAN ECONOMY WITH GIBBS SAMPLED BVECMs," South African Journal of Economics, Economic Society of South Africa, vol. 75(4), pages 631-643, December.
  12. 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.
  13. Rangan Gupta & Sonali Das, 2008. "Spatial Bayesian Methods of Forecasting House Prices in Six Metropolitan Areas of South Africa," Working Papers 200813, University of Pretoria, Department of Economics.
  14. Rangan Gupta & Moses M. Sichei, 2006. "A BVAR Model for the South African Economy," Working Papers 200612, University of Pretoria, Department of Economics.
  15. Hossain Amirizadeh & Richard M. Todd, 1984. "More growth ahead for Ninth District states," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
  16. Rangan Gupta & Alain Kabundi, 2008. "A Dynamic Factor Model for Forecasting Macroeconomic Variables in South Africa," Working Papers 200815, University of Pretoria, Department of Economics.
  17. William C. Gruben & Donald W. Hayes, 1991. "Forecasting the Louisiana economy," Economic and Financial Policy Review, Federal Reserve Bank of Dallas, issue Mar, pages 1-16.
  18. Marco Del Negro, 2001. "Turn, turn, turn: Predicting turning points in economic activity," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 1-12.
  19. Rangan Gupta, 2009. "Bayesian Methods Of Forecasting Inventory Investment," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 113-126, 03.
  20. 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.
  21. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
  22. 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.
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Citations

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Cited by:
  1. 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 2009-42, University of Connecticut, Department of Economics.
  2. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 1209, University of Nevada, Las Vegas , Department of Economics.
  3. Zietz, Joachim & Traian, Anca, 2014. "When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(2), pages 271-281.
  4. Plakandaras, Vasilios & Gupta, Rangan & Papadimitriou, Theophilos & Gogas, Periklis, 2014. "Forecasting the U.S. Real House Price Index," DUTH Research Papers in Economics 10-2014, Democritus University of Thrace, Department of Economics.
  5. Huang, MeiChi, 2014. "Bubble-like housing boom–bust cycles: Evidence from the predictive power of households’ expectations," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 2-16.
  6. Natalia Bailey & Sean Holly & N. Hashem Pesaran, 2013. "A Two Stage Approach to Spatiotemporal Analysis with Strong and weak cross Sectional Dependence," Cambridge Working Papers in Economics 1362, Faculty of Economics, University of Cambridge.
  7. 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.
  8. Mirriam Chitalu Chama-Chiliba & Rangan Gupta & Nonophile Nkambule & Naomi Tlotlego, 2011. "Forecasting Key Macroeconomic Variables of the South African Economy Using Bayesian Variable Selection," Working Papers 201132, University of Pretoria, Department of Economics.
  9. Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, vol. 28(3), pages 891-899, May.

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