Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework
This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.
|Date of creation:||Nov 1996|
|Publication status:||Published in Journal of Real Estate Finance and Economics, March 1999|
|Contact details of provider:|| Postal: University of Connecticut 365 Fairfield Way, Unit 1063 Storrs, CT 06269-1063|
Phone: (860) 486-4889
Fax: (860) 486-4463
Web page: http://www.econ.uconn.edu/
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.:
- Richard M. Todd, 1984. "Improving economic forecasting with Bayesian vector autoregression," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
- Sims, Christopher A., 1988.
"Bayesian skepticism on unit root econometrics,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 12(2-3), pages 463-474.
- Christopher A. Sims, 1988. "Bayesian skepticism on unit root econometrics," Discussion Paper / Institute for Empirical Macroeconomics 3, Federal Reserve Bank of Minneapolis.
- Robert B. Litterman, 1984. "Above-average national growth in 1985 and 1986," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Fall.
- ZELLNER, Arnold & PALM, Franz, "undated".
"Time series analysis and simultaneous equation econometric models,"
CORE Discussion Papers RP
173, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
- Arnott, Richard, 1987. "Economic theory and housing," Handbook of Regional and Urban Economics, in: E. S. Mills (ed.), Handbook of Regional and Urban Economics, edition 1, volume 2, chapter 24, pages 959-988 Elsevier.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
- Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
- Litterman, Robert B, 1986.
"Forecasting with Bayesian Vector Autoregressions-Five Years of Experience,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 4(1), pages 25-38, January.
- Robert B. Litterman, 1985. "Forecasting with Bayesian vector autoregressions five years of experience," Working Papers 274, Federal Reserve Bank of Minneapolis.
- Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
- 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 219-235, November.
- Isaac F. Megbolugbe & Allen P. Marks & Mary B. Schwartz, 1991. "The Economic Theory of Housing Demand: A Critical Review," Journal of Real Estate Research, American Real Estate Society, vol. 6(3), pages 381-393.