DSpace
 

Researchspace >
General science, engineering & technology >
General science, engineering & technology >
General science, engineering & technology >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/5047

Title: Could we have predicted the recent downturn in home sales of the four US census regions?
Authors: Gupta, R
Tipoy, CK
Das, S
Keywords: Forecast accuracy
Home sales
Vector autoregressive models
Bayesian versions
US census regions
Housing predictions
Issue Date: 2010
Publisher: American Real Estate Society
Citation: Gupta, R, Tipoy, CK, and Das, S. 2010. Could we have predicted the recent downturn in home sales of the four US census regions? Journal of Housing Research, Vol.19(2), pp 111-128
Series/Report no.: Workflow request;4881
Abstract: This paper analyzes the ability of a random walk and, classical and Bayesian versions of autoregressive, vector autoregressive and vector error correction models in forecasting home sales for the four US census regions (Northeast, Midwest, South, West), using quarterly data over the period of 2001:Q1 to 2004:Q3, based on an in-sample of 1976:Q1 till 2000:Q4. In addition, the authors also use their models to predict the downturn in the home sales of the four census regions over the period of 2004:Q4 to 2009:Q2, given that the home sales in all the four census regions peaked in 2005:Q3. Based on their analysis, they draw the following conclusions: (i) Barring the South, there always exists a Bayesian model which tends to outperform all other models in forecasting home sales over the out-of-sample horizon; (ii) When they expose their classical and ‘optimal’ Bayesian forecast models to predicting the peaks and declines in home sales, they find that barring the South again, their models did reasonably well in predicting the turning point exactly at 2005:Q3 or with a lead. In general, the fact that different models produce the best forecasting performance for different regions highlights the fact that economic conditions prevailing at the start of the out-of-sample horizon are not necessarily the same across the regions, and, hence, vindicates their decision to look at regions rather than the economy as a whole. In addition, they also point out that there is no guarantee that the best performing model over the out-of-sample horizon is also well-suited in predicting the downturn in home sales.
Description: Copyright: 2010 American Real Estate Society. This is the post print version of the work. The definitive version is published in the Journal of Housing Research, Vol. 19(2)
URI: http://hdl.handle.net/10204/5047
ISSN: 1052-7001
Appears in Collections:Building science and technology
Environmental and resource economics
Logistics and quantitative methods
General science, engineering & technology
General research interest

Files in This Item:

File Description SizeFormat
Das3_2010.pdf679.51 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback