EconPapers    
Economics at your fingertips  
 

Forecasting Connecticut Home Sales in a BVAR Framework Using Coincident and Leading Indexes

Pami Dua and Stephen Miller

The Journal of Real Estate Finance and Economics, 1996, vol. 13, issue 3, 219-35

Abstract: We develop a Bayesian Vector Autoregressive Model (BVAR) to forecast home sales in Connecticut. In addition to home prices and mortgage interest rates, we also include measures of current and future economic conditions to see if these variables provide useful information with which to forecast Connecticut home sales. The best performing model incorporates recently developed coincident and leading employment indexes for Connecticut. These composite indexes perform markedly better than the inclusion of individual variables such as the unemployment rate or housing permits authorized. Copyright 1996 by Kluwer Academic Publishers

Date: 1996
References: Add references at CitEc
Citations: View citations in EconPapers (21)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jrefec:v:13:y:1996:i:3:p:219-35

Ordering information: This journal article can be ordered from
http://www.springer. ... ce/journal/11146/PS2

Access Statistics for this article

The Journal of Real Estate Finance and Economics is currently edited by Steven R. Grenadier, James B. Kau and C.F. Sirmans

More articles in The Journal of Real Estate Finance and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-22
Handle: RePEc:kap:jrefec:v:13:y:1996:i:3:p:219-35