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

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Author Info

  • Dua, Pami
  • Miller, Stephen M

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

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Bibliographic Info

Article provided by Springer in its journal Journal of Real Estate Finance & Economics.

Volume (Year): 13 (1996)
Issue (Month): 3 (November)
Pages: 219-35

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Handle: RePEc:kap:jrefec:v:13:y:1996:i:3:p:219-35

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Web page: http://www.springerlink.com/link.asp?id=102945

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Cited by:
  1. Pami Dua & Stephen Miller, 1995. "Forecasting and Analyzing Economic Activity with Coincident and Leading Indexes: The Case of Connecticut," Working papers 1995-05, University of Connecticut, Department of Economics.
  2. 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.
  3. Sonali Das & Rangan Gupta & Alain Kabundi, 2008. "Could We Have Predicted The Recent Downturn In The South African Housing Market?," Working Papers 200831, University of Pretoria, Department of Economics.
  4. Hong Chen, 2010. "Using Financial and Macroeconomic Indicators to Forecast Sales of Large Development and Construction Firms," The Journal of Real Estate Finance and Economics, Springer, vol. 40(3), pages 310-331, April.
  5. 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.
  6. 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 2009-13, University of Connecticut, Department of Economics.
  7. Pami Dua, 2008. "Interest Rate Modeling and Forecasting in India," Working Papers id:1521, eSocialSciences.
  8. Pami Dua & Stephen M. Miller & David J. Smyth, 1996. "Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework," Working papers 1996-08, University of Connecticut, Department of Economics.

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