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Forecasting Connecticut home sales in a BVAR framework using coincident and leading indexes

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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.

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Dua, P., Miller, S.M. Forecasting Connecticut home sales in a BVAR framework using coincident and leading indexes. J Real Estate Finan Econ 13, 219–235 (1996). https://doi.org/10.1007/BF00217392

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