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Forecasting Connecticut home sales in a BVAR framework using coincident and leading indexes
Authors:Pami Dua  Stephen M. Miller
Affiliation:(1) Department of Economics, University of Connecticut, 06903-2899 Stamford, CT, USA;(2) Centre for Development Economics, Delhi School of Economics, 11007, Delhi, India;(3) Department of Economics, University of Connecticut, 06269-1063 Storrs, CT, USA
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.
Keywords:Connecticut home sales  forecasting  coincident index  leading index  BVAR
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