Journal
INTERNATIONAL JOURNAL OF FORECASTING
Volume 25, Issue 2, Pages 351-372Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ijforecast.2009.01.009
Keywords
Real housing price growth; Autoregressive distributed lag model; Combination forecasts; Mean square forecast error; Coastal/interior US states
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Given the marked differences in housing price growth across US regions since the mid-1990s, we investigate forecasts of state-level real housing price growth for 1995-2006. We evaluate forecasts from an autoregressive benchmark model as well as models based on a host of state, regional, and national economic variables. Overall, our results highlight important differences in the forecastability of real housing price growth across US states, especially between interior and coastal states. More specifically, we find that autoregressive models, and especially models that incorporate information from numerous economic variables, often provide. relatively accurate housing price forecasts for a number of interior states during the period 1995-2006; all forecasting models, however, tend to perform relatively poorly for a group of primarily coastal states that experienced especially strong housing price growth during this period, pointing to a disconnect between housing prices and economic fundamentals for these states. (C) 2009 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
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