“Ripple Effects” and Forecasting Home Prices in Los Angeles_ Las

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                                   “Ripple Effects” and Forecasting Home Prices
                                      in Los Angeles, Las Vegas, and Phoenix
               Rangan Gupta; Stephen M. Miller
               University of Pretoria.
               E-mail: Rangan.Gupta@up.ac.za; Stephen.miller@unlv.edu



               Abstract: We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and
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               Phoenix. First, temporal Granger causality tests reveal that Los Angeles housing prices cause housing prices
               in Las Vegas (directly) and Phoenix (indirectly). In addition, Las Vegas housing prices cause housing prices
               in Phoenix. Los Angeles housing prices prove exogenous in a temporal sense and Phoenix housing prices do
               not cause prices in the other two markets. Second, we calculate out-of-sample forecasts in each market, using
               various vector autoregessive (VAR) and vector error-correction (VEC) models, as well as Bayesian, spatial,
               and causality versions of these models with various priors. Different specifications provide superior forecasts
               in the different cities.




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               Finally, we consider the ability of theses time-series models to provide accurate out-of-sample predictions of
               turning points in housing prices that occurred in 2006:Q4. Recursive forecasts, where the sample is updated
               each quarter, provide reasonably good forecasts of turning points.


               Key words and phrases: C32, R31; Ripple effect, Housing prices, Forecasting.
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