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Page Contents 1 of 2 Print “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.email@example.com Abstract: We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and CPMs Sessions 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. T Page Contents 2 of 2 Print 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. CPMs Sessions T
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