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“Ripple Effects” and Forecasting Home Prices In Los Angeles, Las Vegas, and Phoenix

Author

Listed:
  • Rangan Gupta

    (Department of Economic, University of Pretoria)

  • Stephen M. Miller

    (College of Business, University of Las Vegas, Nevada)

Abstract

We examine the time-series relationship between housing prices in Los Angeles, Las Vegas, and 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. 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.

Suggested Citation

  • Rangan Gupta & Stephen M. Miller, 2009. "“Ripple Effects” and Forecasting Home Prices In Los Angeles, Las Vegas, and Phoenix," Working Papers 200901, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:200901
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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