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El Paso Housing Sector Econometric Forecast Accuracy

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  • Fullerton, Thomas M., Jr.
  • Kelley, Brian W.

Abstract

There is comparatively little empirical evidence regarding the accuracy of regional housing sector forecasts. Much of the recent analysis conducted for this topic is developed for housing starts and indicates a relatively poor track record. This study examines residential real estate forecasts previously published for El Paso, TX using a structural econometric model. Model coverage is much broader than just starts. Similar to earlier studies, the previously published econometric predictions frequently do not fare very well against the selected random walk benchmarks utilized for the various series under consideration.

Suggested Citation

  • Fullerton, Thomas M., Jr. & Kelley, Brian W., 2008. "El Paso Housing Sector Econometric Forecast Accuracy," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 40(1), pages 1-18, April.
  • Handle: RePEc:ags:joaaec:45534
    DOI: 10.22004/ag.econ.45534
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    File URL: https://ageconsearch.umn.edu/record/45534/files/jaae-40-01-385.pdf
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    References listed on IDEAS

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    Cited by:

    1. Arnold Cote, K. Nicole & Smith, Wm. Doyle & Fullerton, Thomas M., Jr., 2010. "Municipal Non-Residential Real Property Valuation Forecast Accuracy," MPRA Paper 32116, University Library of Munich, Germany, revised 11 Feb 2011.

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    More about this item

    Keywords

    Agribusiness; Community/Rural/Urban Development; Political Economy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods
    • 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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