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Predicting the Geography of House Prices

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  • Fingleton, Bernard

Abstract

Prediction is difficult. In this paper we use panel data methods to make reasonably accurate short term ex-post predictions of house prices across 353 local authority areas in England. The issue of prediction over the longer term is also addressed, and a simple method that makes use of the dynamics embodied in New Economic geography theory is suggested as a possible way to approach the problem.

Suggested Citation

  • Fingleton, Bernard, 2010. "Predicting the Geography of House Prices," MPRA Paper 21113, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:21113
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    References listed on IDEAS

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    Cited by:

    1. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    2. Silvia Palombi & Roger Perman & Christophe Tavéra, 2017. "Commuting effects in Okun's Law among British areas: Evidence from spatial panel econometrics," Papers in Regional Science, Wiley Blackwell, vol. 96(1), pages 191-209, March.
    3. Nicolas Debarsy, 2012. "The Mundlak Approach in the Spatial Durbin Panel Data Model," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 109-131, March.
    4. Fingleton, Bernard & Palombi, Silvia, 2013. "Spatial panel data estimation, counterfactual predictions, and local economic resilience among British towns in the Victorian era," Regional Science and Urban Economics, Elsevier, vol. 43(4), pages 649-660.

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    More about this item

    Keywords

    new economic geography; real estate prices; spatial econometrics; panel data; prediction.;
    All these keywords.

    JEL classification:

    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect 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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