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Forecasting State- and MSA-Level Housing Returns of the US: The Role of Mortgage Default Risks

Author

Listed:
  • Christos Bouras

    (Department of Banking and Financial Management, University of Piraeus, 18534, Piraeus, Greece)

  • Christina Christou

    (School of Economics and Management, Open University of Cyprus, 2252, Latsia, Cyprus)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Keagile Lesame

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

Abstract

We analyze the ability of an index of mortgage default risks (MDRI) for 43 states and 20 MSAs of the US derived from Google search queries, in predicting (in- and out-of-sample) housing returns of the corresponding states and MSAs, based on various panel data and time-series approaches. In general, our results tend to prefer the panel data model based on common correlated effects estimation. We highlight that growth in MDRI negatively impacts housing returns within-sample, with predictive gains primarily concentrated beyond a year. These results are robust to alternative out-of-sample periods and econometric frameworks. Given the role of house prices as a leading indicators, our results are of value to policymakers, especially at the longer-run.

Suggested Citation

  • Christos Bouras & Christina Christou & Rangan Gupta & Keagile Lesame, 2020. "Forecasting State- and MSA-Level Housing Returns of the US: The Role of Mortgage Default Risks," Working Papers 202037, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202037
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    More about this item

    Keywords

    Mortgage Default Risks; Housing Returns; States and MSAs; Panel Data Predictive Models;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation 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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