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Higher Frequency Hedonic Property Price Indices: A State Space Approach

Author

Listed:
  • Robert J. Hill

    () (University of Graz, Austria)

  • Alicia N. Rambaldi

    () (School of Economics, University of Queensland, Australia)

  • Michael Scholz

    () (University of Graz, Austria)

Abstract

The hedonic imputation method estimates separate characteristic shadow prices for each period. These are used to construct matched samples, which are inserted into standard price index formulas. We implement two innovations to improve the method’s effectiveness on housing data at higher frequencies. First, we use a time-varying parameter model in state-space form to increase the reliability of the estimated characteristic shadow prices. Second, we significantly reduce the number of parameters by replacing postcode dummies by a geospatial spline surface. Empirically, using a novel criterion, we show that in higher frequency comparisons our hedonic method outperforms competing alternatives.

Suggested Citation

  • Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2018. "Higher Frequency Hedonic Property Price Indices: A State Space Approach," Graz Economics Papers 2018-04, University of Graz, Department of Economics.
  • Handle: RePEc:grz:wpaper:2018-04
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    References listed on IDEAS

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    More about this item

    Keywords

    Housing market; Hedonic imputation; State Space Model; Geospatial data; Spline; Quality adjustment; Matched sample;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • 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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