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Hedonic Imputed Property Price Indexes: The Effects of Econometric Modeling Choices

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  • Alicia N. Rambaldi
  • Cameron S. Fletcher

Abstract

In this paper we consider how choices in the econometric approach to impute prices affect the Törnqvist and Jevons hedonic imputed indexes. We compare the rolling window approach to estimation by smoothing methods. The main difference between the rolling window and the smoothing methods is in the way information is weighted. We propose that the Kalman filter smoother is the most appropriate estimator for the task as it optimally weights current and past information. We show the rolling window approach does not produce estimates that are attenuated over time leading to chain drift in the index. We also compare two alternative specifications to model property location. The empirical section uses data from a small and homogeneous market in the state of Queensland, Australia. The Törnqvist and Jevons indexes differ in value during periods of market volatility. This seems expected given their different weighting of transactions and the likelihood that price movements of properties at the upper and lower end of the price distribution might differ during periods of market volatility.

Suggested Citation

  • Alicia N. Rambaldi & Cameron S. Fletcher, 2014. "Hedonic Imputed Property Price Indexes: The Effects of Econometric Modeling Choices," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 423-448, November.
    • Handle: RePEc:bla:revinw:v:60:y:2014:i:s2:p:s423-s448
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    References listed on IDEAS

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    Cited by:

    1. Robert J. Hill & Alicia N. Rambaldi & Michael Scholz, 2021. "Higher frequency hedonic property price indices: a state-space approach," Empirical Economics, Springer, vol. 61(1), pages 417-441, July.
    2. Robert J. Hill & Norbert Pfeifer & Miriam Steurer & Radoslaw Trojanek, 2021. "Warning: Some Transaction Prices can be Detrimental to your House Price Index," Graz Economics Papers 2021-11, University of Graz, Department of Economics.
    3. Robert J. Hill & Alicia N. Rambaldi, 2022. "Hedonic Models and House Price Index Numbers," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 413-444, Springer.
    4. Marshall Reinsdorf & Robert Hill, 2014. "The 32nd IARIW General Conference, Boston, Massachusetts, 2012: Editors’ Introduction," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S2), pages 277-280, November.
    5. Iqbal A. Syed & Jan De Haan, 2017. "Age, Time, Vintage, And Price Indexes: Measuring The Depreciation Pattern Of Houses," Economic Inquiry, Western Economic Association International, vol. 55(1), pages 580-600, January.
    6. Silver Mick, 2022. "Econometric Issues in Hedonic Property Price Indices: Some Practical Help," Journal of Official Statistics, Sciendo, vol. 38(1), pages 153-186, March.
    7. Mick Silver, 2016. "How to Better Measure Hedonic Residential Property Price Indexes," IMF Working Papers 2016/213, International Monetary Fund.
    8. Melser, Daniel, 2017. "Disaggregated property price appreciation: The mixed repeat sales model," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 108-118.

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