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Rolling-Time-Dummy House Price Indexes: Window Length, Linking and Options for Dealing with the Covid-19 Shutdown

Author

Listed:
  • Robert J. Hill

    (University of Graz, Austria)

  • Michael Scholz

    (University of Graz, Austria)

  • Chihiro

    (University of Tokyo, Japan)

  • Miriam Steurer

    (University of Graz, Austria)

Abstract

The rolling-time-dummy (RTD) method is used by a number of countries to compute their official house price indexes (HPIs), since it requires less data and is more flexible than other hedonic methods. These features also make it well suited for computing higher frequency HPIs (e.g., monthly or weekly). In this paper we address three key issues relating to the RTD hedonic method. First, we develop a method for determining the optimal length of the rolling window. Second, we consider variants on the standard way of linking the current period with earlier periods, and show how the optimal linking method can be determined. Third, we propose three ways of modifying the RTD method to make it robust to the distorting effects of the covid-19 shutdown. These modifications could prove useful for countries using the RTD method in their official HPIs.

Suggested Citation

  • Robert J. Hill & Michael Scholz & Chihiro & Miriam Steurer, 2020. "Rolling-Time-Dummy House Price Indexes: Window Length, Linking and Options for Dealing with the Covid-19 Shutdown," Graz Economics Papers 2020-14, University of Graz, Department of Economics.
    • Handle: RePEc:grz:wpaper:2020-14
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    References listed on IDEAS

    as
    1. W. Erwin Diewert & Saeed Heravi & Mick Silver, 2009. "Response to Jan de Haan's comment on "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Chapters, in: Price Index Concepts and Measurement, pages 201-202, National Bureau of Economic Research, Inc.
    2. W. Erwin Diewert & Saeed Heravi & Mick Silver, 2009. "Hedonic Imputation versus Time Dummy Hedonic Indexes," NBER Chapters, in: Price Index Concepts and Measurement, pages 161-196, National Bureau of Economic Research, Inc.
    3. Diewert, W. Erwin & Fox, Kevin J., 2017. "Substitution Bias in Multilateral Methods for CPI Construction using Scanner Data," Microeconomics.ca working papers erwin_diewert-2017-3, Vancouver School of Economics, revised 23 Mar 2017.
    4. D. S.P. Rao (ed.), 2009. "Purchasing Power Parities of Currencies," Books, Edward Elgar Publishing, number 3725, March.
    5. Diewert, Erwin, 2011. "Alternative Approaches to Measuring House Price Inflation," Economics working papers erwin_diewert-2011-1, Vancouver School of Economics, revised 07 Jan 2011.
    6. W. Erwin Diewert & John S. Greenlees & Charles R. Hulten, 2009. "Price Index Concepts and Measurement," NBER Books, National Bureau of Economic Research, Inc, number diew08-1, February.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Sayag, Doron & Ben-hur, Dano & Pfeffermann, Danny, 2022. "Reducing revisions in hedonic house price indices by the use of nowcasts," International Journal of Forecasting, Elsevier, vol. 38(1), pages 253-266.
    2. Manner, Hans & Rodríguez, Gabriel & Stöckler, Florian, 2024. "A changepoint analysis of exchange rate and commodity price risks for Latin American stock markets," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1385-1403.
    3. Daniel Reiter, 2020. "Socioeconomic Integration through Language: Evidence from the European Union," Graz Economics Papers 2020-15, University of Graz, Department of Economics.

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    More about this item

    Keywords

    House price index; Hedonic quality adjustment; Optimal window length; Optimal chain linking; Higher frequency indexes; Covid-19 shutdown.;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • 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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