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A Simple Repeat Sales House Price Index: Comparative Properties Under Alternative Data Generation Processes

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  • Arthur Grimes

    (Motu Economic and Public Policy Research; and University of Waikato)

  • Chris Young

    (Motu Economic and Public Policy Research)

Abstract

We propose a new method to estimate a repeat-sales house price index. Our unbalanced panel method employs an OLS panel regression to estimate the (log) house price as a function of time fixed effects and house-specific fixed effects. Comparisons are made across three repeat-sales methods using actual data, and using simulated data with both stationary and non-stationary relative price innovations. The unbalanced panel method comprehensively utilises all sale information on a house rather than splitting sales into distinct pairs. It is the simplest of the methods to implement, and possesses superior properties to the other two methods under a wide range of data generation processes.

Suggested Citation

  • Arthur Grimes & Chris Young, 2010. "A Simple Repeat Sales House Price Index: Comparative Properties Under Alternative Data Generation Processes," Working Papers 10_10, Motu Economic and Public Policy Research.
    • Handle: RePEc:mtu:wpaper:10_10
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    File URL: https://motu-www.motu.org.nz/wpapers/10_10.pdf
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    References listed on IDEAS

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    1. Arthur Grimes & Chris Young, 2010. "Anticipatory Effects of Rail Upgrades: Auckland’s Western Line," Working Papers 10_11, Motu Economic and Public Policy Research.
    2. Karl E. Case & Robert J. Shiller, 1987. "Prices of single-family homes since 1970: new indexes for four cities," New England Economic Review, Federal Reserve Bank of Boston, issue Sep, pages 45-56.
    3. Bourassa, Steven C. & Hoesli, Martin & Sun, Jian, 2006. "A simple alternative house price index method," Journal of Housing Economics, Elsevier, vol. 15(1), pages 80-97, March.
    4. Jesse M. Abraham & William S. Schauman, 1991. "New Evidence on Home Prices from Freddie Mac Repeat Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 333-352, September.
    5. Wang, Ferdinand T. & Zorn, Peter M., 1997. "Estimating House Price Growth with Repeat Sales Data: What's the Aim of the Game?," Journal of Housing Economics, Elsevier, vol. 6(2), pages 93-118, June.
    6. de Vries, Paul & de Haan, Jan & van der Wal, Erna & Mariën, Gust, 2009. "A house price index based on the SPAR method," Journal of Housing Economics, Elsevier, vol. 18(3), pages 214-223, September.
    7. Daniel P. McMillen & John McDonald, 2004. "Reaction of House Prices to a New Rapid Transit Line: Chicago's Midway Line, 1983–1999," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 32(3), pages 463-486, September.
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    Cited by:

    1. Arthur Grimes & Chris Young, 2010. "Anticipatory Effects of Rail Upgrades: Auckland’s Western Line," Working Papers 10_11, Motu Economic and Public Policy Research.
    2. Ryan Greenaway‐McGrevy & Arthur Grimes & Mark Holmes, 2019. "Two countries, sixteen cities, five thousand kilometres: How many housing markets?," Papers in Regional Science, Wiley Blackwell, vol. 98(1), pages 353-370, February.
    3. Levente Timar & Arthur Grimes & Richard Fabling, 2014. "That Sinking Feeling: The Changing Price of Disaster Risk Following an Earthquake," Working Papers 14_13, Motu Economic and Public Policy Research.
    4. Grimes, Arthur & Young, Chris, 2013. "Spatial effects of urban rail upgrades," Journal of Transport Geography, Elsevier, vol. 30(C), pages 1-6.
    5. Jed Armstrong & Ashley Dunstan & Tobias Irrcher, 2017. "Evaluating alternative monthly house price measures for New Zealand," Reserve Bank of New Zealand Analytical Notes series AN2017/02, Reserve Bank of New Zealand.

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    More about this item

    Keywords

    Repeat-Sales; House Price Index; Case Shiller; Unbalanced Panel;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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