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Residential Property Price Indexes for Tokyo

Author

Listed:
  • Diewert, Erwin
  • Shimizu, Chihiro

Abstract

The paper uses hedonic regression techniques in order to decompose the price of a house into land and structure components using real estate sales data for Tokyo. In order to get sensible results, a nonlinear regression model using data that covered multiple time periods was used. Collinearity between the amount of land and structure in each residential property leads to inaccurate estimates for the land and structure value of a property. This collinearity problem was solved by using exogenous information on the rate of growth of construction costs in Tokyo in order to get useful constant quality subindexes for the price of land and structures separately.

Suggested Citation

  • Diewert, Erwin & Shimizu, Chihiro, 2013. "Residential Property Price Indexes for Tokyo," Economics working papers erwin_diewert-2013-16, Vancouver School of Economics, revised 11 Apr 2013.
    • Handle: RePEc:ubc:bricol:erwin_diewert-2013-16
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    File URL: http://faculty.arts.ubc.ca/ediewert/dp1307.pdf
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    Cited by:

    1. Diewert, W. Erwin & Shimizu, Chihiro, 2016. "Hedonic regression models for Tokyo condominium sales," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 300-315.
    2. Shimizu, Chihiro & Imai, Satoshi & Diewert, Erwin, 2016. "Alternative Approaches to Housing Services and Japanese CPI: -Bias from Nominal Rigidity of Rents-," HIT-REFINED Working Paper Series 35, Institute of Economic Research, Hitotsubashi University.
    3. Erwin Diewert & Chihiro Shimizu, 2017. "Alternative Approaches to Commercial Property Price Indexes for Tokyo," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(3), pages 492-519, September.
    4. Suzuki, Masatomo & Asami, Yasushi & Shimizu, Chihiro, 2021. "Housing rent rigidity under downward pressure: Unit-level longitudinal evidence from Tokyo," Journal of Housing Economics, Elsevier, vol. 52(C).
    5. Suzuki, Masatomo & Shimizu, Chihiro, 2024. "Obsolete housing equipment, weak renovation, and rapid depreciation of Japanese condominiums," Journal of the Japanese and International Economies, Elsevier, vol. 71(C).
    6. Tokuo Iwaisako & Arito Ono & Amane Saito & Hidenobu Tokuda, 2022. "Disentangling the effect of home ownership on household stockholdings: Evidence from Japanese micro data," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 268-295, March.
    7. Reusens, Peter & Vastmans, Frank & Damen, Sven, 2023. "A new framework to disentangle the impact of changes in dwelling characteristics on house price indices," Economic Modelling, Elsevier, vol. 123(C).
    8. W. Erwin Diewert & Kiyohiko G. Nishimura & Chihiro Shimizu & Tsutomu Watanabe, 2020. "New Estimates for the Price of Housing in the Japanese CPI," Advances in Japanese Business and Economics, in: Property Price Index, chapter 0, pages 299-323, Springer.
    9. Chihiro Shimizu & Erwin Diewert, 2023. "Scanner Data, Product Churn and Quality Adjustment," Working Papers e185, Tokyo Center for Economic Research.
    10. 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.
    11. W. Erwin Diewert & Kevin J. Fox & Chihiro Shimizu, 2016. "Commercial Property Price Indexes And The System Of National Accounts," Journal of Economic Surveys, Wiley Blackwell, vol. 30(5), pages 913-943, December.
    12. Alicia N. Rambaldi & Ryan R. J. McAllister & Cameron S. Fletcher, 2015. "Decoupling land values in residential property prices: smoothing methods for hedonic imputed price indices," Discussion Papers Series 549, School of Economics, University of Queensland, Australia.

    More about this item

    Keywords

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    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand

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