Constructing Building Price Index Using Administrative Data-Reference-Cited by-同舟云学术

Constructing Building Price Index Using Administrative Data

Published:2023-06-01 Issue:2 Volume:39 Page:229-251
ISSN:2001-7367
Container-title:Journal of Official Statistics
language:en
Short-container-title:

Author:

Higo Masahiro¹,Saita Yumi²,Shimizu Chihiro³,Tachi Yuta⁴

Affiliation:

1. 1 The University of Tokyo . 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 , Japan .

2. 2 Kwansei Gakuin University , 1-155, Uegahara Ichiban-cho, Nishinomiya, Hyogo, 662-8501 , Japan .

3. 3 Hitotsubashi University , 2-1 Naka, Kunitachi, Tokyo, 186-8601 , Japan .

4. 4 Reitaku University . 2-1-1, Hikarigaoka, Kashiwa-shi, Chiba, 277-8686 , Japan .

Abstract

Abstract Improving the accuracy of deflators is crucial for measuring real GDP and growth rates. However, construction prices are often difficult to measure. This study uses the stratification and hedonic methods to estimate price indices. The estimated indices are based on the actual transaction prices of buildings (contract prices) obtained from the Statistics on Building Starts survey information from the administrative sector in Japan. Compared with the construction cost deflator (CCD), calculated by compounding input costs, the estimated output price indices show higher rates of increase during the economic expansion phase after 2013. This suggests that the profit surge in the construction sector observed in that period is not fully reflected in the CCD. Furthermore, the difference between the two “output-type” indices obtained by stratification and hedonic methods shrinks when the estimation methods are precisely configured.

Publisher

SAGE Publications

Subject

Statistics and Probability

Link

https://www.sciendo.com/pdf/10.2478/jos-2023-0011

Reference25 articles.

1. Benedetti, I., L. Biggeri, and T. Laureti. 2022. “Sub-National Spatial Price Indexes for Housing: Methodological Issues and Computation for Italy.” Journal of Official Statistics 38(1): 57–82. DOI: http://dx.doi.org/10.2478/JOS-2022-0004.

2. Cabinet Office (Government of Japan). 2022. Explanatory Notes on the Methodology for Estimating National Accounts (Annual Estimates), 2015 Standard Version. Available at: https://www.esri.cao.go.jp/jp/sna/data/reference1/h27benchmark/pdf/kaisetsu_20220726.pdf (accessed December 2022).

3. De Haan, J. 2004. “Direct and indirect time dummy approaches to hedonic price measurement.” Journal of Economic and Social Measurement 29: 427–443. DOI: http://doi.org/10.3233/JEM-2004-0235.

4. Diewert, W.E. 2003. “Hedonic Regressions: A Review of Some Unresolved Issues,” In Proceedings of the Seventh Meeting of the International Working Group on Price Indices: the United Nations Statistical Commission, May 27–29, 2003. Available at: https://econ.sites.olt.ubc.ca/files/2013/06/pdf_paper_erwin-diewert-hedonic-regressions.pdf (accessed December 2022).

5. Diewert, W.E., and C. Shimizu. 2015. “Residential Property Price Indices for Tokyo.” Macroeconomic Dynamics 19: 1659–1714. DOI: https://doi.org/10.1017/S1365100514000042.