1. bookVolume 32 (2016): Issue 2 (June 2016)
Journal Details
License
Format
Journal
eISSN
2001-7367
First Published
01 Oct 2013
Publication timeframe
4 times per year
Languages
English
access type Open Access

The FEWS Index: Fixed Effects with a Window Splice

Published Online: 28 May 2016
Volume & Issue: Volume 32 (2016) - Issue 2 (June 2016)
Page range: 375 - 404
Received: 01 Aug 2014
Accepted: 01 Nov 2015
Journal Details
License
Format
Journal
eISSN
2001-7367
First Published
01 Oct 2013
Publication timeframe
4 times per year
Languages
English
Abstract

This article describes the estimation of quality-adjusted price indexes from ‘big data’ such as scanner and online data when there is no available information on product characteristics for explicit quality adjustment using hedonic regression. The longitudinal information can be exploited to implicitly quality-adjust the price indexes. The fixed-effects (or ‘time-product dummy’) index is shown to be equivalent to a fully interacted time-dummy hedonic index based on all price-determining characteristics of the products, despite those characteristics not being observed. In production, this can be combined with a modified approach to splicing that incorporates the price movement across the full estimation window to reflect new products with one period’s lag without requiring revision. Empirical results for this fixed-effects window-splice (FEWS) index are presented for different data sources: three years of New Zealand consumer electronics scanner data from market-research company GfK; six years of United States supermarket scanner data from market-research company IRI; and 15 months of New Zealand consumer electronics daily online data from MIT’s Billion Prices Project.

Keywords

Aizcorbe, A., C. Corrado, and M. Doms. 2003. “When Do Matched-Model and Hedonic Techniques Yield Similar Price Measures?” Working Paper no. 2003-14, Federal Reserve Bank of San Francisco. Available at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=550421 (accessed March 2016).10.2139/ssrn.550421Search in Google Scholar

Bronnenberg, B.J., M. Kruger, and C.F. Mela. 2008. “The IRI Marketing Data Set” Marketing Science 27: 745–748. Available at: https://www.researchgate.net/publication/259286152_The_IRI_marketing_data_set (accessed April, 2016).Search in Google Scholar

Cavallo, A. 2012. “Overlapping Quality Adjustment Using Online Data.” Presentation to the 2012 Economic Measurement Group, Sydney, November 21–23, Australia. Available at: https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/A.%20Cavallo%20-%20Overlapping%20Quality%20Adjustment%20Using%20Online%20Data.pdf (accessed April 2016).Search in Google Scholar

de Haan, J. 2015a. “The Time-Product Dummy Method and Implicit Quality Adjustment.” Unpublished draft, May 2015.Search in Google Scholar

de Haan, J. 2015b. “Rolling Year Time Dummy Indexes and the Choice of Splicing Method.” Paper presented at the 14th meeting of the Ottawa Group, Tokyo. 20–22 May, 2015. Available at: http://www.stat.go.jp/english/info/meetings/og2015/pdf/t1s3room.pdf (accessed April 2016).Search in Google Scholar

de Haan, J. and H. van der Grient. 2011. “Eliminating Chain Drift in Price Indexes Based on Scanner Data.” Journal of Econometrics 161: 36–46. Doi: http://dx.doi.org/10.1016/j.jeconom.2010.09.004.Search in Google Scholar

de Haan, J. and R. Hendriks. 2013. “Online Data, Fixed Effects and the Construction of High-Frequency Price Indexes.” Paper presented at the 2013 Economic Measurement Group, Sydney, Australia. 28–29 November, 2013. Available at: https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/Jande-Haan-Online-Price-Indexes.pdf (accessed April 2016).Search in Google Scholar

de Haan, J. and F. Krsinich. 2014. “Scanner Data and the Treatment of Quality Change in Non-Revisable Price Indexes.” Journal of Business & Economic Statistics 32: 341–358. Doi: http://dx.doi/10.1080/07350015.2014.880059.Search in Google Scholar

Diewert, W.E. 2004. “On the Stochastic Approach to Linking the Regions in the ICP.” Discussion Paper no. 04-16, Department of Economics, University of British Columbia, Vancouver, Canada. Available at: http://papers.economics.ubc.ca/legacypapers/dp0416.pdf (accessed March 2016).Search in Google Scholar

Ivancic, L., W.E. Diewert, and K.J. Fox. 2011. “Scanner Data, Time Aggregation and the Construction of Price Indexes.” Journal of Econometrics 161: 24–35. Doi: http://dx.doi.org/10.1016/j.jeconom.2010.09.003.Search in Google Scholar

Krsinich, F. 2011a. “Price Indexes from Scanner Data: A Comparison of Different Methods.” Paper presented at the 12th meeting of the Ottawa Group, Wellington, New Zealand. 4–6 May, 2011. Available at: http://www.stats.govt.nz/~/media/Statistics/ottawa-group-2011/Ottawa-2011-Papers/Krsinich-2011-paper-PImethods-comparison.pdf (accessed April 2016).Search in Google Scholar

Krsinich, F. 2011b. “Measuring the Price Movements of Used Cars and Residential Rents in the New Zealand Consumers Price Index.” Paper presented at the 12th meeting of the Ottawa Group, Wellington, New Zealand. 4–6 May, 2011. Available at: http://www.stats.govt.nz/~/media/Statistics/ottawa-group-2011/Ottawa-2011-Papers/Krsinich-2011-paper-Rentals-cars.pdf (accessed April 2016).Search in Google Scholar

Krsinich, F. 2013. “Using the Rolling Year Time-Product Dummy Method for Quality Adjustment in the Case of Unobserved Characteristics.” Paper presented at the 13th meeting of the Ottawa Group, Copenhagen, Denmark. 1–3 May, 2013. Available at: http://www.dst.dk/da/Sites/ottawa-group/~/media/Kontorer/12-Priser-og-forbrug/Ottawa-Group/Frances%20Krsinich%202%20Ottawa%20Group%202013%20RYTPD%20final.pdf (accessed April 2016).Search in Google Scholar

Krsinich, F. 2014. “Fixed Effects with a Window Splice – Non-Revisable Quality-Adjusted Price Indexes with No Characteristic Information.” Paper presented at the meeting of the group of experts on consumer price indices, 26–28 May 2014, Geneva, Switzerland. Available at: http://www.unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.22/2014/New_Zealand_-_FEWS.pdf (accessed April 2016).Search in Google Scholar

Krsinich, F. 2015. “Price Indexes from Online Data Using the Fixed-Effects Window-Splice Method.” Paper presented at the 14th meeting of the Ottawa Group, Tokyo, Japan. 20–22 May, 2015. Available at: http://www.stat.go.jp/english/info/meetings/og2015/pdf/t1s2p7_pap.pdf (accessed April 2016).Search in Google Scholar

Lamboray, C. and F. Krsinich. 2015. “A Modification of the GEKS Index When Product Turnover is High.” Paper presented at the 14th meeting of the Ottawa Group, Tokyo, Japan. 20–22 May, 2015. Available at: http://www.stat.go.jp/english/info/meetings/og2015/pdf/t1s1p2_pap.pdf (accessed April 2016).Search in Google Scholar

Melser, D. 2011. “Constructing Cost of Living Indexes Using Scanner Data.” Unpublished draft, September 2011 – an updated version of “Constructing High Frequency Indexes Using Scanner Data.” Paper presented at the 12th meeting of the Ottawa Group, Wellington, New Zealand. 4–6 May, 2011. Available at: http://www.stats.govt.nz/~/media/Statistics/ottawa-group-2011/Ottawa-2011-Papers/Melser-2011-paper-Constructing-indexes.pdf (accessed April 2016).Search in Google Scholar

The Billion Prices Project. 2016. Available at: http://bpp.mit.edu (accessed April 2016).Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo