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Electronic Transactions As High-Frequency Indicators Of Economics Activity

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  • John Galbraith

    ()

  • Greg Tkacz

    ()

Abstract

Since the advent of standard national accounts data over 60 years ago, economists have relied on monthly or quarterly data supplied by central statistical agencies for macroeconomics modelling and forecasting. However, technological advances of the past several years have resulted in new high-frequency data sources that could potentially provide more accurate and timely information on the current level of economic activity. In this paper we explore the usefulness of electronic transactions as real-time indicators of economics activity, using Canadian debit card data as an example. These data have the advantages of daily availability and teh high market penetration of debit cards. We find that (i) household transactions vary greatly according to the day of the week, peaking every Friday and falling every Sunday; (ii) debit card data can help lower consensus forecast errors for GDP growth; (iii) debit card transactions are correlated wtih Statistics Canada's revisions to GDP; (iv) high-frequency analyses of transactions around extreme events are possible, and in particular we are able to analyze expenditure patterns around the September 11 terrorist attacks and the August 2003 electrical blackout.

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Bibliographic Info

Paper provided by McGill University, Department of Economics in its series Departmental Working Papers with number 2008-04.

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Length: 23 pages
Date of creation: Mar 2008
Date of revision:
Handle: RePEc:mcl:mclwop:2008-04

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  1. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  2. Ariel Burstein & Martin Eichenbaum & Sergio Rebelo, 2004. "Large Devaluations and the Real Exchange Rate," RCER Working Papers 513, University of Rochester - Center for Economic Research (RCER).
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  5. Silver, Mick & Heravi, Saeed, 2001. "Scanner Data and the Measurement of Inflation," Economic Journal, Royal Economic Society, vol. 111(472), pages F383-404, June.
  6. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions," PIER Working Paper Archive 07-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  7. Silver, Mick & Heravi, Saeed, 2005. "A Failure in the Measurement of Inflation: Results From a Hedonic and Matched Experiment Using Scanner Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 269-281, July.
  8. Athanasios Orphanides, 1998. "Monetary policy rules based on real-time data," Finance and Economics Discussion Series 1998-03, Board of Governors of the Federal Reserve System (U.S.).
  9. Judith A. Chevalier & Anil K. Kashyap & Peter E. Rossi, 2000. "Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data," NBER Working Papers 7981, National Bureau of Economic Research, Inc.
  10. Ron Borzekowski & Elizabeth K. Kiser & Shaista Ahmed, 2006. "Consumers' use of debit cards: patterns, preferences, and price response," Finance and Economics Discussion Series 2006-16, Board of Governors of the Federal Reserve System (U.S.).
  11. Geoffrey R. Gerdes & Jack K. Walton II & May X. Liu & Darrel W. Parke, 2005. "Trends in the use of payment instruments in the United States," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Spr, pages 180-201.
  12. Venkatesh Shankar & Ruth N. Bolton, 2004. "An Empirical Analysis of Determinants of Retailer Pricing Strategy," Marketing Science, INFORMS, vol. 23(1), pages 28-49, May.
  13. David Humphrey & Lawrence Pulley & Jukka Vesala, 2000. "The Check's in the Mail: Why the United States Lags in the Adoption of Cost-Saving Electronic Payments," Journal of Financial Services Research, Springer, vol. 17(1), pages 17-39, February.
  14. Luis C. Nunes, 2005. "Nowcasting quarterly GDP growth in a monthly coincident indicator model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 575-592.
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Cited by:
  1. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions," PIER Working Paper Archive 07-028, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  2. S. Boragan Aruoba & Francis X. Diebold & Chiara Scotti, 2007. "Real-Time Measurement of Business Conditions, Second Version," PIER Working Paper Archive 08-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 04 Apr 2008.

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