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A Note on Monitoring Daily Economic Activity Via Electronic Transaction Data

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  • John W. Galbraith
  • Greg Tkacz

Abstract

Economists have traditionally relied on monthly or quarterly data supplied by central statistical agencies for macroeconomic monitoring. 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 economic activity, using Canadian debit card data, and using two potentially important economic events as examples. In particular we are able to analyze expenditure patterns around the September 11 terrorist attacks and the August 2003 electrical blackout, and are able to note qualitative differences in the effects of these events which could not be observed through aggregate measures. Les économistes se sont traditionnellement appuyés sur les données mensuelles ou trimestrielles publiées par les agences centrales de statistiques pour suivre la situation macroéconomique. Cependant, les avancées technologiques qui ont été réalisées au cours des dernières années ont entraîné de nouvelles sources de données à haute fréquence, et ces dernières pourraient potentiellement donner lieu à une information plus exacte et plus opportune sur l'état actuel de l'activité économique. Dans le document actuel, nous explorons l'utilité des transactions électroniques comme indicateurs en temps réel de l'activité économique. Pour ce faire, nous recourons aux données canadiennes sur les cartes de débit et utilisons, à titre d'exemples, deux événements économiques susceptibles d'être importants. Plus particulièrement, nous sommes en mesure d'analyser la structure des dépenses lors des attaques terroristes du 11 septembre et de la panne d'électricité d'août 2003 et de noter des différences qualitatives dans les répercussions de ces événements, lesquelles ne pourraient être observées en recourant aux mesures globales.

Suggested Citation

  • John W. Galbraith & Greg Tkacz, 2009. "A Note on Monitoring Daily Economic Activity Via Electronic Transaction Data," CIRANO Working Papers 2009s-23, CIRANO.
  • Handle: RePEc:cir:cirwor:2009s-23
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    References listed on IDEAS

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    1. Ariel Burstein & Martin Eichenbaum & Sergio Rebelo, 2005. "Large Devaluations and the Real Exchange Rate," Journal of Political Economy, University of Chicago Press, vol. 113(4), pages 742-784, August.
    2. Silver, Mick & Heravi, Saeed, 2001. "Scanner Data and the Measurement of Inflation," Economic Journal, Royal Economic Society, vol. 111(472), pages 383-404, June.
    3. Martin D. D. Evans, 2005. "Where Are We Now? Real-Time Estimates of the Macroeconomy," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
    4. Ron Borzekowski & K. Kiser Elizabeth & Ahmed Shaista, 2008. "Consumers' Use of Debit Cards: Patterns, Preferences, and Price Response," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(1), pages 149-172, February.
    5. 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;Western Finance Association, vol. 17(1), pages 17-39, February.
    6. Judith A. Chevalier & Anil K. Kashyap & Peter E. Rossi, 2003. "Why Don't Prices Rise During Periods of Peak Demand? Evidence from Scanner Data," American Economic Review, American Economic Association, vol. 93(1), pages 15-37, March.
    7. Jerry Hausman & Ephraim Leibtag, 2009. "CPI Bias from Supercenters: Does the BLS Know that Wal-Mart Exists?," NBER Chapters, in: Price Index Concepts and Measurement, pages 203-231, National Bureau of Economic Research, Inc.
    8. Aruoba, S. BoraÄŸan & Diebold, Francis X. & Scotti, Chiara, 2009. "Real-Time Measurement of Business Conditions," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 417-427.
    9. Geoffrey R. Gerdes & May X. Liu & Darrel W. Parke & Jack K. Walton, 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.), vol. 91(Spr), pages 180-201.
    10. 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.
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    Cited by:

    1. Raquel Nadal Cesar Gonçalves, 2022. "Nowcasting Brazilian GDP with Electronic Payments Data," Working Papers Series 564, Central Bank of Brazil, Research Department.
    2. Valentina Aprigliano & Guerino Ardizzi & Libero Monteforte, 2017. "Using the payment system data to forecast the Italian GDP," Temi di discussione (Economic working papers) 1098, Bank of Italy, Economic Research and International Relations Area.
    3. Tut, Daniel, 2023. "FinTech and the COVID-19 pandemic: Evidence from electronic payment systems," Emerging Markets Review, Elsevier, vol. 54(C).

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    Keywords

    debit cards; electronic transactions; monitoring ; cartes de débit; transactions électroniques; suivi;
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