IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp17311.html
   My bibliography  Save this paper

The IZA / Fable Swipe Consumption Index

Author

Listed:
  • Askitas, Nikos

    (IZA)

  • Martinez, Anoop Bindra

    (Fable Data)

  • Cereda, Fabio Saia

    (Fable Data)

Abstract

This paper introduces a novel monthly consumption indicator: the IZA / Fable Data consumption indicator for Germany. It is based on credit card transactions data collected and anonymised by Fable Data from 2017 onwards. We study some of the properties of the data and use a so-called "one year look back rolling panel" method to construct a monthly consumption indicator which expresses the year on year change. The data provisioning is fast and data is updated daily so that our indicator is stable with a 3 day lag. Moreover preliminary results for a month can be delivered as early as the middle of the month by comparing months partially. Our indicator is a new experimental early indicator ideal for nowcasting purposes and forecasting of breaking trends in consumer behaviour.

Suggested Citation

  • Askitas, Nikos & Martinez, Anoop Bindra & Cereda, Fabio Saia, 2024. "The IZA / Fable Swipe Consumption Index," IZA Discussion Papers 17311, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp17311
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp17311.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    2. Nikolaos Askitas, 2016. "Predicting Road Conditions with Internet Search," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-12, August.
    3. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    4. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "Health and well-being in the great recession," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 26-47, April.
    5. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "Health and well-being in the great recession," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 26-47, April.
    6. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    7. Nikolaos Askitas & Klaus F. Zimmermann, 2013. "Nowcasting Business Cycles Using Toll Data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(4), pages 299-306, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    2. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
    3. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
    4. Gutiérrez, Antonio, 2022. "Movilidad urbana y datos de alta frecuencia [Urban mobility and high frequency data]," MPRA Paper 114854, University Library of Munich, Germany.
    5. Rui Wang & Jing Kang, 2024. "Financial Interconnectedness and Bank Risk-Taking: Evidence from China," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 11819-11847, September.
    6. Luca Bonacini & Giovanni Gallo & Fabrizio Patriarca, 2021. "Identifying policy challenges of COVID-19 in hardly reliable data and judging the success of lockdown measures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 275-301, January.
    7. Fabo, B., 2017. "Towards an understanding of job matching using web data," Other publications TiSEM b8b877f2-ae6a-495f-b6cc-9, Tilburg University, School of Economics and Management.
    8. Raymundo M. Campos-Vázquez & Julio César Martínez Sánchez, 2024. "Habilidades buscadas por las empresas en el mercado laboral mexicano: un análisis de las ofertas laborales publicadas en internet/Skills sought by companies in the Mexican labor market: An analysis o," Estudios Económicos, El Colegio de México, Centro de Estudios Económicos, vol. 39(2), pages 243–278-2.
    9. Jan Drahokoupil & Brian Fabo, 2022. "The limits of foreign-led growth: Demand for skills by foreign and domestic firms," Review of International Political Economy, Taylor & Francis Journals, vol. 29(1), pages 152-174, January.
    10. Mutascu, Mihai & Horky, Florian & Strango, Cristina, 2023. "Good or bad? Digitalisation and green preferences," Energy Economics, Elsevier, vol. 121(C).
    11. Nwaobi, Godwin, 2019. "University Postgraduate Research Programmes: Digitization(ICT),Innovations and Applications," MPRA Paper 96730, University Library of Munich, Germany.
    12. Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The internet as a data source for advancement in social sciences," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
    13. Askitas, Nikos, 2015. "Calling the Greek Referendum on the Nose with Google Trends," IZA Discussion Papers 9569, Institute of Labor Economics (IZA).
    14. Lucia Mýtna Kureková & Zuzana Žilinčíková, 2016. "Are student jobs flexible jobs? Using online data to study employers’ preferences in Slovakia," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-14, December.
    15. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.
    16. Yu Qin & Hongjia Zhu, 2018. "Run away? Air pollution and emigration interests in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 31(1), pages 235-266, January.
    17. Florin Paul Costel LILEA & Alexandru MANOLE & Maria MIREA & Andreea - Ioana MARINESCU, 2017. "Models Of Development Of Labour Productivity Forecast," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(4), pages 107-114, April.
    18. Riccardo Corradini, 2019. "A Set of State–Space Models at a High Disaggregation Level to Forecast Italian Industrial Production," J, MDPI, vol. 2(4), pages 1-53, November.
    19. Fabio Milani, 2021. "COVID-19 outbreak, social response, and early economic effects: a global VAR analysis of cross-country interdependencies," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(1), pages 223-252, January.
    20. Gutiérrez, Antonio, 2023. "La brecha de género en el emprendimiento y la cultura emprendedora: Evidencia con Google Trends [Entrepreneurship gender gap and entrepreneurial culture: Evidence from Google Trends]," MPRA Paper 115876, University Library of Munich, Germany.

    More about this item

    Keywords

    consumption expenditures; credit card transactions; nowcasting;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • E2 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp17311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.