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From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time

Author

Listed:
  • Friederike Fourné
  • Robert Lehmann

Abstract

In this paper, we use high-frequency transaction data to develop a weekly tracker for private consumption expenditures. Furthermore, we apply the transaction data in a nowcasting experiment and compare their performance with other, readily available indicators that are regularly linked to private consumption in Germany. The weekly tracker produces precise estimates and can thus be used in real-time, especially in very turbulent times such as a pandemic or the high-inflation-phase in its aftermath. In terms of nowcast accuracy, the tracker outperforms all remaining indicators, making it a powerful tool for applied forecasting work. We plan to regularly publish the weekly consumption tracker in the future, thereby complementing the database for Germany.

Suggested Citation

  • Friederike Fourné & Robert Lehmann, 2023. "From Shopping to Statistics: Tracking and Nowcasting Private Consumption Expenditures in Real-Time," CESifo Working Paper Series 10764, CESifo.
    • Handle: RePEc:ces:ceswps:_10764
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    File URL: https://www.cesifo.org/DocDL/cesifo1_wp10764.pdf
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    References listed on IDEAS

    as
    1. Anirban Bhattacharya & Debdeep Pati & Natesh S. Pillai & David B. Dunson, 2015. "Dirichlet--Laplace Priors for Optimal Shrinkage," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1479-1490, December.
    2. Gary Koop & Stuart McIntyre & James Mitchell & Aubrey Poon, 2020. "Regional output growth in the United Kingdom: More timely and higher frequency estimates from 1970," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(2), pages 176-197, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    private consumption expenditures; real-time tracker; high-frequency transaction data; mixed-frequency vectorautoregression; Bayesian estimation;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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