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A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data

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Abstract

The recent worldwide development and widespread use of electronic payment systems opened the opportunity to explore new data sources for monitoring macroeconomic activity. In this paper, we analyse the usefulness of data collected from Automated Teller Machines (ATM) and Points-Of-Sale (POS) for nowcasting and forecasting quarterly private consumption. To take advantage of the high frequency availability of such data, we use Mixed Data Sampling (MIDAS) regressions. A comparison of several MIDAS variants proposed in the literature is conducted, both single- and multiple variable models are considered, as well as different information sets within the quarter. Given the high penetration of ATM/POS technology in Portugal, it becomes a natural case study to assess its information content for tracking private consumption behaviour. We find that ATM/POS data displays better forecast performance than typical indicators, reinforcing the potential usefulness of this novel type of data among policymakers and practitioner.

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  • Cláudia Duarte, 2016. "A Mixed Frequency Approach to Forecast Private Consumption with ATM/POS Data," Working Papers w201601, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w201601
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    Cited by:

    1. Gurgul Henryk & Suder Marcin, 2016. "Calendar and Seasonal Effects on the Size of Withdrawals from Atms Managed By Euronet," Statistics in Transition New Series, Statistics Poland, vol. 17(4), pages 691-722, December.
    2. Cláudia Duarte & Sónia Cabral, . "Nowcasting Portuguese tourism exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    3. Cláudia Duarte & Sónia Cabral, 2016. "Nowcasting Portuguese tourism exports," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.

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    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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