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Exploiting payments to track Italian economic activity: the experience at Banca d’Italia

Author

Listed:
  • Valentina Aprigliano

    (Bank of Italy)

  • Guerino Ardizzi

    (Bank of Italy)

  • Alessia Cassetta

    (Bank of Italy)

  • Alessandro Cavallero

    (Bank of Italy)

  • Simone Emiliozzi

    (Bank of Italy)

  • Alessandro Gambini

    (Bank of Italy)

  • Nazzareno Renzi

    (Bank of Italy)

  • Roberta Zizza

    (Bank of Italy)

Abstract

This paper provides an overview of how information on payments has been recently exploited by Banca d’Italia staff for the purposes of tracking economic activity and forecasting. In particular, the payment data used for this work are drawn from the payment systems managed by Banca d’Italia (BI-COMP and TARGET2) and from the Anti-Money Laundering Aggregate Reports submitted by banks and by Poste Italiane to the Banca d’Italia’s Financial Intelligence Unit (Unità di Informazione Finanziaria, UIF). We show that indicators drawn from these sources can improve forecasting accuracy; in particular, those available at a higher frequency have proved crucial to properly assessing the state of the economy during the pandemic. Moreover, these indicators make it possible to assess changes in agents’ behaviour, notably with reference to payment habits, and, thanks to their granularity, to delve deeper into the macroeconomic trends, exploring heterogeneity by sector and geography.

Suggested Citation

  • Valentina Aprigliano & Guerino Ardizzi & Alessia Cassetta & Alessandro Cavallero & Simone Emiliozzi & Alessandro Gambini & Nazzareno Renzi & Roberta Zizza, 2021. "Exploiting payments to track Italian economic activity: the experience at Banca d’Italia," Questioni di Economia e Finanza (Occasional Papers) 609, Bank of Italy, Economic Research and International Relations Area.
    • Handle: RePEc:bdi:opques:qef_609_21
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    short term forecasting; high-frequency data; payment systems; TARGET2; money laundering; COVID-19;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System

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