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Un modello statistico per il monitoraggio delle entrate tributarie (MoME)

Author

Listed:
  • Enrico D’Elia

    (Ministry of Economy and Finance of Italy)

  • Francesca Faedda

    (Ministry of Economy and Finance of Italy)

  • Giacomo Giannone

    (Ministry of Economy and Finance of Italy)

Abstract

Le entrate tributarie mensili lorde di competenza, accertate nel bilancio dello Stato, derivanti da IVA, accise sui prodotti petroliferi e ritenute Irpef (che rappresentano circa il 70% del totale delle entrate tributarie lorde) sono state proiettate utilizzando dei modelli bridge e alcuni indicatori statistici particolarmente tempestivi, come l’indice del fatturato, dell’occupazione, delle retribuzioni contrattuali e delle importazioni. I risultati mostrano che, anche utilizzando modelli piuttosto semplici, è possibile ottenere proiezioni statistiche abbastanza accurate, utilizzabili sia per fini previsivi sia, più propriamente, per il monitoraggio delle entrate e l’individuazione precoce di eventuali scostamenti significativi rispetto alle rispettive previsioni annuali. I modelli descritti in questo lavoro sono di tipo aggregato e come tali si prestano ad integrare ed anticipare le informazioni fornite dai modelli di microsimulazione attualmente utilizzati dal Dipartimento delle Finanze. Tra gli ulteriori impieghi si annovera anche la possibilità di monitorare e prevedere in via sperimentale i flussi di cassa; fornire la stima anticipata di alcuni indicatori macroeconomici a prezzi correnti; valutare l’effetto del ciclo sulle entrate tramite simulazioni dinamiche fuori campione.

Suggested Citation

  • Enrico D’Elia & Francesca Faedda & Giacomo Giannone, 2020. "Un modello statistico per il monitoraggio delle entrate tributarie (MoME)," Working Papers wp2020-5, Ministry of Economy and Finance, Department of Finance.
  • Handle: RePEc:ahg:wpaper:wp2020-5
    as

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    References listed on IDEAS

    as
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    More about this item

    Keywords

    tax revenues forecasting; high-frequency forecasting model; bridge model; Italy tax revenues;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue

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