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Besides promising economic growth, will the Italian NRRP also produce fewer emissions?

Author

Listed:
  • Ilenia Romani

    (Università degli Studi di Brescia and Fondazione Eni Enrico Mattei)

  • Marzio Galeotti

    (Università degli Studi di Milano and Fondazione Eni Enrico Mattei)

  • Alessandro Lanza

    (LUISS and Fondazione Eni Enrico Mattei)

Abstract

The funds allocated by the National Recovery and Resilience Plan (NRRP) aim to trigger a multiplier effect on GDP as they are designed to help the recovery after the Covid-19 pandemic. The GDP increase is in turn expected to drive energy consumption up which will increase CO2 emissions, given that fossil fuels still account for 79% of the Italian total primary energy consumption. At the same time, as the NRRPs are part of the EU Green Deal, an important share of the Plan’s investments is aimed at facilitating the green transition, with expected favorable effects on emissions. Which one of these two effects will prevail remains to be ascertained. In this study we have used the GEM (Global Economic Model) by Oxford Economics to build a number of scenarios and generate the relevant simulations aimed at assessing the impact of the Italian NRRP’s interventions on energy consumption and CO2 emissions. To validate the use of GEM we extensively considered the macroeconomic impact on GDP and unemployment rate generated by the model and compare the results to those presented by other institutions and obtained using different models. The results show that when the green investments of the NRRP display their effects, there are climatic benefits in terms of reduced emissions. Compared to the implementation of the NRRP in 2021, however, the reduction in emissions by 2030 is modest and equal to 5%. As those investments largely refer to the adoption of clean technologies, the climate benefits are likely to be more substantial only in subsequent years and over longer horizons.

Suggested Citation

  • Ilenia Romani & Marzio Galeotti & Alessandro Lanza, 2022. "Besides promising economic growth, will the Italian NRRP also produce fewer emissions?," Working Papers 2022.08, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2022.08
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    1. Fabio Bacchini & Cristina Brandimarte & Piero Crivelli & Roberta De Santis & Marco Fioramanti & Alessandro Girardi & Roberto Golinelli & Cecilia Jona-Lasinio & Massimo Mancini & Carmine Pappalardo & D, 2013. "Building the core of the Istat system of models for forecasting the Italian economy: MeMo-It," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 15(1), pages 17-45.
    2. Janos Varga & Jan in 't Veld, 2014. "The potential growth impact of structural reforms in the EU. A benchmarking exercise," European Economy - Economic Papers 2008 - 2015 541, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
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    More about this item

    Keywords

    National Recovery and Resilience Plan; CO2 emissions; Large-scale macroeconomic model; Post-Covid recovery;
    All these keywords.

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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