metadata: authors: 0: author: Orecchia,Carlo
1: author: Cala,Valerio Ferdinando
2: author: de Cristofaroa,Fabiana
3: author: Dudu,Hasan
count: Italy
docna: 0: docna: Assessing the Efficiency and Fairness of the
            Fit for 55 Package toward Net Zero Emissions under Different
            Revenue Recycling Schemes for Italy
docty: Policy Research Working Paper
abstracts: cdata!: One of Italy&#x2019;s key objectives
            is to reform and modernize the tax system to increase tax
            efficiency and improve environmental sustainability and
            regional economic outcomes, in line with the European Union
            strategy.  Within the framework of the European Green Deal,
            Italy is committed to contributing to the goal of becoming
            the first climate neutral region by 2050 (the
            &#x201c;Fit for 55&#x201d; package). As an
            intermediate step toward the 2050 target, the European Union
            must reduce greenhouse gas emissions by at least 55 percent
            by 2030 compared to 1990 levels. Carbon pricing is at the
            core of the proposal, but its full implementation is also
            expected to have regressive effects, harming poorer
            households, and adverse economic impacts, reducing
            firms&#x2019; competitiveness. This paper evaluates the
            effects of the carbon pricing proposal of the
            &#x201c;Fit for 55&#x201d; package on welfare,
            sectoral production, and income distribution. To tackle the
            adverse social and economic effects, it compares different
            revenue recycling schemes shifting the tax burden from major
            direct and indirect taxes to carbon emissions. It finds that
            well-targeted revenue recycling policies might significantly
            reduce the negative effects. The analysis adopts the Italian
            Regional and Environmental Computable General Equilibrium of
            the Department of Finance model, which is a new (recursive)
            dynamic computable general equilibrium model developed by
            the Italian Ministry of the Economy with technical
            assistance from the World Bank. It has a detailed energy
            specification that allows for capital/labor/energy
            substitution in production, intra-fuel energy substitution
            across all demand agents, a multi-output and multi-input
            production structure, an extended energy system with 11
            different types of technologies, multiple households to
            address distributional impacts, and detailed information on
            the Italian tax system.
display_title: Assessing the Efficiency and
            Fairness of the Fit for 55 Package toward Net Zero Emissions
            under Different Revenue Recycling Schemes for Italy
listing_relative_url: /research/2023/10/34186262/assessing-efficiency-fairness-fit-55-package-toward-net-zero-emissions-under-different-revenue-recycling-schemes-italy
topicv3: Carbon Pricing m1327308 1846,Dynamic Computable General Equilibrium
            m1439225 3111
publishtoextweb_dt: 2023-10-26T00:00:00Z
dois: 10.1596/1813-9450-10592
author_keys: 0: author_key: 921249
1: author_key: NA
2: author_key: NA
3: author_key: 911597
model_extractions: Policy Research Working Paper 10592 Assessing the Efficiency and Fairness of the Fit for 55 Package toward Net Zero Emissions under Different Revenue Recycling Schemes for Italy _Carlo Orecchia Valerio Ferdinando Cala Fabiana de Cristofaro Hasan Dudu_ Macroeconomics, Trade and Investment Global Practice October 2023
Policy Research Working Paper 10592

# **Abstract**

One of Italy’s key objectives is to reform and modernize the tax system to increase tax efficiency and improve environmental sustainability and regional economic outcomes, in line with the European Union strategy. Within the framework of the European Green Deal, Italy is committed to contributing to the goal of becoming the first climate neutral region by 2050 (the “Fit for 55” package). As an intermediate step toward the 2050 target, the European Union must reduce greenhouse gas emissions by at least 55 percent by 2030 compared to 1990 levels. Carbon pricing is at the core of the proposal, but its full implementation is also expected to have regressive effects, harming poorer households, and adverse economic impacts, reducing firms’ competitiveness. This paper evaluates the effects of the carbon pricing proposal of the “Fit for 55” package on welfare, sectoral production, and income distribution. To tackle the adverse social and economic effects, it compares different revenue recycling schemes shifting the tax burden from major direct and indirect taxes to carbon emissions. It finds that well-targeted revenue recycling policies might significantly reduce the negative effects. The analysis adopts the Italian Regional and Environmental Computable General Equilibrium of the Department of Finance model, which is a new (recursive) dynamic computable general equilibrium model developed by the Italian Ministry of the Economy with technical assistance from the World Bank. It has a detailed energy specification that allows for capital/ labor/energy substitution in production, intra-fuel energy substitution across all demand agents, a multi-output and multi-input production structure, an extended energy system with 11 different types of technologies, multiple households to address distributional impacts, and detailed information on the Italian tax system.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at hdudu@imf.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Assessing the Efficiency and Fairness of the Fit for 55 Package toward Net Zero Emissions under Different Revenue Recycling Schemes for Italy**<sup>**1**</sup>

by _Carlo Orecchia_<sup>_a_</sup> **,** _Valerio Ferdinando Cala_<sup>_a_</sup> _, Fabiana de Cristofaro_<sup>_a_</sup> _, Hasan Dudu_<sup>_b_</sup> a Department of Finance; Italian Ministry of Economy and Finance, Italy.

b International Monetary Fund. Hasan Dudu was with the World Bank during the preparation of the working paper.

> 1 This paper has been developed at the Department of Finance-Italian Ministry of Economy and Finance under the project ‘Improving the evaluation of VAT and excise tax policies in Italy’, funded by the European Union in collaboration with DG Reform and the World Bank. We are particularly grateful to Maria Teresa Monteduro, Marco Manzo, Paolo Di Caro, Silvia Carta, Gavino Mura, Jan Ignacy Witajewski-Baltvilks, Maria Alessandra Tullio, Elisa Fusco, Pasquale Giacobbe, Francesca Laratta, Lorenzo Marchetti, Alessio Marabucci, Louise Wandhal-Jensen. We wish to thank also SOGEI spa for the support. The views expressed in the paper do not reflect those of the institutions of affiliation. The usual disclaimer applies.
# **1 Introduction**

Green transition is becoming more pressing than ever, both in the context of climate change and in the energy crisis scenario caused by the Russian invasion of Ukraine. To face the climate change challenge, the European Green Deal (see EU 2020), adopted in 2020, sets the path to make the EU's climate, energy, transport, and taxation policies fit for efficiently facing the environmental degradation threat. As part of the European Green Deal, with the European Climate Law, EU Member States agreed on the ambitious target of achieving climate neutrality by 2050, under the so-called “Fit for 55” package. In accordance with this set of measures, as an intermediate step, Member States are pledged to reduce emissions by at least 55% by 2030, compared to 1990 levels. The significant commitment thereof comes as an opportunity for developing new policy evaluation tools, especially in the new energy crisis scenario that seems to undermine the achievement of the ambitious “Fit for 55” goals. The increase in energy prices and the worsening of international relations with the Russian Federation are already influencing economic activity, employment, and household living conditions so that new policy strategies are needed. Developing and testing new economic models featuring detailed energy structure can play an important role in designing quick policy responses and assessing options for the energy crisis.

This paper has two main research objectives, which are novel contributions to the existing literature. From a methodological perspective, we present the Italian Regional and Environmental Computable General Equilibrium of the Department of Finance (IRENCGE-DF, henceforth), which seeks to answer to the new current policy needs. As we shall see, IRENCGE-DF’s structure makes it very topical and extremely useful for analyzing different policy scenarios coming either from the EU legislation or from the international political scenario. The IRENCGE-DF is a single-country CGE model with regional and environmental modules, tailored to the specific Social Accounting Matrix (SAM) built for Italy. It is a multi-sector, multi-household CGE model, based on a set of equations which aim to capture the structure of the economy and behavioral response of agents such as firms, households, government, and the rest of the world. This provides a very rich framework to simulate the policy changes and trace the impact on the key economic variables, including income and expenditure flows. The model incorporates an environmental module which features a detailed energy specification that allows for capital/labor/energy substitution in production, intra-fuel energy substitution across all the demand agents, a multi-output multi-input production structure, an energy system extended with 11 different types of technologies including renewable and clean energy, and an extended environmental policy that can allow simulation of the effects of carbon tax and carbon emission on different sectors.

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From a policy perspective, the comprehensive environmental and tax structure of the IRENCGE-DF model makes it well suited for analyzing a wide range of policy scenarios. In particular, the “Fit for 55” package is analyzed in the model by limiting the level of emissions and letting the model calculate the endogenous price consistent with this cap. Thanks to the extensive focus on tax modeling, the IRENCGE-DF model is able to properly fit scenarios with new structures of tax rates based on the energy content and environmental performance of the fuels and electricity and also to simulate broader taxable bases by including more products in the scope and by removing some of the current exemptions and reductions. Several simulation scenarios will be discussed in the following sections.

The remainder of the paper is organized as follows. In Section 2, we present the data and methodology, reviewing the main aspects of the IRENCGE-DF model. In the Section 3, we present the results of our policy simulations. The final section concludes with some policy implications.

# **2 Data and Methodology**

# **2.1 SAM Construction**

The model is calibrated on the 2017 SAM. We update the benchmark data to 2020 by using macroeconomic variations resulting from the latest public economic and financial documents (i.e. Italian annual budget law, etc.).

The information contained in the SAM is obtained by combining national account data, such as the national account matrix for 2014, supply-use tables for 2017, and Eurostat data. In addition, we integrate missing information with data from tax returns available at the Department of Finance.

National accounts data provide detailed information on the final and intermediate consumption at activity and commodity levels, though they do not contain detailed information on taxation. Hence, we use the tax return data to distribute taxes and subsidies per commodity. In Table 1, we provide a description of the sets and structure used in the analysis. For the purpose of this study, the SAM distinguishes between 77 activities, 68 commodities, 10 household groups and 10 tax categories.

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_Table 1: Sets used in model definition_

|_Set_<br><br>|_Description_|
|---|---|
|i<br><br>|Full set of SAM Accounts|
|a(i)<br><br>|Set of Armington agents—includes all production activities and final demand|
|a(a)<br><br>|Set of production activities|
|oa(a)<br><br>|Other Armington agents—mostly final demand accounts|
|f(oa)<br><br>|Final demand accounts (excludes the trade and transport margin accounts)|
|h(oa)<br><br>|Household accounts|
|f(oa)<br><br>|Other final demand accounts|
|i(i)<br><br>|Commodities|
|e(i)<br><br>|Energy commodities|
|i(i)<br><br>|Non-energy commodities|
|k<br><br>|Consumed commodities|
|in(k)<br><br>|The energy bundle in consumed commodities|
|ii(i)<br><br>|Institutions (for transfers)|
|f(i)<br><br>|Factors of production|
|l(f)<br><br>|Labor categories|
|ul(l)<br><br>|Unskilled labor types|
|il(k)<br><br>|Skilled labor types|
|lif(f)<br><br>|Land types|
|caf(f)<br>|Capital types|
|v|Vintages (Old and New)|

_Table 2: sectoral coverage_

|**Agriculture**|**Sewerage-Waste**|
|---|---|
|**Forestry**|Construction|
|**Fishing**|Trade-of-motor-vehicles|
|**Mining**|Wholesale-trade|
|**Coal**|Retail-trade|
|**Oil**|Land-transport|
|**Gas**|Water-transport|
|**Food-products**|Air-transport|
|**Textiles**|Warehousing-and-stransportation|
|**Wood**|Postal|
|**Paper**|Accommodation-food-serv|
|**Printing**|Publishing|
|**Coke-and-pp**|Motion-picture-TV|
|**Chemicals**|Telecommunications|
|**Pharmaceutical**|Computer-prog-Information-serv|
|**Rubber-and-plastic**|Financial-serv|
|**Non-metallic-mineral-products**|Insurance|
|**Basic-metals**|Aux-to-financial-svcs-insurance|
|**Metal-products**|Real-estate|

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|**Computer-electronic**|Legal-accounting-consultancy|
|---|---|
|**Electrical-equipment**|Architectural-engineering|
|**Machinery-Equipment-nec**|Scientific-research-development|
|**Motor-vehicles-trailers**|Advertising|
|**Other-transport-equipment**|Other-professional-Veterinary|
|**Furniture-Other-manufacturing**|Rental-leasing|
|**Repair-installation**|Employment-activities|
|**Transmission and Distrib.**|Travel-agency-Tourism|
|**CoalBL**|Other-serv|
|**GasBL**|Public-administration|
|**WindBL**|Education|
|**HydroBL**|Health|
|**OilBL**|Residential-care|
|**OtherBL**|Creative-arts-cultural|
|**GasP**|Sports|
|**HydroP**|Membership-organisations|
|**OilP**|Repair-of-computers-and-personal-goods|
|**SolarP**|Other-personal-serv|
|**Gdt**|Households|
|**Water**||

# **_Taxes_**

Information on major taxes in Italy is obtained by reconciling tax return data with information from Istat (the Italian National Institute of Statistics) national accounts. Among commodity taxes in the model, the following are explicitly considered:

- Value Added Tax (VAT), whose aggregate amount is published by the Istat, is allocated by commodity according to the VAT Microsimulation Model developed by the Department of Finance (DF). The VAT DF Microsimulation Model estimates VAT by commodity distinguishing between final consumption of households, intermediate goods and capital goods.

- Excises, published by Istat with the details of the goods they are imposed on, have been allocated by commodity accordingly and associated to both intermediate and final consumption using the use table from Istat.

- Tariffs on Imports are computed by applying estimated import tariffs to imports.

- Other Net Tax on Products (other indirect taxes less subsidies on products) are calculated as a residual by subtracting VAT, excises and tariffs on imports by commodity from the net indirect taxes on products published by Istat in the Supply table for 2017.

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Taxes by activity explicitly considered are the following:

- Corporate income tax IRES (“Imposta sul reddito delle società”) and the regional production tax IRAP (“Imposta regionale sulle attività produttive”) are added together and disaggregated by activity using tax return data available at DF (the Department of Finance). The implicit tax rates are calculated using the operating surplus as a tax base and will increase the cost of capital used by each firm.

- Social Security contributions paid by the employer (SSCs Employer) are retrieved from the use table, defined as the difference between employee income of regular workers and gross wages by sector of economic activity; subsequently, this value is classified according to the type of skill category: low skilled, skilled, and high skilled.

- Other taxes on production are published by Istat by sector. As IRAP is considered with IRES as a separate entry in the SAM, its amount is subtracted to obtain the other taxes on production as the residual value.

Finally, households’ direct taxes are included in the model and treated as a single entry that combines income taxes (imposta sui redditi delle persone fisiche (IRPEF)) and IRPEF surcharges, substitutive taxes (forfeit mixed, rents, capital income taxes etc.) and other special regimes and social security contribution paid by the employee.

# **2.2 The IRENCGE-DF Model**

## **_Model Overview_**

The Italian Regional and Environmental Computable General Equilibrium of Department of Finance (IRENCGE-DF) Model is a (recursive) dynamic single country computable general equilibrium (CGE) model that is developed by the Italian Ministry of the Economy with technical assistance from the World Bank. It is based on the MANAGE-WB model of the World Bank (World Bank, 2023), which is in turn based on the MANAGE model that is documented in van der Mensbrugghe (2021).

IRENCGE-DF is designed to focus on energy, emissions and climate change. In addition to the standard features of a single country CGE model, the IRENCGE-DF model includes a detailed energy specification that allows for capital/labor/energy substitution in production, intra-fuel energy substitution across all demand agents, and a multi-output multi-input production structure. Furthermore, the model introduces household heterogeneity to better analyze the impacts of environmental and energy policies on welfare and inequality and disaggregates the representative household into ten household groups. The sources of income and consumption structure reflect the 6
information coming from statistical households’ surveys. Labor growth is exogenous. Capital accumulation derives from savings/investment decisions. The model has a vintage structure for capital that allows for putty/semi-putty assumptions with sluggish mobility of installed capital.

The model allows for a wide range of productivity assumptions that include autonomous improvements in energy efficiency that can differ across agents and energy carriers. The model can be calibrated to different SAMs that follow a standard set of conventions in representing the economic structure. The model is implemented in the General Algebraic Modeling System (GAMS) software and an aggregation facility is used as a front-end to the model to allow for full aggregation flexibility.

# **_Model Description_**

The IRENCGE-DF model is a recursive dynamic computable general equilibrium (CGE) model. Each year, a scenario is solved as a static equilibrium, with dynamic equations linking exogenous factors (such as population growth and capital accumulation) across years with, in addition, update equations for productivity factors. Each static equilibrium relies on a relatively standard set of equation specifications.

Production is modeled using a series of nested constant-elasticity-of-substitution (CES) functions designed to capture the substitutions and complements across the different inputs, notably capital and labor, but also with a focus on energy as energy policies are one of the key objectives of the IRENCGE-DF model. Energy is assumed to be a near-complement with capital in the short-run, but a substitute in the long-run. Thus, rising energy prices tend to lead to rising production costs in the short-run when substitution is low, but a long-run response would lead to energy-saving technologies that dampen the cost-push factor. This feature of the model is embodied in a vintage capital structure that captures the semi-putty/putty relations across inputs with more elastic long-run behavior as compared to the short-run.

The model allows for both multi-input and multi-output production. The former, for example, would allow for electricity supply to be produced by multiple activities—thermal, hydro, solar and other renewable forms of electricity production. The latter allows for a single activity to produce more than one product—for example, oil seed crushing produces both vegetable oils and oil cakes (for feed).

Labor and capital income are largely allocated to households with pass-through accounts to enterprises. Government revenue is derived from both direct and indirect taxes.

Households are disaggregated into ten income groups and their demand is modeled using the constant-differences-in-elasticity (CDE) demand function that is the standard utility function used in the Global Trade Analysis Project (GTAP) model. The model allows for a different specification of 7
demanded commodities (indexed by k) from supplied commodities (indexed by i). A transition matrix approach is used to convert consumer goods to supplied goods that also relies on a nested CES approach. The transition matrix is largely diagonal in the current version with consumed commodities directly mapped to supplied commodities. Energy demand is bundled into a single commodity and disaggregated by energy type using a CES structure that allows for inter-fuel substitution. Other final demand is handled similarly, though the aggregate expenditure function is a CES function rather than the CDE.

Goods are evaluated at basic prices with tax wedges. The model incorporates trade and transport margins that add an additional wedge between basic prices and end-user prices. The trade and transport margins are differentiated across transport nodes-farm/factory gate to domestic markets and the border (for exports), and from port to end-user (for imports).

Import demand is modeled using the ubiquitous Armington assumption, i.e., goods with the same nomenclature are differentiated by region of origin. This allows for imperfect substitution between domestically produced goods and imported goods. The level of the CES elasticity determines the degree of substitutability across regions of origin. Domestic production is analogously differentiated by region of destination using the constant-elasticity-of-transformation (CET) function. The ability of producers to switch between domestic and foreign markets is determined by the level of the CET elasticity. The model allows for perfect transformation in which case the law-of-one price must hold.

Market equilibrium for domestically produced goods sold domestically is assumed through market clearing prices. By default, the small country assumption is assumed for export and import prices and thus they are exogenous, i.e., export levels do not influence the price received by exporters and import demand does not influence (CIF) import prices. The model does allow for implementation of an export demand schedule and an import supply schedule in which case the terms-of-trade would be endogenously determined.

The current version of the model assumes market clearing wages on the labor markets with the possibility of an upward sloping labor supply schedule and sluggish mobility of labor across sectors. Introduction of more labor market segmentation (for example rural versus urban) and some form of wage rigidity could be readily implemented.

In dynamic simulations, new capital, i.e. that generated by recent investments, is allocated across sectors so as to equalize the rate of return across sectors. Old capital remains installed in its original sector unless the sector is in decline. A sector in decline is one in which potential supply, as measured by the capital/output ratio, exceeds ex post demand. This can occur from a variety of shocks that 8
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activities. In addition, revenues from carbon pricing can be used to lower existing distortionary taxes with the aim of promoting both greater efficiency and equity in the tax system. To evaluate the economic appeal of alternative reforms, we start from a reference scenario (Baseline) that represents future demographic, energy and emissions evolution under current policy legislation. Then a set of policy scenarios are evaluated which implement the climate mitigation measures to achieve the fitfor55 emissions reductions. The policy measures are represented through the introduction of carbon prices and are compared with respect to the baseline scenario to estimate the policy impacts. Scenarios cover the 2021-2030 timeframe.

|**Scenarios**|**Description**|
|---|---|
|Baseline|Continuation of current policies: 40% reduction in GHGs compared to 1990|
|Fit55|Increased climate ambition to achieve 55% emissions reduction target|
|Fit55 – Wage<br>tax|Fit for 55 with additional carbon revenues recycling to reduce Labour taxes (i.e. Social Security<br>Contributions paid by the employer, SSCer) – revenue-neutral reform|
|Fit55 – CIT|Fit for 55 with additional carbon revenues recycling to reduce corporate income taxes (IRAP and IRES)<br>– revenue-neutral reform|
|Fit55 – VAT|Fit for 55 with additional carbon revenues recycling to reduce VAT – revenue-neutral reform|
|Fit55 – Excises|Fit for 55 with additional carbon revenues recycling to reduce Excises – revenue-neutral reform|
|Fit55 – Income<br>tax|Fit for 55 with additional carbon revenues recycling to reduce households' income taxes - revenue-<br>neutral reform|

The baseline scenario replicates trends of the Gross Domestic Product (GDP) from the International Monetary Fund’s (IMF, 2021). To capture the expected energy and emission trends, some assumptions on energy-related variables are assumed: costs of renewable electricity generation decline over time, non-price related changes in preferences in favor of renewables, increases in electricity shares for the final and intermediate consumers, improvements in energy efficiency. In addition to these assumptions, in the baseline scenarios we also introduce carbon prices to replicate the current climate targets ambition (see Figure 2). Under these assumptions, GHGs emissions are declining considerably in the baseline scenario to achieve a reduction of at least 40% (from 1990 levels). The fitfor55 policy scenarios raise the 2030 greenhouse gas emission reduction target, 10
<!-- Start of picture text --> (MtCO,e)<br>600<br>518<br>500<br>432 -40% -55%<br>400<br>333<br>300 261<br>200<br>100<br>0 Historical Historical Baseline “Fitforss:<br>~100 1990 2017 2030 2030<br>Hnon-ETS METS wm Lulucf<br><!-- End of picture text -->
<!-- Start of picture text --> (% change wrt Bau) GDP<br>0.1<br>0.0<br>2022 2027 2028 2029 2030<br>01<br>-0.2<br>-0.3<br>-0.4<br>-0.5<br>-0.6<br>oe 55, em 55 & wage tax ome (55 & CIT<br>om £55 & VAT em 55 REXCISES = =e f55 & Income tax<br><!-- End of picture text -->
two aspects deepen the inefficiency across sectors as some incur very high abatement costs to reduce carbon emissions while others do not abate even when their abatement costs are significantly low. On the contrary, with a uniform carbon price endogenously determined by the model, all profitmaximizing firms will reduce emissions up to the point where marginal abatement costs are equal to the carbon tax rate ensuring that the required level of emissions reduction is achieved at least cost. Finally, as shown in Bohringer et al. 2008 and 2016, overlapping regulation can determine efficiency losses as the use of multiple policy instruments to curb greenhouse gas emissions as it is in the presence of a comprehensive emission pricing and energy taxes can cause what is defined as “excess cost”. Thus, the cut of energy taxes could reduce this additional cost due to the overlapping regulation.

_Table 3: Macroeconomic results in 2030 (% change wrt Baseline)_

|**Scenarios**|**consumption**|**gov.**<br>**Expend.**|**investment**|**public**<br>**investment**|**export**|**import**|**gdp**|**Gini index**<br>_(Average_<br>_2022-2030)_|
|---|---|---|---|---|---|---|---|---|
|f55|-0.9|-0.5|0.4|-0.5|-1.0|-1.3|-0.5|0.009|
|f55 & wage tax|-0.6|-0.4|0.1|-0.4|-0.9|-1.2|-0.4|0.004|
|f55 & CIT|-0.5|-0.3|0.0|-0.3|-0.9|-1.1|-0.3|0.001|
|f55 & VAT|-0.5|-0.4|-0.6|-0.4|-1.0|-1.3|-0.4|-0.006|
|f55 & EXCISES|-0.3|-0.3|-0.5|-0.3|-0.8|-1.0|-0.3|-0.004|
|f55 & Income tax|-0.7|-0.5|-0.1|-0.5|-1.0|-1.3|-0.5|-0.006|

In terms of income distribution, we can look at the Gini index (average 2022-2030). From Table 3, we can observe that there are regressive effects on income distribution in the “f55” scenario to comply to the stringent climate policy constraints. The negative impacts on income distribution are reduced in all recycling schemes. The Gini index slightly declines in some scenarios with the largest reductions in the “f55 & Income tax” and “f55 & VAT” recycling schemes where carbon revenues are used to reduce the personal income tax and VAT tax.

In Figure 4, welfare impacts are differentiated across household deciles. We observe that welfare effects differ significantly across households, with poorer households bearing a disproportional 13
<!-- Start of picture text --> (% change wrtBaseline) Welfare impacts in 2030<br>0.00<br>-0.20<br>-0.30<br>-0.40<br>-0.50<br>-0.60<br>-0.70<br>-0.80<br>-0.90<br>H-Decl H-Dec2 H-Dec3 H-Dec4 H-DecS H-Dec6 H-Dec? H-Dec8 H-Dec9 H-Decx<br>mf55 mf55&wagetax mfSS&CIT mf55&VAT mf55&EXCISES mf55 & Income tax<br><!-- End of picture text -->
<!-- Start of picture text --> (% change wrt Bau) Fossil fuels and energy-intensive industry sectors<br>5.0<br>0.0 =| = se =| i“wa =<br>-5.0<br>-10.0<br>150<br>-20.0<br>-25.0<br>£55 £55 & wage tax £55 & CIT £55 & VAT £55 & EXCISES £55 & Income tax<br>ma-Coal mail ma-Gas<br>@a-Coke-and-pp a-Chemicals Wa-Rubber-and-plastic<br>@a-Non-metallic-mineral-products TM a-Basic-metals Wa-Land-transport<br>Wa-Water-transport We-Air-transport<br><!-- End of picture text -->

<!-- Start of picture text --> (% changewrt Bau) Electricity<br>15.0<br>10.0<br>0.0 lil il<br>-5.0<br>-10.0<br>-15.0<br>-20.0<br>-25.0<br>30.0<br>35.0<br>£55, £55 & wage tax £55 & CIT £55 & VAT £55 & EXCISES £55 & Income tax<br>@a-CoalBL Ma-GasBL Ma-WindBL Ma-HydroBL Ma-OilIBL Ma-OtherBL Ma-OilP Ma-SolarP<br><!-- End of picture text --> <!-- Start of picture text --> (% change wrt Bau) other activities<br>25<br>2.0<br>15<br>1.0<br>0.0 alll als | | | I. | |<br>. £55, £55 & wage tax £55 & CIT | £55 & VA- £55 & EXCI!a” £55 & Income. tax<br>-0.5<br>@ a-Textiles @ a-Metal-products @ a-Computer-electronic<br>®@ a-Electrical-equipment @ a-Machinery-Equipment-nec @ a-Motor-vehicles-trailers<br>@ a-Other-transport-equipment @ a-Computer-prog-Information-serv @ a-Architectural-engineering<br>@ a-Scientific-research-development<br><!-- End of picture text -->
# **4. Concluding Remarks**

In this paper, we analyzed the effects on the Italian economy of an increasing reduction over time of GHG emissions to meet the target required by the Fit for 55 EU proposal by 2030. We adopt the IRENCGE-DF model, a new (recursive) dynamic computable general equilibrium (CGE) model developed by the Italian Ministry of the Economy and the World Bank. The model endogenously calculates a carbon price to comply with the desired level of emissions abatement simulating the behavior of agents based on optimizing microeconomic theory. Carbon price negatively impacts the performance of the Italian economy, reducing GDP by 0.5% in 2030 compared to our reference scenario. Regressive effects on income distribution are also observed in this scenario considering the change in the Gini index. To tackle the adverse social and economic effects, we compared different revenue recycling schemes shifting the tax burden from major direct and indirect taxes to carbon emissions. It turns out that recycling carbon revenues can significantly reduce the negative impacts on GDP and welfare. In particular, the most cost-effective recycling schemes are with excises and corporate income taxes, with GDP decreasing by -0.5% to -0.3%. Although differences are small in size, the use of carbon revenues to reduce VAT and Personal Income Tax are found to be the most desirable recycling options in terms of equity and income distribution.

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