The implications of high energy and carbon prices on firms

Yakut, Aykut Mert; McArdle, Samuel; De Bruin, Kelly C. Research Report The implications of high energy and carbon prices on firms Research Series, No. 179 Provided in Cooperation with: The Economic and Social Research Institute (ESRI), Dublin Suggested Citation: Yakut, Aykut Mert; McArdle, Samuel; De Bruin, Kelly C. (2024) : The implications of high energy and carbon prices on firms, Research Series, No. 179, The Economic and Social Research Institute (ESRI), Dublin, https://doi.org/10.26504/RS179 This Version is available at: https://hdl.handle.net/10419/298381 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ THE IMPLICATIONS OF HIGH ENERGY AND CARBON PRICES ON IRISH FIRMS AYKUT MERT YAKUT, SAMUEL MCARDLE AND KELLY DE BRUIN RESEARCH SERIES NUMBER 179 APRIL 2024 E V I D E N C E F O R P O L I C Y THE IMPLICATIONS OF HIGH ENERGY AND CARBON PRICES ON IRISH FIRMS Aykut Mert Yakut Samuel McArdle Kelly de Bruin April 2024 ESRI RESEARCH SERIES NUMBER 179 Available to download from www.esri.ie ©The Economic and Social Research Institute Whitaker Square, Sir John Rogerson’s Quay, Dublin 2 https://doi.org/10.26504/rs179 This Open Access work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. ABOUT THE ESRI The Economic and Social Research Institute (ESRI) advances evidence-based policymaking that supports economic sustainability and social progress in Ireland. ESRI researchers apply the highest standards of academic excellence to challenges facing policymakers, focusing on ten areas of critical importance to 21st Century Ireland. The Institute was founded in 1960 by a group of senior civil servants led by Dr T.K. Whitaker, who identified the need for independent and in-depth research analysis. Since then, the Institute has remained committed to independent research, and its work is free of any expressed ideology or political position. The Institute publishes all research reaching the appropriate academic standard, irrespective of its findings or who funds the research. The ESRI is a company limited by guarantee, answerable to its members and governed by a Council comprising up to 14 representatives drawn from a cross-section of ESRI members from academia, civil services, state agencies, businesses and civil society. Funding for the ESRI comes from research programmes supported by government departments and agencies, public bodies, competitive research programmes, membership fees, and an annual grant-in-aid from the Department of Public Expenditure, NDP Delivery and Reform. Further information is available at www.esri.ie THE AUTHORS Aykut Mert Yakut is a Research Officer at the Economic and Social Research Institute (ESRI) and is an Adjunct Assistant Professor at Trinity College Dublin (TCD), Samuel McArdle is a Research Assistant at the ESRI, and Kelly de Bruin is a Senior Research Officer at the ESRI and is an Adjunct Associate Professor at TCD. ACKNOWLEDGEMENTS The research carried out in this report was funded by the Department of Enterprise, Trade and Employment (DETE) and is part of an ongoing modelling programme funded by the Department of Environment, Climate and Communications (DECC). This report has been accepted for publication by the Institute, which does not itself take institutional policy positions. The report has been peer-reviewed prior to publication. The authors are solely responsible for the content and the views expressed. Table of Contents | iv TABLE OF CONTENTS LIST OF TABLES ....................................... v LIST OF FIGURES ....................................... v ABBREVIATIONS ....................................... vi EXECUTIVE SUMMARY ................................... vii Introduction....................................... vii MainFindings...................................... viii CHAPTER 1 INTRODUCTION ................................ 1 CHAPTER 2 METHODOLOGY AND SCENARIOS ....................... 5 2.1 TheI3EModel................................... 5 2.1.1 Households................................ 6 2.1.2 Production and Investment . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.3 Government ............................... 12 2.1.4 LabourMarket .............................. 14 2.2 Scenarios ..................................... 16 CHAPTER 3 RESULTS .................................... 18 3.1 Macroeconomic Aggregates . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 3.2 SectoralImpacts.................................. 22 CHAPTER 4 CONCLUSION .................................. 29 REFERENCES ......................................... 32 APPENDIX .......................................... 37 A AdditionalTables ................................. 37 v|The Implications of High Energy and Carbon Prices on Irish Firms LIST OF TABLES Table 2.1: Scenario Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Table 3.1: Macroeconomic Results of Main Scenarios, % change w.r.t. BaU . . . . . 18 Table 3.2: Aggregated Sectoral Results . . . . . . . . . . . . . . . . . . . . . . . . 23 Table 3.3: Manufacturing Sectors Results, % change w.r.t. BaU . . . . . . . . . . . 27 Table A.1: List of Commodities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Table A.2: List of Activities and Aggregation Key . . . . . . . . . . . . . . . . . . . 38 LIST OF FIGURES Figure 2.1: Interlinkages within the I3E Model . . . . . . . . . . . . . . . . . . . . 5 Figure 2.2: Nested Structure of Consumption . . . . . . . . . . . . . . . . . . . . . 7 Figure 2.3: Nested Structure of Electricity Production . . . . . . . . . . . . . . . . 10 Figure 2.4: Nested Structure of Production, Except Electricity Production . . . . . . 11 Abbreviations | vi ABBREVIATIONS CGE Computable General Equilibrium CPI Consumer Price Index CRRA Constant Relative Risk Aversion DECC Department of Environment, Climate and Communications DETE Department of Enterprise, Trade and Employment ETS Emissions Trading System EU ETS European Union Emissions Trading System FOC First-order Condition GDP Gross Domestic Product GHG Greenhouse Gases I3E Ireland Environment-Energy-Economy LFS Labour Force Survey PP Percentage Points RHGs Representative Household Groups SILC Survey on Income and Living Conditions vii | The Implications of High Energy and Carbon Prices on Irish Firms Executive Summary INTRODUCTION Transitioning to a low-carbon economy requires undertaking massive investment expenditures, and how to finance these expenditures remains at the core of economic debates. However, the cost of not transitioning to a low-carbon economy is often forgotten in these debates. These costs have increased under current global geopolitical tensions, especially for imported fossil fuel-dependent countries, such as Ireland. This report aims to quantify the cost of decarbonisation inaction. What costs will Irish firms face if they continue with their current energy use patterns when the carbon tax (set by the Irish government) and the European Union Emissions Trading System (EU ETS) price (determined by the market conditions at the EU level) are increasing while at the same time, international energy prices are at their extremely high levels? The report utilises the Ireland Environment-Energy-Economy (I3E) model, an intertemporal computable general equilibrium (CGE) model for Ireland, by considering three scenarios describing future energy price developments. Firstly, the impacts of a hypothetical continuation of skyrocketed international energy prices are investigated in the HEP scenario. In this scenario, the price of emissions allowances in the EU, i.e., the EU ETS price and the carbon tax, are fixed at their 2022 level. Secondly, in addition to high international energy prices, the impacts of a gradually increasing Irish carbon tax until 2030 as committed by the government are investigated (CT scenario). Finally, the CT_ETS scenario quantifies the impacts of gradually increasing the EU ETS price along with the carbon tax until 2030 while international energy prices are high and the carbon tax increases following the government-committed trajectory. Since the focus of the report is the implications of the energy and carbon price shocks on the macroeconomic environment and production sectors in Ireland, the results for basic macroeconomic aggregates, the aggregate production sectors, and manufacturing sub-sectors are discussed. However, the details of the distributional implications of the shocks across households, which are available upon request, are only briefly discussed. Methodology and Scenarios | 5 CHAPTER 2 Methodology and Scenarios 2.1 The I3E Model This analysis applies the Ireland Environment-Energy-Economy (I3E) model. The I3E model is an intertemporal computable general equilibrium (CGE) model, which reproduces the structure of the economy in its entirety. It includes production sectors, households, and the government, among others. The model quantifies the nature of all existing economic transactions among diverse economic agents. According to microeconomic behaviour, producers/consumers maximise their profits/utility given their budget constraints. In other words, a CGE model examines how inputs and outputs flow between production sectors of the economy and, finally, result in final goods consumed by households. Figure 2.1 gives an overview of the interlinkages within the I3E model. FIGURE 2.1: INTERLINKAGES WITHIN THE I3E MODEL 6|The Implications of High Energy and Carbon Prices on Irish Firms In the remainder of this chapter, the problems of households and firms will be explained first, and the role of the government and the labour market dynamics will be discussed. A complete technical description of the model and the details of data used in the calibration can be found in de Bruin and Yakut (2021b,a), respectively. The explicit modelling of sectoral interlinkages makes it possible to investigate the wider economic impacts of a specific shock or policy through the different transmission channels in the economy. The model enables us to quantify the impacts of a policy change on the macroeconomic aggregates, labour market, fiscal balances, households, and emissions, as well as on other sectors, i.e. the spillover effect. 2.1.1 Households There are ten representative Household Groups (RHGs) in the model. Each RHG solves the following intertemporal utility maximisation problem where the utility function is in the form of Constant Relative Risk Aversion (CRRA): max CChh,t ∞ ∑ t=11+grwt 1+ρhh t(CChh,t)1−θhh 1−θhh s.t PCChh,tCChh,t+SAVhh,t≤WINChh,t+CINChh,t+TRhh,t+ PENhh,t+FAIhh,t+NMT TRhh,t (2.1) where grwtis the economic growth rate in the period t,ρhh is time preference rate, θhh is intertemporal elasticity of substitution, CChh,tis household-specific composite consumption and PCChh,tis its price, SAVhh,tis savings, W INChh,t,CINChh,t,TRhh,t,PENhh,t,FAIhh,t, and NMTTRhh,tare net-of-tax wage income, net-of-tax capital income (distributed dividends), transfers from the government, pension income from the government, income from foreign asset holdings, and non-means-tested transfer income from the government, respectively. The total values of income items are disaggregated across RHGs based on the share parameters calibrated from the Survey on Income and Living Conditions (SILC). For instance, the total Methodology and Scenarios | 7 net-of-tax wage income received by the labour type lis distributed across households, and WINChh,tis the sum of these incomes over labour types. FIGURE 2.2: NESTED STRUCTURE OF CONSUMPTION CC σ=2 TRP σ=0 LND σ=0 PRV σ=1.2 TElec TDie GAL LTS WTS ATS REN σ=0 RHC σ=1.2 NGS HElec SLD σ=1.5PEA COA LQD σ=0KRS LPG HDie LElec NTR σ=2 AGR FBT SER σ=2 ACC TEL FSR RES PSE ADS PUB EDU HSS OSE OTC σ=2 all other COMs Each RHG chooses the level of composite consumption to maximise the present discounted value of intertemporal utility. The first-order condition (FOC) of this problem, eq. (2.2), is the well-known consumption Euler equation and solves for the sequence of composite consumption where DRt is the domestic interest rate. CChh,t+1 CChh,t =(1+grwt)1+DRt+1 1+ρhh PCChh,t PCChh,t+11 θhh (2.2) 8|The Implications of High Energy and Carbon Prices on Irish Firms The CC is disaggregated across commodities in the second stage based on the consumption nest depicted in Figure 2.2, where Transportation (TRP), Residential Energy (REN), Nourishment (NTR), Services (SER), and other commodities (OTC) are the main composite commodities. The values of elasticity of substitution parameters, σ, are chosen either as 0 or in a range of 1.2 and 2 to reflect the different substitution possibilities across different commodities that constitute the composite commodity.7 2.1.2 Production and Investment Firms are divided into two broad categories: dividend maximisers, dm, and non-dividend maximisers, ndm. The dm firms maximise the present value of the firm (Vdm,t, or equivalently the present discounted value of their dividend streams, DIVdm,t) by choosing the level of physical investment, PSIdm,t, the sector-specific capital, FDdm,k,t, and composite labour, CLDdm,t. max PSIdm,t,FDdm,k,t,CLDdm,t Vdm,t=qdm,tFDdm,k,t= ∞ ∑ t=11+grwt 1+DRtt DIVdm,t s.t(2.3) FDdm,k,t+1= (1−δdm,t)FDdm,k,t+PSIdm,t(2.4) FDdm,k,tevolves according to the capital accumulation function (2.4) and depreciates at the rate δdm,t. The Lagrange multiplier of this maximisation problem is Tobin’s q8: DIVdm,t= (1−corptaxt)FPdm,k,tFDdm,k,t−INVdm,t(2.5) INVdm,t=PPSItPSIdm,t+PVAdm,tADJdm,t(2.6) ADJdm,t=φdm,t PSI2 dm,t FDdm,k,t (2.7) where FPdm,k,tand PPSItare the prices of capital and investment, respectively. The sectoral dividend equals net-of-corporate tax profit minus investment expenditures, INVdm,t, including the cost of new investment 7The full list of commodities is available in Table A.1. 8Tobin’s qis the ratio of the market value of existing capital to its replacement cost, also known as the marginal value of capital. See Hayashi (1982) for further discussion. Methodology and Scenarios | 9 equipment and the adjustment cost, ADJdm,twith a parameter φdm,t, measured by the price of the value added, PVAdm,t. Adjustment cost is an increasing and convex function of investment; for a given level of sectoral capital stock, the cost of installing new capital equipment will be greater. For the given level of φdm,t,qdm,tand δdm,tare calibrated. The FOCs of this dividend maximisation problem w.r.t. the levels of physical investment and capital stock, respectively, are as follows. qdm,t=PPSIt+2PVAdm,t ADJdm,t PSIdm,t (2.8) qdm,t(1+DRt) (1+grwt) = qdm,t+1(1−δdm,t) + PVAdm,t+1 ADJdm,t+1 FDdm,k,t+1 + (1−corptaxt+1)FPdm,k,t+1 (2.9) For the ndm firms, the capital stock accumulates by (2.4) and depreciates at the rate of 0.05, and the investment (by destination) expenditure in period t is a fixed γinvdes ndm,tfraction of its total net-of-corporate tax profits in period t. INVndm,t=γinvdes ndm,tFDndm,k,tFPndm,k,t(1−corptaxt)(2.10) The total value of production, the LHS of eq. (2.11), is equal to payments to factors of production, i.e. value added, production taxes paid to the government, the total cost of intermediate inputs, and the net cost of the Emissions Trading System (ETS). PXa,tQXa,t=PVAa,tVAa,t+PRODTAXSa,t+PCINa,tCCINa,t+ CETSa,t−∑ c CTXADJc,a,t (2.11) where QXa,tis the total production and CCINais composite intermediate input demand; PXa,tand PCINa,tare their prices, respectively. The term (CETSa,t−∑cCTXADJc,a,t) is the net cost of ETS, which excludes carbon tax rebates as firms covered by the ETS are exempt from paying the carbon tax. 10|The Implications of High Energy and Carbon Prices on Irish Firms FIGURE 2.3: NESTED STRUCTURE OF ELECTRICITY PRODUCTION QX σ=2 VA σ=2 K CLD σ=2 LSL MSL HSL BEN σ=1.3 NGS ELC OTE σ=1.5 PEA COA CRO GAL KRS FUO LPG DIE OTI σ=2 All other inputs The production nests of electricity producers and all other sectors are depicted in Figures 2.3 and 2.4, respectively. The production QX is an aggregate of value added (VA), business energy (BEN), and other inputs (OTI). VA is a CES aggregate of factors of production, and OTI is an aggregate of all intermediate inputs but energy. The composite labour is a CES aggregate of three types of labour. For all activities, except electricity production, the commodity BEN is assumed to be an aggregate of energy electricity (EElec), fuel (FUE) and business heating (BH). The values of σBEN and σOTE shown in Figure 2.3 are for the conventional electricity production sector (A_CLC), which uses all energy commodities. However, these parameters are 0 for the electricity producers using wind (A_WND) and other renewables (A_ORE). The coverage of sectoral emissions by the ETS is 100% for the energy production, petroleum refining, mineral, and aviation sectors. On the contrary, land transportation (road or railway), agriculture, waste, and residential sectors are exempted from the ETS but are subject to the Irish carbon tax. For the other sectors, the ETS coverage varies based on the average size of production units regarding the combustion capacity, production capacity, etc. (Environmental Protection Agency (EPA),2018). As the Irish government exempts the ETS emissions from the carbon tax to prevent double taxation, Irish firms subject to the EU ETS legislation must directly internalise both the cost of ETS and the carbon tax exemptions in Methodology and Scenarios | 11 FIGURE 2.4: NESTED STRUCTURE OF PRODUCTION, EXCEPT ELECTRICITY PRODUCTION QX σ=2 VA σ=2 K CLD σ=2 LSL MSL HSL BEN σ1=0, σ2=1.3, σ3=1.5 FUE σ1=0, σ2=1.3, σ3=1.5 GAL KRS FUO LPG DIE EElec BH σ1=0, σ2=1.3, σ3=1.5 PEA COA CRO NGS BElec OTI σ=2 All other inputs their cost minimisation problems. As an example, the optimal level of intermediate input in the composite commodity of business heating (BH) is INTc,a,t="PCINBH,a,tγbh c,a,t PQDc,t+ET SADJc,a,t−CTXADJc,a,t#σbh a,t CCINBH,a,t(2.12) where INTc,a,tis intermediate input demand for commodity cby activity a, CCINBH,a,tis intermediate demand on the composite commodity BH by activity aand PCINBH,a,tis its price, and γbh c,a,tand σbh a,tare share and exponent parameters of the CES function, respectively. The denominator in the parentheses is the sector-specific unit cost of a commodity cfor activity awhere PQDc,tis the purchaser price of commodity c,ETSADJc,a,tis the ETS adjuster and CTXADJc,a,tis the carbon tax exemption adjuster. The values of these adjusters are equal to ET SADJc,a,t=PET StET StoEa,t(1−AtoTa,t)carconc CTXADJc,a,t=PCARtET StoEa,tcarconcαc,t(1+staxc,t)(2.13) where PETStis the EU ETS price of a per tonne emission allowance, ET StoEa,tis ETS emissions-to-total activity emissions ratio, AtoTa,tis the ratio of ETS allowance to ETS emissions of activity, carconcis the carbon 12|The Implications of High Energy and Carbon Prices on Irish Firms emission factor of commodity c,PCARtis the unit carbon tax per tonne eq-CO2,αc,tcaptures the carbon leakages in the economy, and staxc,tis the sales tax rate. As the value of the parameter ET StoEa,tis 0 for non-EU ETS sectors, e.g. land transportation, ET SADJc,a,t=CTXADJc,a,t=0holds and the incurred cost of commodity cis equal to the purchaser price of it, PQDc,t. As PQDc,t includes the carbon tax, the sector bears the carbon tax cost. If ETStoEa,tis positive, the sector must buy new allowances when its total ETS-covered emissions exceed its free allowances. The term ET SADJc,a,tintroduces this cost component into the optimality condition stemming from the cost minimisation problem. As the ETS price, the ETS emissions-to-total emissions ratio, and the carbon content of a commodity increase, the value of ET SADJc,a,talso increases which, in turn, increases the sector-specific incurred unit cost. On the other hand, the higher value of the ratio of the allowances-to-ETS emissions, AtoTa,t, which is an endogenous variable for the given sequence of free allowances, lowers ET SADJc,a,tand thus the incurred unit cost. In other words, a higher level of AtoTa,tdampens the incentives for activities to lower their ETS emissions. Although activity ais exempted from the carbon tax based on its ETS coverage, it pays the carbon tax-inclusive price of commodity c,PQDc,t, at the time of purchase. The term CT XADJc,a,tintroduces the carbon tax exemptions. 2.1.3 Government The government collects direct taxes on labour incomes and sectoral profits, indirect taxes on the sale of commodities, carbon tax on energy commodities, production tax on production activities, export tax on exported commodities, and receives half of the total ETS cost.9It allocates its total revenues to consumption and transfers to households regarding welfare transfers and pensions. The total government consumption of commodities evolves as shown in equation (2.14). GOVCONt=GOVCONAt+mps GDP t(2.14) 9Export tax is positive only for electricity, of which not domestic sales but exports are subject to the carbon tax. Methodology and Scenarios | 13 where GOVCONAtis the autonomous expenditures, fixed in nominal terms, mpstis the marginal propensity to spend, and GDP tis the nominal GDP. The level of welfare transfer to households is a function of both the level of consumer price index (CPI) and the unemployment rate as follows. GTRHHt=GT RHH +gtrhhtunr,tTUNRt+gtrhhcpi,tCPIt(2.15) where GTRHHtis the nominal value of the total government welfare transfers, GTRHH is the fixed transfers, TUNRtis the total unemployment rate, and gtrhhtunr,tand gtrhhcpi,tare positive parameters. The parameters were estimated using a simple Ordinary Least Square estimation procedure covering the period from 2000 to 2019 and then slightly adjusted to ensure the model dynamics were in line with other macroeconomic models for Ireland, e.g., COSMO and HERMES, as explained in de Bruin et al. (2020). The difference between total revenues and expenditures of the government is public savings: GSAVt=GOVREVt−GOVCONt−GTRHHt+ TOTPENtCPIt−r ftGFDSt (2.16) where GTRHHtis the total welfare transfers, TOTPENtis the real value of pension payments to households, r ftis the foreign interest rate, and GFDSt is the debt stock, which grows by the level of government savings: GFDSt+1=GFDSt−GSAVt(2.17) The domestic interest rate, DRt, is one of the main determinants of households’ and firms’ consumption and investment decisions, respectively. DRt=1−πt GSAVt GDP tr ft(2.18) where πtis a positive parameter. Since GSAVT=0holds, DRT=r fTholds, where Tis the terminal period and ensures no-arbitrage condition. In the model, only the government has a debt stock in the economy, and it can borrow from abroad as much as needed to keep its budget balanced. A higher borrowing requirement means that the government dissaves, i.e. 14|The Implications of High Energy and Carbon Prices on Irish Firms GSAVt<0, which makes the domestic interest rate higher than the foreign interest rate as the term in the parentheses is more than 1. In other words, higher government indebtedness increases the risk premium in the domestic market. 2.1.4 Labour Market Net migration flow plays an important buffering role in the Irish labour market. An increase in the wage rate during an economic expansion attracts net migration into Ireland, which, in turn, enlarges the total labour supply and thus hinders further increases in the wage rate. Higher emigration decreases the total labour supply in an economic contraction, preventing larger wage rate declines and stabilising the unemployment rate. The labour market in the I3E model allows involuntary unemployment, international migration, and labour force participation of the Irish population to adjust endogenously to cover all of those aspects. The level of net migration is a function of the wage-income differential between Ireland and the rest of the world. The model incorporates involuntary unemployment and international migration. Total net migration, NMIGt, is a function of the per-employee real net-of-tax wage income differential between Ireland and the rest of the world as follows.10 NMIGt=ζ0,t+ζ1,t(NWINCt−NFWINCtERt)(2.19) where NWINCtand NFWINCtare the per-employee real net-of-tax wage income in Ireland and the rest of the world, respectively. The latter variable is exogenous and fixed in the model, whereas the former is calculated as follows. NWINCt=∑hh WINChh,t CPIt∑a,lLDa,l,t (2.20) 10 Since the I3E model is a single country model, there is no distinction between the source country of migrants. In the related literature, the net migration to Ireland is modelled as a function of the relative employment and wages (Kearney,1998), the wage rate and unemployment rate differentials (Bergin et al.,2013), and the real after-tax earning differential (Bergin et al.,2017) between Ireland and the UK. Results | 21 well-designed Irish welfare system compensates for adverse implications of the labour market outcomes and plays a cushioning role (Savage et al.,2019; Doorley et al.,2021;Yakut and de Bruin,2023). Although the response of the Irish welfare system with respect to inflationary pressures, or cost-of-living crisis in general, is criticised for being ad hoc (PBO,2021;CBO,2022), the total budget of the welfare transfers in the I3E model is a positive function of both the consumer price index and the aggregate unemployment rate. As both variables increase in all scenarios, the total amount of welfare transfers, distributed across households in favour of poorer ones, also increases. Dynamic CGE models converge to a new equilibrium after a shock is introduced. At the new equilibrium, economic agents tend not to change their decisions. This requires any adjustments in the model economy to be completed. In this analysis, the shocks introduced to prices are not completed until 2030. Therefore, the convergence to the new equilibrium continues after 2030. To assess whether this convergence displays new and different dynamics, results for the year 2040 have also been reported in Table 3.1. The results for 2040 are consistent with the results obtained for 2030. The economic contraction continues, with real GDP falling by 0.9%, 1.7%, and 2.1%, in the HEP, CT and CT_ETS scenarios, respectively. This contraction is once more reflected in private consumption expenditures, whereas there are small improvements in investment expenditures compared to the 2030 results. As investment expenditures drive capital accumulation, the slight improvement in these expenditures prevents a larger deterioration in the labour market outcome in 2040 compared to 2030. The improvement in the trade balance, primarily due to the economic contraction, is more pronounced. In the CT_ETS scenario, although the government still receives half of the EU ETS revenues, the increase in the debt-to-GDP ratio becomes larger than that of the CT scenario in 2040. By 2040, the reduction in total emissions reaches 20.6% in the HEP scenario. In the CT and CT_ETS scenarios, total emission reductions reach 32% and 40%, respectively, with the larger falls in ETS emissions driving the decrease. The cumulative emissions reductions in 2040 in the CT_ETS scenario, compared to BaU are 28%, 28%, and 21% in the total, ETS, and non-ETS emissions, respectively. 22|The Implications of High Energy and Carbon Prices on Irish Firms 3.2 Sectoral Impacts The results for the aggregated sectors and the manufacturing sub-sectors are presented in Table 3.2 and Table 3.3, respectively. The modelling of how firms internalise the costs of carbon pricing (carbon tax and EU ETS price) should be reiterated to better understand the sectoral impacts of policy changes. The Irish government exempts the sectoral emissions that fall under the EU ETS from paying the carbon tax to avoid double taxation. However, those firms subject to EU ETS pay the carbon tax when purchasing an energy commodity, as the retail prices include the carbon tax. In the I3E model, like all CGE models, all agents are price-takers, i.e., they pay the same retail price. However, we introduce two components (the so-called ETS and carbon tax adjusters as presented in eq. 2.13) to the optimality conditions of firms’ (eq. 2.12) energy demand to differentiate the unit prices of energy commodities. These adjusters take different values for each sector and energy commodity depending on the EU ETS coverage of sectoral emissions, the sectoral free allowances-to-ETS emissions ratio, the levels of EU ETS price and carbon tax, and the carbon content of the energy commodity. The unit sectorand commodity-specific incurred cost of energy commodity is calculated by the retail price of commodity plus the ETS adjuster minus the carbon tax adjuster. These adjusters are zero if the sector is not subject to EU ETS, e.g., land transportation, mining, and construction, and it only pays the carbon tax. Results | 23 TABLE 3.2: AGGREGATED SECTORAL RESULTS, % CHANGE W.R.T. BAU Sectoral Activity Emissions Value addedaEmployment Non-ETS ETS Cost of ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS Total -0.5 -1.1 -1.4 -0.8 -1.5 -1.8 -18.0 -32.9 -36.1 -23.3 -25.5 -39.5 5.3 0.5 31.1 Agriculture -0.4 -0.8 -0.9 -1.0 -1.8 -2.1 -14.5 -31.6 -32.9 Mining -1.5 -4.7 -6.4 -1.9 -6.6 -8.4 -11.0 -55.3 -57.4 Construction -0.7 -1.5 -1.7 -1.0 -2.0 -2.3 -15.9 -33.5 -34.9 Trade -0.5 -1.1 -1.2 -0.9 -1.7 -2.1 -15.9 -32.2 -33.8 Financial Services 0.0 -0.4 -0.3 -0.5 -1.2 -1.3 -18.4 -34.2 -36.0 Accomm. & Hotel Ser. -0.3 -0.6 -0.7 -0.5 -0.9 -1.0 -15.1 -31.1 -32.4 Public Services -1.2 -1.7 -2.1 -0.8 -1.4 -1.6 -16.1 -32.1 -33.5 Electricity 3.3 1.2 3.7 1.0 -1.1 -0.1 -41.9 -43.4 -66.9 -11.8 -14.1 -8.2 Manufacturing -0.3 -0.8 -1.0 -1.1 -2.0 -2.5 -24.7 -30.3 -40.1 -21.1 -24.6 -38.1 11.4 4.0 39.1 Transportation -2.2 -3.1 -4.8 -1.9 -3.2 -4.3 -18.0 -36.2 -38.0 -14.2 -15.1 -23.5 13.3 11.0 61.5 2030 Services -0.7 -1.4 -1.6 -0.6 -1.2 -1.4 -17.3 -33.5 -35.0 -18.1 -33.9 -35.8 23.2 -1.9 74.1 Total -0.7 -1.4 -1.7 -0.9 -1.6 -1.9 -17.7 -33.3 -36.6 -25.0 -27.6 -43.1 4.6 -0.4 28.6 Agriculture -0.8 -1.5 -1.7 -1.0 -1.9 -2.2 -14.2 -32.0 -33.2 Mining -2.2 -5.9 -8.5 -2.0 -5.9 -8.1 -10.2 -52.7 -54.7 Construction -0.8 -1.6 -1.8 -0.9 -1.8 -2.1 -15.6 -33.7 -35.0 Trade -0.7 -1.4 -1.6 -0.9 -1.7 -2.0 -15.5 -32.5 -34.0 Financial Services -0.1 -0.6 -0.5 -0.4 -1.1 -1.1 -17.9 -34.5 -36.2 Accomm. & Hotel Ser. -0.5 -0.9 -1.1 -0.6 -1.1 -1.3 -15.0 -31.7 -33.0 Public Services -1.3 -1.9 -2.4 -1.1 -1.7 -2.0 -16.1 -32.8 -34.3 Electricity 5.1 2.4 6.0 -0.3 -2.5 -3.5 -49.0 -50.7 -75.4 -22.5 -25.2 -31.8 Manufacturing -0.6 -1.2 -1.6 -1.1 -1.9 -2.5 -24.4 -30.6 -41.6 -21.6 -25.6 -40.5 11.5 4.0 39.1 Transportation -2.8 -4.0 -6.3 -1.9 -3.3 -4.4 -17.7 -36.7 -38.5 -15.8 -16.9 -27.7 16.2 13.7 63.3 2040 Services -0.8 -1.5 -1.8 -0.7 -1.4 -1.6 -17.1 -34.0 -35.7 -18.1 -34.7 -36.7 23.5 -2.5 72.6 a: In real terms. 24|The Implications of High Energy and Carbon Prices on Irish Firms Higher international energy prices in the HEP scenario, compared to BaU, lower the aggregate real value added and employment by 0.5% and 0.8%, respectively, in 2030. The total sectoral non-ETS15 and ETS emissions decrease by 18% and 23%, respectively, and the total cost of the ETS increases by 5.3%. The sector-specific results show that only the aggregate electricity production sector is positively affected. Although the cost of electricity production by the conventional electricity production sector increases due to higher energy prices, the electricity mix across sectors shifts towards the wind and other renewable sectors. Despite the decline in demand for all energy commodities, including electricity, the sectoral shift triggers the investment expenditures of the wind and other renewable resources sector, increasing the aggregate value added. This is also reflected by the substantial reduction in the sectoral emissions, which are entirely subject to the EU ETS. All energy prices increase, but the change in peat price is negligible as it is not subject to international trade and is unaffected by international prices. Therefore, the reduction in its demand is also negligible in the HEP scenario, compared to BaU, but the reduction in the mining sector’s value added is the second-highest as the sector’s main output is peat. The reductions in the sectoral non-ETS emissions are the highest for the manufacturing sector. As evident in Table 3.3, all sectors but the petroleum sector, of which all emissions are subject to EU ETS, are affected negatively, and their non-ETS emissions decline substantially. The petroleum sector is affected positively due to the price differential between crude oil and oil-related products, e.g., diesel, gasoline, and kerosene. As the prices of oil-related products are higher in international markets than crude oil, their import demand declines more, which triggers domestic production. The increase in the carbon tax lowers the real value added and employment in all aggregated sectors (Table 3.2), and the mining and transportation sectors are hit the hardest. In addition to higher international energy prices, which increase the cost of import, the reduction in the output of energy production sectors, e.g., petroleum and natural gas supply within manufacturing (Table 3.3), increases domestic energy prices even more than 15 Household emissions, including residential and private transportation-related emissions, and government emissions constitute other non-ETS emissions. Results | 25 just the impact of the higher carbon tax. The higher carbon tax lowers the demand for all energy commodities, but the impact on coal (not produced in Ireland) is substantially higher than other energy commodities. Even though the electricity production sector does not pay the carbon tax, the additional impact of the taxation is second-highest (the difference between the CT and HEP scenarios) as the increase in energy prices lowers the demand for energy commodities. The land transportation sector mainly drives the results for the aggregate transportation sector since aviation does not pay the carbon tax, which is also reflected in the non-ETS emissions (its reduction is doubled in the CT scenario compared to the HEP scenario) and a very limited further reduction in the ETS emissions of the aggregate transportation sector. The impacts of the higher carbon tax on sectoral non-ETS emissions are in line with the sectoral economic impacts. The higher carbon tax hit the natural gas supply, other non-metallic products, basic metals, wood and wood products, and rubber and plastic sectors the hardest across manufacturing sectors, compared to BaU, Table 3.3. The additional cost stemming from the higher carbon tax (the difference between the CT and HEP scenarios) affects the natural gas supply sector the most. The petroleum sector’s real value added still experiences an increase, compared to BaU, but the higher carbon tax reduces it by around 5 pp. The increase in the EU ETS price, the CT_ETS scenario, lowers the total ETS emissions by around 40%, and the total cost of the scheme for the Irish firms increases by 31% in 2030, compared to BaU. Among the aggregate sectors subject to EU ETS, the transportation sector (driven by the contraction in the aviation sector) is hit the hardest. The cost of EU ETS decreases for the electricity production sector for two reasons. First, the lower share of fossil fuels in electricity production lowers the output level in the conventional electricity production sector, which has to buy allowances from the EU ETS market to cover all its emissions as it has zero free allowances. Secondly, the current version of the model does not allow other sectors to switch from fossil fuels to renewable energy resources, e.g., biomass, biodiesel, and renewable waste. As Ireland increases its use of renewable resources in electricity production, firms can switch to electricity, which lowers sectoral and, thus, economy-wide emissions. However, as the required investment expenditures to ensure the transition in electricity production are financed 26|The Implications of High Energy and Carbon Prices on Irish Firms by electricity producers through retained earnings, the higher share of renewable resources does not lead to lower electricity prices. Therefore, non-electricity producers do not pay the cost of their energy system transition to low-carbon options but pay the cost of the transition in electricity production. It should be noted that the scenario includes assumptions neither on the share of renewable resources nor the level of required investment. The model endogenously responds to the policy shock considered (along with other assumptions imposed, e.g., the COVID-19 impacts, etc.), and the level of investment expenditures made by electricity producers may not be equal to the level envisaged by the authorities or energy companies. The 21 pp increase in the share of renewable resources in electricity production positively affects the aggregate electricity production sector through higher investment expenditures of the wind and other renewable sectors and also hinders the decline in the aggregate investment expenditures. The transition in electricity production also lessens the negative employment impact of the CT scenario while reducing the sector’s emissions substantially by around 67%, compared to BaU. Results | 27 TABLE 3.3: MANUFACTURING SECTORS RESULTS, % CHANGE W.R.T. BAU Sectoral Activity Emissions Value addedaEmployment Non-ETS ETS Cost of ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS HEP CT CT_ETS Food, Bev. and Tobacco -0.6 -1.0 -1.1 -1.1 -2.0 -2.4 -25.6 -29.2 -42.6 -25.6 -29.2 -42.6 8.3 2.2 45.4 Textile -0.8 -1.4 -1.7 -1.1 -2.0 -2.4 -18.1 -32.3 -34.8 Wood and Wood Prod. -1.6 -2.7 -3.4 -1.7 -3.0 -3.7 -16.3 -31.0 -33.4 Other Industrial Prod. -0.6 -1.2 -1.4 -0.9 -1.7 -2.0 -17.8 -33.5 -35.4 Petroleum 6.0 1.1 -2.5 4.6 -0.3 -3.8 -13.6 -20.5 -36.7 28.1 16.0 60.5 Other Manufacturing -1.5 -2.0 -2.7 -1.8 -2.7 -3.7 -28.9 -32.2 -47.6 -28.9 -32.2 -47.6 6.2 1.0 40.2 Chemical Prod. 0.3 0.2 0.5 -0.5 -1.1 -1.2 -25.6 -28.5 -42.6 -25.6 -28.5 -42.6 10.2 5.5 51.2 Basic Pharmaceutical Prod. 0.4 0.4 0.8 -0.3 -0.9 -0.9 -18.7 -21.6 -19.9 -18.7 -21.6 -19.9 68.1 100.3 231.2 Rubber and Plastic Prod. -1.5 -2.5 -2.9 -1.7 -2.9 -3.5 -15.6 -33.3 -34.7 Other Non-metallic Prod. -3.3 -3.8 -8.6 -3.3 -4.0 -8.8 -17.8 -19.0 -28.3 -7.9 -8.5 -17.0 27.3 25.4 81.3 Basic Metals -3.8 -3.7 -6.6 -4.3 -5.2 -6.9 -29.4 -32.6 -39.6 -29.4 -32.6 -39.6 -5.5 -17.0 6.3 High-Tech Prod. -0.2 -0.6 -0.7 -0.7 -1.4 -1.6 -24.2 -27.0 -40.8 -24.2 -27.0 -40.8 13.3 8.8 58.7 Transportation Equipment -0.9 -1.7 -2.0 -1.1 -2.0 -2.4 -15.3 -30.3 -32.2 Natural Gas Supply -1.9 -8.4 -15.8 -2.0 -8.5 -15.7 -33.4 -40.4 -64.3 1.1 -9.4 -0.8 2030 Water and Sewerage -1.5 -2.3 -3.1 -0.6 -1.2 -1.4 -15.1 -30.5 -32.1 Food, Bev. and Tobacco -0.9 -1.6 -1.8 -1.1 -2.0 -2.4 -25.9 -29.9 -44.2 -25.9 -29.9 -44.2 9.5 2.9 45.6 Textile -1.0 -1.7 -2.0 -1.0 -2.0 -2.3 -17.4 -32.4 -34.7 Wood and Wood Prod. -1.7 -3.0 -3.6 -1.6 -2.8 -3.4 -15.4 -30.9 -32.8 Other Industrial Prod. -0.8 -1.4 -1.7 -0.9 -1.7 -2.0 -17.4 -33.8 -35.6 Petroleum 7.1 0.3 -4.6 4.7 -0.7 -4.5 -13.9 -21.6 -38.9 28.5 15.5 58.2 Other Manufacturing -2.1 -2.7 -3.9 -1.9 -2.8 -3.8 -29.0 -32.8 -48.8 -29.0 -32.8 -48.8 6.5 0.5 38.3 Chemical Prod. 0.1 0.0 0.3 -0.4 -1.0 -1.0 -25.6 -28.9 -43.4 -25.6 -28.9 -43.4 11.0 5.7 51.0 Basic Pharmaceutical Prod. 0.3 0.3 0.7 -0.2 -0.7 -0.6 -17.4 -20.8 -22.5 -17.4 -20.8 -22.5 -71.2 -95.2 -113.0 Rubber and Plastic Prod. -1.7 -2.9 -3.5 -1.6 -2.9 -3.4 -14.9 -33.4 -34.5 Other Non-metallic Prod. -4.4 -4.9 -11.9 -3.9 -4.6 -10.7 -20.7 -22.0 -34.9 -9.4 -10.0 -21.1 28.5 26.9 81.8 Basic Metals -4.6 -5.2 -7.7 -4.1 -5.2 -6.9 -27.9 -31.9 -41.2 -27.9 -31.9 -41.2 -14.5 -24.0 -1.3 High-Tech Prod. -0.4 -0.8 -0.9 -0.6 -1.3 -1.4 -23.8 -27.1 -41.1 -23.8 -27.1 -41.1 14.3 9.2 59.2 Transportation Equipment -1.0 -1.8 -2.2 -1.0 -1.9 -2.2 -14.6 -30.3 -31.9 Natural Gas Supply -2.9 -11.9 -21.5 -2.2 -9.0 -16.1 -33.8 -41.4 -65.2 0.6 -10.9 -3.5 2040 Water and Sewerage -1.4 -2.2 -2.8 -0.7 -1.3 -1.6 -14.9 -31.0 -32.5 a: In real terms. 28|The Implications of High Energy and Carbon Prices on Irish Firms In the CT_ETS scenario, the gradually increasing EU ETS price amplifies the cost of production in the sectors subject to the EU ETS. Compared to BaU, the impacts are the highest in the natural gas supply, followed by other non-metallic minerals and basic metals sectors (Table 3.3). Since the ETS emissions of a sector are a fixed fraction of its total emissions from the combustion of fossil fuels, the percentage changes in the sub-sectoral ETS and non-ETS emissions in Table 3.3 are the same. The exception is the other non-metallic products sector, which has, in addition to combustion emissions, process emissions that are linked to the level of sectoral output. The cost of EU ETS decreases in the HEP and CT scenarios for the basic metals sector. In eq. (2.13), the variable AtoT, the free allowances-to-emissions ratio, increases for the exogenous free allowances with a decline in emissions. As it increases, it reduces the additional cost of EU ETS in eq. (2.12). The cost reduces more in the CT scenario than the HEP scenario because the increase in the carbon tax increases the carbon tax rebates received by the firm, which further reduces the unit incurred cost of energy commodities, and, thus the cost of EU ETS. In the CT_ETS scenario, however, the increase in the EU ETS price suppresses the impact of the decline in the AtoT and the cost of the scheme increases. The presented outcomes are observed in 2040 as well. The aggregated sectoral results in Table 3.2 confirm that the contraction in the economy continues in 2040. Once more, the contraction is led by the mining and transportation sectors. As expected, these sectors also account for the largest percentage of emissions falls. The aggregate electricity sector’s ETS cost declines due to the decline in the use of fossil fuels in electricity production; the share of electricity production from renewable resources exceeds 70% in 2040. Within the manufacturing sector, the natural gas supply, other non-metallic products, and basic metals sectors are the most adversely affected in terms of value added and employment. Conclusion | 29 CHAPTER 4 Conclusion The transition to a low-carbon economy is crucial in lowering energy-related emissions to reach the targets set by environmental legislation. The transition requires all economic agents to switch from fossil fuels to renewable energy resources. This switching can be accomplished by replacing all combustion systems currently in use, which requires a huge amount of investment. However, avoiding undertaking the necessary actions would result in not only keeping the level of emissions higher but also having a cost, especially when carbon prices have increasing trends with substantial volatility with unexpected spikes in energy prices. This report investigates the implications of higher energy and carbon prices under the assumption of no further policy intervention and, thus, attempts to present a picture of the cost of not moving towards a low-carbon economy. The analysis utilises an intertemporal computable general equilibrium model, namely the Ireland Environment-Energy-Economy (I3E). Given the peak energy prices observed in 2022, three scenarios are considered. The first scenario, HEP, includes the spikes in international energy prices and the EU ETS price to quantify the effects of the price shock in international markets. The second scenario, CT, includes only the increases in the carbon tax until 2030 to show how reaching the carbon tax target would affect the Irish production sectors in addition to higher energy prices. The third scenario, CT_ETS, examines the implications of gradually increasing the EU ETS price when energy prices and the Irish carbon tax are higher. The results for basic macroeconomic aggregates, the aggregate production sectors, and manufacturing sub-sectors are discussed. As the main focus of the report is the production sectors, the distributional implications of higher energy and carbon prices across households are briefly discussed, but their details are available upon request. The external energy and carbon pricing shock adversely affects the Irish economy such that real gross domestic product (GDP), investment and consumption expenditures decline, and labour market outcomes 30|The Implications of High Energy and Carbon Prices on Irish Firms deteriorate. The only positively affected macroeconomic aggregate is the trade balance, which results from both the economic contraction (the reduction in import demand, i.e., the income effect) and the lower energy bill. The reduced economic activity leads to reduced emissions. Also, with a shrinking economy, government revenues decrease, and the government debt burden increases. The higher carbon price in the CT and CT_ETS scenarios amplifies the negative implications of higher energy prices on macroeconomic aggregates. The CT_ETS scenario differs regarding its result on the government debt stock, which increases less than in the other two scenarios as the government reclaims half of the ETS revenue. The positive contribution of the higher EU ETS price in the short run, however, vanishes in the medium run as the decline in economic activity suppresses the EU ETS impact. The higher EU ETS price generates higher reductions in total emissions despite lower reductions in non-ETS emissions. The brunt of the economic contraction is borne by the mining and transportation sectors, with substantially higher falls in real value added and employment. The electricity sector is positively affected in all scenarios due to the increased production in the wind and other renewable sectors. The positive impact is the lowest in the CT scenario as there is a substantial reduction in energy demand. The positive impact is the highest if the EU ETS price increases as electricity production shifts to renewable sources such that their share increases from 40% to 70%. These three sectors also account for high emission reductions. Within the manufacturing sector, the petroleum and natural gas supply sectors are hit the hardest. The carbon tax and the EU ETS price changes are assumed to end by 2030, but the model is run for a longer time horizon. An overview of the results for 2040 reveals that the core results closely follow those in 2030. The cost of not transitioning to a low-carbon economy quantified in the report should be considered as the upper-end results as they are based on the assumption that energy prices will stay constant at their extremely high levels and firms will keep their current composition of energy demand across commodities. Although the current prices are substantially lower than their assumed levels in the analyses, the report provides important insights Appendix | 37 Appendix A Additional Tables TABLE A.1: LIST OF COMMODITIES CODE NAME CODE NAME C_AGR Agriculture C_HTP High-tech products C_PEA Peat C_TRE Transportation equipment C_COA Coal C_ELC Electricity C_CRO* Crude oil C_NGS Natural gas C_OMN* Other mining C_WAT Water and sewerage C_FBT Food, beverage, and tobacco C_CON Construction C_TEX Textile C_TRD Trade C_WWP Wood and wood products C_LTS Land transportation C_OIN Other industrial products C_WTS Water transportation C_GAL Gasoline C_ATS Air transportation C_KRS Kerosene C_OTR Other transportation C_FUO* Fuel-oil C_ACC Accom. and hotel services C_LPG Liquid petroleum gas C_TEL Telecommunication services C_DIE Diesel C_FSR Financial services C_OPP Other petroleum products C_RES Real estate services C_OTM Other manufacturing C_PSE Professional services C_CHE Chemical products C_ADS Admin and support services C_BPP Basic pharmaceuticals C_PUB Public services C_RUP Rubber and plastic C_EDU Education C_ONM Other non-metallic minerals C_HHS Health C_BFM Basic fabricated metals C_OSE Other services *: Not subject to private consumption. 38|The Implications of High Energy and Carbon Prices on Irish Firms TABLE A.2: LIST OF ACTIVITIES AND AGGREGATION KEY CODE ACTIVITY NACE CODES AGGREGATE SECTOR A_ACC Accommodation and Hotel Services 55-56 ACC A_AGR Agriculture 1-3 AGR A_CON Construction 41-43 CON A_FSR Financial Services 64-66 FSR A_PUB Public Sector 84 PUB A_TRD Trade 45-47 TRD A_ELC Conventional ELC A_WND Wind ELC Electricity A_ORE Other Renewables ELC A_BFM Basic Metal Manufacturing 24-25 MAN Manufacturing A_BPP Basic Pharmaceutical Products 21 MAN A_CHE Chemical Products 20 MAN A_FBT Food, Beverage and Tobacco 10-12 MAN A_HTP High-Tech Products 26-28 MAN A_NGS Natural Gas Supply MAN A_OIN Other Industrial Products 17,18,33 MAN A_ONM Other Non-metallic Products 23 MAN A_OTM Other Manufacturing 31-32 MAN A_PET Petroleum MAN A_RUP Rubber and Plastic Products 22 MAN A_TEX Textile 13-15 MAN A_TRE Transportation Equipment 29-30 MAN A_WAT Water and Sewerage 36,37-39 MAN A_WWP Wood and Wood Products 16 MAN A_OMN Other Mining Products MIN Mining A_PEA Peat MIN A_ATS Air Transportation 51 TRP Transportation A_LTS Land Transportation 49 TRP A_WTS Water Transportation 50 TRP A_OTR Other Transport (Storage and Postal) 52-53 TRP A_EDU Education Sector 85 SER A_HHS Health Sector 86-88 SER A_RES Real Estate Services 68 SER A_TEL Telecommunication Services 61 SER Services A_PSE Professional Services 69-75 SER A_ADS Admin and Support Services 77-82 SER A_OSE Other Services remaining SER *:It excludes NACE codes 5-9 (Mining, Quarrying and Extraction), 19 (Petroleum Products), and 35 (Electricity and Gas Supply). The activities without NACE codes are further disaggregated sectors. Whitaker Square, Sir John Rogerson’s Quay, Dublin 2 Telephone +353 1 863 2000 Email [email protected] Web www.esri.ie Twitter @ESRIDublin