The impact of the EU Emission Trading Scheme (EU ETS) on firms - - PowerPoint PPT Presentation

The impact of the EU Emission Trading Scheme (EU ETS)

• n firms’ performance and energy efficiency

Georgia Makridou (ESCP Europe Business School, UK) Kostas Andriosopoulos (ESCP Europe Business School, UK) Michael Doumpos (Technical University of Crete, Greece) Emilios Galariotis (Audencia Business School, France)

Introduction

 The European Union Emission Trading Scheme (EU ETS) is regarded as the cornerstone of the EU climate policy.  Its objective: ‘promote greenhouse gas (GHG) reductions in a cost-effective and economically efficient manner’ (European Commission, 2003).  The EU ETS relies on the principle of “cap-and-trade”.  It operates in 31 countries (all 28 EU countries plus Iceland, Liechtenstein and Norway).  It covers around 45% of the EU’s GHG emissions.

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Subject of Research

 This study aims at evaluating the profitability and environmental performance of firms under the EU ETS in a wide EU context since its launch.

Profitability = Operating P/L[=EBIT] / Total assets

✓ Economic and Environmental data of a large sample of EU firms covered by the EU ETS are used.

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Data

 Dataset (22.972 data) ✓ 25 EU countries (Croatia and Cyprus are excluded due to small number of firms) ✓ 2006 to 2014 ✓ 8 main industrial sectors About 4.185 European firms

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Data

✓ The industrial sectors and the number of firms per sector

❖ The sectors of Manufacturing and Electricity represent 90% of the sample.

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✓ Regional distribution of firms

Country Number of firms per country

Country Country ISO Code Number of firms per country

Country Number of firms Austria 82 Belgium 169 Bulgaria 71 Czech Republic 219 Denmark 4 Finland 115 France 280 Germany 595 Greece 10 Hungary 104 Ireland 8 Italy 654 Latvia 9 Lithuania 3 Luxembourg 8 Netherlands 17 Norway 25 Poland 208 Portugal 162 Romania 132 Slovakia 118 Slovenia 53 Spain 632 Sweden 171 United Kingdom 336

Data

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Variables

❖ Economic data is obtained from the ORBIS database. ❖ Environmental data comes from the European Union Transaction Log (EUTL). Variable Explanation CR Current_Ratio=Current Assets / Current Liabilities SR Solvency_Ratio=(Shareholders Funds / Total Assets) * 100 EBITTA EBIT_TO_Tot_Assets=Operating P/L[=EBIT]/Total assets SZ Size=log (Total assets) NETTA No_Empl_TO_Tot_Assets=Number of employees/Total assets ORTTA Oper_Rev_TO_Tot_Assets=Operating revenue / Total assets AF Alloc_Factor=Allowances allocated/Verified emissions VETS Ver_Emiss_TO_Sales=Verified emissions/Sales

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Variables

 Environmental Variables ➢ Alloc_Factor (Allocation Factor): Allowances Allocated / Verified Emissions

• AF > 1 => entity has received allowances that exceed its emissions
• AF < 1 => entity either has to buy additional emissions allowances or

abate some of its emissions ➢ Ver_Emiss_TO_Sales: Verified Emissions / Sales

• Ver_Emiss_TO_Sales = 1 => high amount of emissions
• Ver_Emiss_TO_Sales = 0 => low amount of emissions

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Methodology

✓ Regression analysis in STATA ✓Four different settings for the variables (M1, M2, M3, M4)

• 6 economic variables
• 2 environmental variables

✓ Dependent Variable: EBITTA ✓ The value of all independent variables are one unit of time ago compared to the dependent variable

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Methodology

The examined models (M1, M2, M3, M4)

Variable M1 M2 M3 M4

Economic Variables

CR (Current Ratio) ✓ ✓ ✓ ✓ SR (Solvency Ratio) ✓ ✓ ✓ ✓ EBITTA ✓ ✓ ✓ ✓ SZ (Size) ✓ ✓ ✓ ✓ NETTA (No_Empl_TO_Tot_Assets) ✓ ✓ ✓ ✓ ORTTA (Oper_Rev_TO_Tot_Assets) ✓ ✓ ✓ ✓

Environ. Variables

AF (Allocation Factor) ✓ ✓ VETS (Ver_Emiss_TO_Sales) ✓ ✓

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Methodology

✓ Model 1 (M1):

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Methodology

✓ Model 2 (M2):

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✓ Model 3 (M3): ✓ Model 4 (M4):

Data Analysis

Pairwise Correlation Coefficients ✓ There is no multicollinearity among variables ✓ EBITTA is correlated positively with all economic variables, except NETTA and the environmental variables

13 Note: All correlations are significant at the 1% level except + (p-value = 0.651).

Results

(M1) (M2) (M3) (M4) EBITTA EBITTA EBITTA EBITTA Solvency Ratio (SR) 0.0003*** 0.0003*** 0.0003*** 0.0003*** Size (SZ) 0.0051*** 0.0048** 0.0041** 0.0036* Current Ratio (CR)

• 0.0020***
• 0.0020**
• 0.0019**
• 0.0018**

No_Empl_TO_Tot_Assets (NETTA)

• 1.177***
• 1.171***
• 1.176***
• 1.167***

Oper_Rev_TO_Tot_Assets (ORTTA) 0.0247*** 0.0245*** 0.0236*** 0.0232*** Allocation Factor (AF)

• 0.0023***
• 0.0032***

Ver_Emiss_TO_Sales (VETS)

• 0.0005***
• 0.0005***

_cons 0.0434* 0.0460** 0.0514** 0.0561** r2 0.0768 0.0778 0.0779 0.0793 Chi-squared 397.2 404.4 409.7 421.9 Note: (* p < 0.1, ** p < 0.05, *** p < 0.01) 14

Conclusions

 Both economic and environmental characteristics contribute to the profitability of firms under the EU ETS: ➢ It is mainly affected by the solvency ratio, employment, operating revenue to total assets as well as by the verified emissions to sales and the number

• f free allocation of emissions allocated to the verified emissions.

 The information gained through this study sheds light on the effect of the EU ETS at firm’s economic and environmental performance.

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Next Steps

 Future research: ➢ enrichment of the data set with firms that are not participating in EU ETS, ➢ analysis on different groups (under- versus over-allocated firms), ➢ a more extensive time period (up-to-date data) ➢ examination of more economic and environmental characteristics

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