Microsoft Word - ea_2021_1_final.docx DOI: 10.28934/ea.21.54.1.pp92-103 SCIENTIFIC PAPER Panel Cointegration Analysis of Total Environmental Taxes and Economic Growth in EU Countries Vera Mirović1 | Branimir Kalaš1* | Nada Milenković1 1 University of Novi Sad, Faculty of Economics in Subotica, Department for Finance and Accounting, Subotica, Serbia ABSTRACT The paper investigates the nexus between total environmental taxes and economic growth for twenty-eight EU countries from 1994 to 2018. The objective of this research is to evaluate the long- run relationship between these variables based on panel data analysis. The analysis includes panel cointegration test as well as panel ordinary least squares such as DOLS and FMOLS models. The results identify long-run relationship between total environmental taxes and economic growth in selected countries. Likewise, there is a significant relation running from total environmental taxes to economic growth measured by gross domestic product rate. Empirical findings confirm that revenue of environmental taxes have positive impact on economic growth measured by gross domestic product rate. Key words: Environment taxation, economic growth, panel cointegration, EU countries JEL Classification: E60, H23, Q5 INTRODUCTION – THEORETICAL BACKGROUND Economic growth has become the basic aim of developing countries without adequate consideration of environmental issues (Mitić et al. 2019). However, as environmental issues become more relevant, governments have realized the significance of balanced economic and environmental development (Gao et al. 2019). Pautrel (2009) argue that effect of the environmental policy can have positive implications to the economy when impacts of pollution on health are reduced. Zhou et al. (2020) detected that an increase in environmental tax rate can reduce the use of polluting consumer goods by households as well as investment in polluting factors by companies. Likewise, their growth can negatively impact employment, income and economic growth and include both effects: substitution effect and income effect on household consumption. Likewise, Wesseh et al. (2017) highlight that tax policy is often more efficient or less distorted than direct regulation. Accordingly, taxes are effective tools to modify consumers' behaviour in terms of sustainability (Kosonen and Nicodème, 2009). For most environmental problems, adequately determined fiscal policy is the most natural tools for including environmental detriment into the products price and non-market actions (Heine et al. 2012). Stram (2014) determined that tax revenues enables stability and support for research focused on energy sources and emissions reduction in the long-run. According that, many economists and international institutions determine environmental taxes as the most efficient market-based * Coressponding author, e-mail: branimir.kalas@ef.uns.ac.rs Vera Mitrović, Branimir Kalaš, Nada Milenković 93 tools (Lin and Li, 2011). Mirović et al. (2019) highlight that tax forms should take an important place in the economic policy of each country. The findings of Castiglione et al. (2014) suggest that countries should take advantage of the relationship between economic growth and institutional enforcement ie, the nexus between economic development and environmental awareness in order to provide an adequate environmental tax policy. Environmental taxes enhance the costs and price products for the environment and decrease the pressure on it. (Piciu and Trică, 2012) where Davidović et al. (2019) determined environmental taxes as crucial for more effective environmental protection. Andrei et al. (2016) emphasized that environmental taxes have significant impact on economic sustainability in post-transition countries. Environmental taxes are increasingly considered as essential part of the economic policy where their proper design can enable economic incentives, dynamic innovation. It implies that these taxes help achieving economic, social and environmental benefits (Withana et al. 2014). Accordingly, environmental taxes have a more relevant role in Europe and especially in the Scandinavian economies compared to the rest of the world at the beginning of the 2000 (Radulescu et al. 2017). Also, Bachus et al. (2019) determined that taxes are robust tool for reducing complex environmental problems in the world. Labeaga and Labandeira (2020) defined environmental taxes such as cost-effective corrective approach which contributes development and uses clean technologies. Liobikiene et al. (2019) argue that environmental taxes are imposed with the aim to decrease negative effects to environment. On the other hand, Borozan (2018) argue that energy taxes are not efficient policy tool for directly effecting electricity consumption due to various subventions and exemptions through European Union. Vukadinović and Ješić (2019) cite that ecological modernization that includes carbon tax, a decline of labour costs and subsidies for research and development. Tantau et al. (2018) determined significant impact of environmental tax revenues in European Union to recycling rate of municipal waste for the period 2010-2014. Further, Aubert et al. (2019) point out regressive effect of indirect taxes where environmental taxation decreases consumers’ purchasing power and has regressive implications to poor consumers compared to rich. The nexus between the environment and economic growth is one of the most essential relation for policy makers (Mitić et al. 2017). The standard way to evaluate economic success is by measuring economic growth (Petrov and Trivić, 2018). Analyzing causality between environmental taxes and economic growth, in OECD countries from 1995 to 2006, Morley and Abdullah (2010) identified long-run causality between economic growth and environmental taxation. Likewise, this analysis manifested short-run causality between these variables in the reverse direction. Liang et al. (2007) and highlight that effect of carbon tax may depend on the economic conditions of an economy. Hájek et al. (2019) indicate that it’s more environmentally efficient if taxes have been collected for a longer time. Dökmen (2012) researched the relationship between environmental taxes and economic growth in twenty-nine EU countries for the period 1996-2010. The results of panel vector autoregressive models identified positive and statistically significant effect of environmental taxes on economic growth in these countries for the observed period. Abdullah and Morley (2014) investigated causality between environmental taxes and economic growth in EU countries and OECD countries for the period 1995-2006. Empirical results showed long-run causality running from economic growth to increased environmental tax revenues, as well as, short-run causality in the reverse direction. Loganathan et al. (2014) analysed the relationship between carbon taxation and economic growth in Malaysia from 1974 to 2010. Their findings suggest that there is bidirectional causality between these components for the analysed period. Li and Masui (2018) found that the environmental tax and carbon tax would lead to a GDP loss of 0.1% to 0.67% and highlighted that energy- intensive sectors will have bigger damage compared to service sector and agriculture that will have a small growth. He et al. (2019) confirmed that environmental taxes are cointegrated with energy consumption, economic growth, and CO2 emissions in China, Finland and Malaysia. 94 Economic Analysis (2021, Vol. 54, No. 1, 92-103) Similarly, Busu and Trica (2019) revealed significant and positive effect of environmental taxes on economic growth in EU countries for the observed period 2010-2017. The need for research is manifested in providing information support and giving guidance to economic policymakers in EU about the long-run relationship between total environmental taxation and economic growth in these countries. It implies that fundamental goal of this research is to reveal are environmental taxes significant for economic growth in EU countries. The structure of this paper is as follows. After the introduction and definition of necessity of environmental tax approach, there is an analysis of environmental taxes and gross domestic product in EU countries from 1994-2018. The greatest part of this research includes empirical analysis and results which consist panel cointegration tests and different panel models such as POLS, DOLS and FMOLS. The last segment includes summarizes and conclusion about cointegration between total environmental taxes and economic growth in EU countries from 1994 to 2018. THE NECESSITY OF ENVIRONMENTAL TAX APPROACH AND DOUBLE DIVIDEND HYPOTHESIS Over the last three decades, ecological modernisation has emerged as a strong political discourse in which economic growth, environmental protection as well as energy security are jointly intensifying (Machin, 2019). The government should implement stricter and more comprehensive system of environmental policy in order to provide future sustainable development. It implies reasonable tax system and design of ecological policy system based on neutrality (Yang et al. 2019). According to European Environmental Agency green taxes are classified into three categories: cost-covering charges, incentive taxes and fiscal environmental tax forms (European Environmental Agency, 1996). The main purpose of cost-covering charges is covering the costs of regulation and control and implies that users pay for consumption of environmental resources. Further, incentive taxes are created in line with Pigouvian tax where core idea is to change the behaviour of the polluter in the long-term. Fiscal environmental taxes are main driving force of green tax reforms where highlight the tax for use of resources without significant change to the budgetary balance (Maxim and Zander, 2019). Environmental taxation has been increasingly seen as an effective economic tool to make incentives in terms of cleaner production and consumption habits (Freire-González, 2018). Own resources based on taxes for the European Union can be a powerful tool to the current lack of sustainability because they have the potential to cover existing sustainability gaps in tax systems in the EU (Krenek and Schratzenstaller, 2017). There is a growing consensus that environmental taxes are not only a promising instrument to reducing environmental effects, but also a way to increase public revenues and decrease fiscal pressure (Freire-González and Ho, 2019). Alexeev et al. (2016) argue that an emissions taxes are used as an environmental policy instrument to decline environmental damages. Bachus et al. (2019) highlight an importance of recycling the revenues from an environmental tax reform and defined a “Ladder of Acceptability of Revenue Recycling Options” based on: a) financing special environmental programmes; b) reducing taxes on labour, consumption, corporate income, property or other distortionary taxes; c) returning the additional tax forms from one sector to that same sector in a way that is not proportional to the emissions, pollution or resource use; d) eliminating regressive effects of the environmental taxes; e) reducing public debt or adding to the general budget. Kirchner et al. (2019) provided that carefully designed tax policy about CO2 can potentially enable an equitable double dividend, where the double dividend hypothesis implies the possibility of realizing economic and environmental benefits as a result of implementing an environmental tax policy and recycling revenues (Wesseh et al. 2019). This theoretical approach is a widely examined topic that considers the possibility of producing additional economic benefits using environmentally beneficial tax measures (Maxim and Zander, 2019). The early version of the double dividend hypothesis can also be determined as the efficiency double Vera Mitrović, Branimir Kalaš, Nada Milenković 95 dividend in which the essence was that green tax reform can decrease pollution and increase economic efficiency (Maxim et al. 2019). Double dividend hypothesis arises from progress of the environmental conditions as a result of environmental tax incentives as well as improvement of economic conditions due of the shift from high distorting taxes to less distorting taxes (Freire- González, 2018). Sasmaz (2016) examined the effect of environmental tax reforms on environment and employment in fifteen countries in EU (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, United Kingdom) for the period 1995-2012. Using panel cointegration and fully modified ordinary least square tests, this analysis showed the validity of double dividend hypothesis in these countries. METHODS AND MATERIALS In this research twenty-eight EU countries are analysed for the period 1994-2018. The research used Eurostat for environmental taxation and IMF for gross domestic product. In order to stationary, panel unit root tests are applied for selected variables. After we determined that variable are stationary at first difference and integrated of order one process or I(1), we have applied cointegration analysis. After identifying long-run relation between variables, an analysis has included different panel models such as POLS, DOLS and FMOLS. Before presenting panel cointegration estimation it is necessary to develop research hypothesis which is defined as follows: H1: Environmental taxes have significant and positive impact on economic growth in EU countries. Panel cointegration test is often used to identify a potential long-run relation between two or more variables. The long-run relationship implies the variables move together over time. The panel cointegration test allows for cross-sectional interdependence with both different individual effects and deterministic trends can be determined as follows: lnYit = αit δit  βilnEit εit (1) εit=ρitεit-1 + uit (2) where i = 1,…N reflects the panel member, t = 1,…T refers to the time period, Y reflects the GDP, TET reflects the total environmental taxes and βi reflects the slope coefficient. The parameters αit and δi allow for possibility of country-specific effects and deterministic trend effects, where εit manifests the evaluated residual deviations from the long-run relation (Adhikari, Chen, 2012). EMPIRICAL ANALYSIS AND RESULTS This segment includes analysis trend of gross domestic product rate and total environmental taxes from aspect of their share and collected revenue from 1994 to 2018. After that, empirical study implies panel cointegration tests and three models such as POLS, DOLS and FMOLS. 96 Economic Analysis (2021, Vol. 54, No. 1, 92-103) -4, 000 -2, 000 0 2, 000 4, 000 1995 2000 2005 2010 2015 AustriaAustria -4, 000 -2, 000 0 2, 000 4, 000 1995 2000 2005 2010 2015 BelgiumBelgium -10, 000 -5, 000 0 5, 000 10, 000 1995 2000 2005 2010 2015 BulgariaBulgaria -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 CroatiaCroatia -8, 000 -4, 000 0 4, 000 8, 000 12, 000 1995 2000 2005 2010 2015 CyprusCyprus -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 Czech RCzech R -6, 000 -4, 000 -2, 000 0 2, 000 4, 000 1995 2000 2005 2010 2015 DenmarkDenmark -20, 000 -10, 000 0 10, 000 20, 000 1995 2000 2005 2010 2015 EstoniaEstonia -10, 000 -5, 000 0 5, 000 10, 000 1995 2000 2005 2010 2015 FinlandFinland -4, 000 -2, 000 0 2, 000 4, 000 1995 2000 2005 2010 2015 Franc eFranc e -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 GermanyGermany -10, 000 -5, 000 0 5, 000 10, 000 1995 2000 2005 2010 2015 GreeceGreece -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 HungaryHungary -10, 000 0 10, 000 20, 000 30, 000 1995 2000 2005 2010 2015 I relandI reland -6, 000 -4, 000 -2, 000 0 2, 000 4, 000 1995 2000 2005 2010 2015 I talyI taly -20, 000 -10, 000 0 10, 000 20, 000 1995 2000 2005 2010 2015 LatviaLatvia -20, 000 -10, 000 0 10, 000 20, 000 1995 2000 2005 2010 2015 L ithuaniaL ithuania -5, 000 0 5, 000 10, 000 1995 2000 2005 2010 2015 L uxembourgL uxembourg -4, 000 0 4, 000 8, 000 12, 000 1995 2000 2005 2010 2015 MaltaMalta -4, 000 -2, 000 0 2, 000 4, 000 6, 000 1995 2000 2005 2010 2015 NetherlandsNetherlands 0 2, 000 4, 000 6, 000 8, 000 1995 2000 2005 2010 2015 PolandPoland -6, 000 -4, 000 -2, 000 0 2, 000 4, 000 6, 000 1995 2000 2005 2010 2015 PortugalPortugal -10, 000 -5, 000 0 5, 000 10, 000 1995 2000 2005 2010 2015 RomaniaRomania -8, 000 -4, 000 0 4, 000 8, 000 12, 000 1995 2000 2005 2010 2015 SlovakiaSlovakia -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 SloveniaSlovenia -4, 000 -2, 000 0 2, 000 4, 000 6, 000 1995 2000 2005 2010 2015 SpainSpain -8, 000 -4, 000 0 4, 000 8, 000 1995 2000 2005 2010 2015 SwedenSweden -6, 000 -4, 000 -2, 000 0 2, 000 4, 000 6, 000 1995 2000 2005 2010 2015 United KingdomUnited Kingdom Figure 1. GDP rate in EU countries Source: Authors calculation based on IMF Although gross domestic product is being criticized for not adequately representing social welfare in terms of development, the GDP is a dominant and widely used indicator for measuring economic activity (Sanyé-Mengual et al. 2019). The gross domestic product in the European Union was around 13.94 trillion euros which reflects the total value of all goods and services produced in EU countries. Figure 1 shows trend of GDP rate in EU countries for the period 1994- 2018. The average GDP rate was 2.68%, where Ireland had the highest average GDP rate of 6.05% during observed period. On the other hand, Italy had the smallest average GDP rate of 0.69%. Analyzing by countries, Estonia, Lithuania and Slovakia had average GDP rate above 4%, while other countries had smaller growth rate of gross domestic product. The level of average GDP rate of 2% was recorded in Latvia, Luxembourg, Malta and Romania, while most of countries had mean GDP rate around 2%. Twelve of twenty-eight economies had mean GDP rate below EU average, while Greece and Italy recorded average GDP rate below 1%. Vera Mitrović, Branimir Kalaš, Nada Milenković 97 2. 0 2. 2 2. 4 2. 6 2. 8 1995 2000 2005 2010 2015 Aus tri aAus tri a 2. 2 2. 4 2. 6 2. 8 1995 2000 2005 2010 2015 Bel gi u mBel gi u m 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 3. 5 1995 2000 2005 2010 2015 Bu l gari aBu l gari a 2. 4 2. 8 3. 2 3. 6 1995 2000 2005 2010 2015 C ro ati aC ro ati a 2. 0 2. 4 2. 8 3. 2 3. 6 4. 0 1995 2000 2005 2010 2015 C yp ru sC yp ru s 2. 0 2. 2 2. 4 2. 6 2. 8 1995 2000 2005 2010 2015 Cz ech RCz ech R 3. 5 4. 0 4. 5 5. 0 5. 5 1995 2000 2005 2010 2015 Den m arkDen m ark 0. 5 1. 0 1. 5 2. 0 2. 5 3. 0 1995 2000 2005 2010 2015 Es to n i aEs to n i a 2. 4 2. 6 2. 8 3. 0 3. 2 3. 4 1995 2000 2005 2010 2015 Fi n l an dFi n l an d 1. 8 2. 0 2. 2 2. 4 2. 6 1995 2000 2005 2010 2015 Fran ceFran ce 1. 6 1. 8 2. 0 2. 2 2. 4 2. 6 2. 8 1995 2000 2005 2010 2015 Germ anyGerm any 2. 0 2. 5 3. 0 3. 5 4. 0 1995 2000 2005 2010 2015 GreeceGreece 2. 0 2. 4 2. 8 3. 2 3. 6 1995 2000 2005 2010 2015 Hu ngaryHu ngary 1. 5 2. 0 2. 5 3. 0 3. 5 1995 2000 2005 2010 2015 Irel an dIrel an d 2. 4 2. 8 3. 2 3. 6 1995 2000 2005 2010 2015 Ital yItal y 0 1 2 3 4 1995 2000 2005 2010 2015 Latvi aLatvi a 1. 6 2. 0 2. 4 2. 8 3. 2 1995 2000 2005 2010 2015 Li thu an i aLi thu an i a 1. 6 2. 0 2. 4 2. 8 3. 2 1995 2000 2005 2010 2015 Luxem b o urgLuxem b o urg 2. 4 2. 8 3. 2 3. 6 4. 0 1995 2000 2005 2010 2015 Mal taMal ta 3. 2 3. 3 3. 4 3. 5 3. 6 1995 2000 2005 2010 2015 N eth erl an d sN eth erl an d s 1. 6 2. 0 2. 4 2. 8 1995 2000 2005 2010 2015 P o l an dP o l an d 2. 0 2. 4 2. 8 3. 2 3. 6 1995 2000 2005 2010 2015 P ortu galP ortu gal 1. 5 2. 0 2. 5 3. 0 3. 5 4. 0 1995 2000 2005 2010 2015 R om an i aR om an i a 1. 8 2. 0 2. 2 2. 4 2. 6 1995 2000 2005 2010 2015 Sl o vaki aSl o vaki a 2. 5 3. 0 3. 5 4. 0 4. 5 5. 0 1995 2000 2005 2010 2015 Sl o ven i aSl o ven i a 1. 4 1. 6 1. 8 2. 0 2. 2 2. 4 1995 2000 2005 2010 2015 Sp ai nSp ai n 2. 0 2. 2 2. 4 2. 6 2. 8 3. 0 1995 2000 2005 2010 2015 SwedenSweden 2. 0 2. 2 2. 4 2. 6 2. 8 1995 2000 2005 2010 2015 Uni ted K i ngdo mUni ted K i ngdo m Figure 2. Total environmental taxes in EU countries Source: Authors calculation based on Eurostat After presenting GDP rate in EU countries, next figure manifests share of total environmental taxes in the gross domestic product from 1994 to 2018. Environmental tax revenues in the European Union totalled 324.6 billion euro which is 3% increase in nominal terms compared to previous year and 49% higher than in 2002 (https://ec.europa.eu/eurostat/web/products- eurostat-news/-/ddn-20200219-1). European Union has growth of the environmental tax revenues in the period 2005-2008, but since 2008 the revenue based on environmental taxes decreased in these countries (Munitlak Ivanović and Golušin, 2012). Total environmental taxes had average share 2.66% of GDP during observed period, where Denmark had the highest mean share 4.43% of GDP. On the other hand, Spain is a country with the smallest average share 1.9% of GDP for the analyzed period. Economies such as Croatia, Italy, Malta, Netherlands and Slovenia had average share above 3% of GDP, while most of analyzed countries had mean share around 2%. Seventeen of twenty-eight countries recorded mean share of total environmental taxes below EU average during observed period. In most cases, environmental taxes refer to exploitation of natural resources such as energy and water as well as waste generation. The highest part of the revenue is raised through taxes on energy products where significant level of revenues is also collected via taxes on motor vehicles (Golušin et al. 2013). An increase of environmental taxes in the European Union resulted in a growth of revenues based on environmental taxes where fifteen countries increased environmental taxes including excise duties on energy products and electricity (Hodžić and Bratić, 2015). Table 1. Descriptive statistics of total environment tax revenue Country Mean Std. Dev Min Max Austria 6532.03 1485.61 3974.84 8855.83 Belgium 8231.15 2125.01 5303.99 12407.2 Bulgaria 826.56 485.71 84.2 1648.09 Croatia 1289.79 210.53 1001.29 1853.35 Cyprus 430.93 143.06 188.62 589.4 Czech R 2726.52 1046.46 1205.44 4507.93 Denmark 9567.33 1404.39 6099.74 11065.4 98 Economic Analysis (2021, Vol. 54, No. 1, 92-103) Country Mean Std. Dev Min Max Estonia 325.14 214.89 25.61 708.95 Finland 4993.47 1095.01 2930.92 6848 France 38132.77 7260.88 30139 55949 Germany 53626.48 6113.61 41524.55 59737 Greece 4933.84 1371.79 3190.58 7162 Hungary 2263.69 706.98 905.53 3142.61 Ireland 3754.73 1089.64 1565.12 5186.03 Italy 45331.86 8566.98 31015.51 58735 Latvia 453.99 296.92 40.74 982.72 Lithuania 477.46 202.47 95.99 899.78 Luxembourg 812.43 204.56 468.77 1039.61 Malta 186.48 62.04 87.6 321.75 Netherlands 19100.53 4280.41 11190.14 25832 Poland 7352.46 3546.65 1939.76 13500.41 Portugal 4146.89 587.75 3047.89 5270.52 Romania 2154.67 1167.89 499.25 4239.84 Slovakia 1155.87 642.48 374.32 2232.7 Slovenia 1099.30 323.05 632.25 1609.66 Spain 16594.21 3486.29 9976.01 22066 Sweden 8582.46 1472.35 5292.38 10341.43 United Kingdom 46627.26 8772.09 25538.44 63763.36 Total 10418.23 15691.72 25.61 63763.36 Source: Authors calculation Results of descriptive analysis show that France, Germany, Italy and United Kingdom have the highest mean level of total environment tax revenue in the analyzed period. In these countries, environment revenue are above thirty-five billion euro which is far more than other economies. The mean total environment tax revenue are 10418.23 billion euro, where only six countries recorded higher revenue level compared to average value in observed period. It implies that there is a greater difference between selected countries, where for example Germany has more than fifty billion euro which is far more than Baltic countries (Estonia, Latvia and Lithuania). The smallest standard deviation is identified in Malta (62.04), while United Kingdom and France had the highest value of standard deviation. It implies that these economies had no stability in environment revenue level in observed period. Table 2. Stationary tests Variable Levin-Lin-Chu test Im, Pesaran Shin test Augmented Dickey-Fuller test Phillips- Perron test GDP Intercept -11.83 -9.99 201.483 192.91 GDP Intercept & trend -10.81 -7.59 152.-55 149.92 Δ GDP Intercept -23.68*** -22.77*** 479.524*** 1073.35*** Δ GDP Intercept & trend -18.69*** -18.81*** 362.08*** 1255.52*** TET Intercept -2.18 -6.47 25.35 32.25 TET Intercept & trend -2.07 -0.04 64.32 50.18 ΔTET Intercept -16.67*** -14.27*** 293.24*** 347.92*** ΔTET Intercept & trend -15.29*** -13.21*** 250.35*** 310.03*** Source: Authors calculation The results of these tests show that selected variables are not stationary at level, but variables are stationary at first difference. It implies that null hypothesis can be rejected at the 1% when applying each variable at first difference. It can notice that these variables are stationary at first difference and integrated of order one process. After we confirm that variables are the first Vera Mitrović, Branimir Kalaš, Nada Milenković 99 difference, the next step is to estimate the long-run nexus between selected variables (Nguyen and Kakinaka, 2018). Table 3. Cointegration tests Cointegration GDP - TET TET – GDP Intecept Intercept & trend Intercept Intercept & trend Within-Dimension Panel v-statistic -2.27** -6.56*** -0.32** -4.78*** Panel rho-statistic -12.59*** -6.80*** -15.98*** -17.74*** Panel PP-statistic -26.72*** -31.69** -16.17*** -18.06*** Panel ADF-statistic -19.48*** -23.18** -15.51*** -17.98*** Between-Dimension Group rho-statistic -10.45*** -14.92*** -9.52*** -15.16*** Group PP-statistic -40.21** -50.89*** -16.89*** -17.49*** Group ADF-statistic -20.84*** -24.26*** -15.03*** -18.46*** Source: Authors calculation Table 3 presents panel cointegration test statistics between GDP and TET for analyzed period 1994-2018. The analysis manifests a cointegration between GDP and TET and can reject the null-hypothesis of no cointegration. Presence of a cointegration between GDP and TET implies that these variables move together in the long-run and we can conclude there is a long-run relation between GDP and TET in EU countries from 1994 to 2018. After identifying the cointegration relationship, the next step is to examine the cointegration coefficients of independent variables by using panel fully modified ordinary least squares (FMOLS) and panel dynamic ordinary least squares (DOLS) models (Bilgili et al. 2016). The long-run cointegration vector is analyzed by these panel models. Table 4. Results of different panel models Variable GDP Model OLS DOLS FMOLS TET 0.18 (0.03) 0.21 (0.01) 0.23 (0.02) R-squared 0.41 0.72 0.68 Source: Authors calculation Table 4 reflects the results of the panel OLS, DOLS and FMOLS estimators for EU countries. The empirical results show that TET have positive and significant effect on GDP. First, OLS shows that a 1% increase in revenue of total environmental taxes enhances GDP by 0.18% with 41% explanation of variations in this model. Second, DOLS reflects that a 1% increase in revenue of total environment taxes raises GDP by 0.21% with 72% explanation of variations in this model. Finally, FMOLS manifests that a 1% increase in revenue of total environmental taxes rises GDP by 0.23%. CONCLUSION Environmental policy is a necessary for sustainable economic development although some economists cite that society have to choose between environmental policy and economic growth. Environment taxes can be a very powerful tool to increase public revenues and contribute to the environment protection. Namely, these taxes can be more considered by EU countries to improve green economic activity and discourage”dirty” industries. This paper should reveal are environmental taxes statistically significant for economic growth in EU countries and the research examines the relationship between total environmental taxes and economic growth for 100 Economic Analysis (2021, Vol. 54, No. 1, 92-103) twenty-eight EU countries for the period 1994-2018. The objective of this paper is to evaluate the long-run relationship between these variables based on panel data analysis that includes panel cointegration test, and three models such as POLS, DOLS and FMOLS. The results show long-run relationship between total environmental taxes and economic growth in EU countries for the observed period. Empirical findings reflect that environmental taxes have a positive and significant impact on economic growth which implies that hypothesis H1 can be accepted. Precisely, results of different panel models manifest that a 1% increase in total environmental taxes enhances GDP, where FMOLS model has shown a greatest change of GDP by 0.23%. These empirical findings confirm previous research studies (Morley and Abdullah, 2010; Dökmen (2012; Abdullah and Morley, 2014; He et al. (2019) that have shown positive and significant relationship between these components. The contribution of the research is manifested in the fact that we have ensured the quantitative measurement of relation between total environmental taxes and economic growth in EU countries. The research has provided a better understanding of the relation between this type of taxes and economic growth, as well as the direct taxes and macroeconomic aggregates, as well as the character and intensity of their effects. REFERENCES Abdullah, S. and Morley, B. (2014). “Environmental Taxes and Economic Growth: Evidence from Panel Causality Tests”. Energy Economics, 42: 27 – 33. doi: 10.1016/j.eneco.2013.11.013. Adhikari, D. and Chen, Y. (2012). “Energy Consumption and Economic Growth: A Panel Cointegration Analysis for Developing Countries”. Review of Economics & Finance, 3: 68-80. Andrei, J., Miela, M., Popescu, G., Nica, E. and Cristina M. (2016). “The Impact and Determinants of Environmental Taxation on Economic Growth Communities in Romania”. Energies, 9: 1-11. DOI: 10.3390/en9110902 Alexeev, A., Good, D. H. and Krutilla, K. (2016). “Environmental taxation and the double dividend in decentralized jurisdictions”. Ecological Economics, 122: 90–100. DOI:10.1016/j.ecolecon.2015.12.004 Aubert, D. and Chiroleu-Assouline, M. (2019). “Environmental Tax Reform and Income Distribution with Imperfect Heterogeneous Labour Markets”. European Economic Review, 116: 60-82. DOI:10.1016/j.euroecorev.2019.03.006 Bachus, K., Van Ootegem, L. and Verhofstadt, E. (2019). “No taxation without hypothecation: towards an improved understanding of the acceptability of an environmental tax reform”. Journal of Enivornmental Policy & Planning, 21(4): 1-12. DOI: 10.1080/1523908x.2019.1623564 Bilgili, F., Koçak, E. and Bulut, Ü. (2016). “The dynamic impact of renewable energy consumption on CO 2 emissions: A revisited Environmental Kuznets Curve approach. Renewable and Sustainable Energy Reviews, 54: 838–845. doi:10.1016/j.rser.2015.10.080 Borozan, D. (2018). “Efficiency of Energy Taxes and the Validity of the Residential Electricity Environmental Kuznets Curve in the European Union”. Sustainability, 10(7): 1-16. DOI: 10.3390/su10072464 Busu, M. and Trica, C.L. (2019). “Sustainability of Circular Economy Indicators and Their Impact on Economic Growth of the European Union”. Sustainability, 11(19): 1-13. DOI: 10.3390/su11195481 Castiglione, C., Infante, D., Minervini, M. T. and Smirnova, J. (2014). “Environmental taxation in Europe: What does it depend on?” Cogent Economics & Finance, 2(1): 1-8. DOI:10.1080/23322039.2014.967362 Davidović, D., Harring, N. and Jagers, S. (2019). “The contigent effects of environmental concern and ideology: institutional context and people’s willingness to pay environmental taxes”. Environmental Politics, 1: 1-23. DOI: 10.1080/09644016.2019.1606882 Vera Mitrović, Branimir Kalaš, Nada Milenković 101 Dökmen, G. (2012). “Environmental Tax and Economic Growth: A Panel Var Analysis”. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Sayı, 40: 43-65. European Environmental Agency. (1996). In: GEE, D., editor. “Environmental Taxes: Implementation and Environmental Effectiveness”. Environmental Issues Series No. 1. Copenhagen: European Environment Agency Eurostat. https://ec.europa.eu/eurostat retrieved from https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_ac_tax&lang=en Eurostat. https://ec.europa.eu/eurostat retrieved from https://ec.europa.eu/eurostat/web/products-eurostat-news/-/ddn-20200219-1 Freire-González, J. (2018). “Environmental taxation and the double dividend hypothesis in CGE modelling literature: A critical review”. Journal of Policy Modeling, 40(1): 194–223. DOI:10.1016/j.jpolmod.2017.11.002 Freire-González, J. and Ho, M. S. (2019). “Carbon taxes and the double dividend hypothesis in a recursive-dynamic CGE model for Spain”. Economic Systems Research, 31(2): 1–18. DOI:10.1080/09535314.2019.1568969 Gao, X., Zheng, H., Zhang, Y. and Golsanami, N. (2019). “Tax Policy, Environmental Concern and Level of Emission Reduction”. Sustainability, 11(4): 1-17. DOI: 10.3390/su11041047 Golušin, M., Munitlak Ivanović, O., Filipović, S., Andrejević, A. and Djuran, J. (2013). “Environmental taxation in the European Union—Analysis, challenges, and the future”. Journal of Renewable and Sustainable Energy, 5(4): 1-13. doi:10.1063/1.4817963 Hájek, M., Zimmermannová, J., Helman, K. and Rozenský, L. (2019). “Analysis of carbon tax efficiency in energy industries of selected EU countries”. Energy Policy, 134: 1-11. doi:10.1016/j.enpol.2019.110955 He, P., Ya, Q., Chengfeng, L., Yuan, Y. and Xiao, C. (2019). “Nexus between Environmental Tax, Economic Growth, Energy Consumption, and Carbon Dioxide Emissions: Evidence from China, Finland, and Malaysia Based on a Panel-ARDL Approach”. Emerging Markets Finance & Trade, 57(3): 1-15. DOI: 10.1080/1540496X.2019.1658068 Heine, D., Norregaard, J. and Parry, I. (2012). “Environmental Tax Reform: Principles from Theory and Practice to Date”. IMF Working Paper 180, International Monetary Fund, Washington D.C. Hodžić, S. and Bratić, V. (2015). “Comparative analysis of environmental taxes in EU and Croatia”. Ekonomska misao i praksa, 24(2): 555-578. IMF. https://www.imf.org/ retrieved from https://www.imf.org/external/pubs/ft/weo/2019/02/weodata/weoselgr.aspx Kirchner, M., Sommer, M., Kratena, K., Kletzan-Slamanig, D. and Kettner-Marx, C. (2019). “CO2 taxes, equity and the double dividend – Macroeconomic model simulations for Austria”. Energy Policy, 126: 295–314. doi:10.1016/j.enpol.2018.11.030 Kosonen, K. and Nicodème, G. (2009). “The role of fiscal instruments in environmental policy”. European Commision, Working Paper No. 19. Krenek, A. and Schratzenstaller, M. (2017). “Sustainability-oriented tax-based own resources for the European Union: a European carbon-based flight ticket tax”. Empirica, 44(4), 665–686. DOI: 10.1007/s10663-017-9381-7 Labeaga, J. and Labandeira, X. (2020). “Economics of Environmental Taxes and Green Tax Reforms”. Sustainability, 12(1): 1-3. DOI: 10.3390/su12010350 Li, G. and Masui, T. (2018). “Assessing the Impacts of China’s Environmental Tax Using a Dynamic Computable General Equilibrium Model”. Journal of Cleaner Production, 208: 316- 324. DOI:10.1016/j.jclepro.2018.10.016 Liang, Q.M., Fan, Y. and Wei, Y.M. (2007). Carbon taxation policy in China: How to protect energy and trade intensive sectors? Journal of Policy Modelling, 29: 311-333. Lin, B. and Li, X. (2011). “The effect of carbon tax on per capita CO2 emissions”. Energy Policy, 39(9): 5137–5146. DOI: 10.1016/j.enpol.2011.05.050 102 Economic Analysis (2021, Vol. 54, No. 1, 92-103) Liobikiene, G., Butkus, M. and Matuzevičiūtė, K. (2019). “The Contribution of Energy Taxes to Climate Change Policy in the European Union (EU)”. Resources, 8(2): 1-23. DOI: 10.3390/resources8020063 Loganathan, N., Shahbaz, M. and Taha, R. (2014). “The link between green taxation and economic growth on CO2 emissions: Fresh evidence from Malaysia”. Renewable and Sustainable Energy Reviews, 38: 1083-1091. DOI: 10.1016/j.rser.2014.07.057 Machin, A. (2019). “Changing the story? The discourse of ecological modernisation in the European Union”. Environmental Politics, 28(2): 208–227. doi:10.1080/09644016.2019.1549780 Maxim, M., and Zander, K. (2019). “Can a Green Tax Reform Entail Employment Double Dividend in European and non-European Countries? A Survey of the Empirical Evidence”. International Journal of Energy Economics and Policy, 9(3): 218-228. Maxim, M., Zander, K., and Patuelli, R. (2019). “Green Tax Reform and Employment Double Dividend in European and Non-European Countries: A Meta-Regression Assessment”. International Journal of Energy Economics and Policy, 9(4): 342-355. Mirović, V., Kalaš, B. and Andrašić, J. (2019). “The Modelling of Tax Influence on Macroeconomic Framework in Spain”. Economic Analysis, 52(2): 128-136. DOI: 10.28934/ea.1952.2 Mitić, P., Mutilak Ivanović, O. and Zdravković , A. (2017). „A Cointegration Analysis of Real GDP and CO2 Emissions in Transitional Countries“. Sustainability, 9(4): 1-18. DOI: 10.3390/su9040568 Mitić, P., Kresoja, M. and Minović, J. (2019). “A Literature Survey of the Environmental Kuznets Curve“. Economic Analysis, 52(1): 109-127. Morley, B. and Abdullah, S. (2010). “Environmental Taxes and Economic Growth: Evidence from Panel Causality Tests”. Bath Economics Research Papers, No. 04/10. Munitlak Ivanović, O. and Golušin, M. (2012). “Environmental Taxation as a Tool for Sustainable Development Policy-State Comparison of Serbia and Application of Ecological Taxation Reform in European Union”. Economic Analysis, 45, (1-2): 32-44. Nguyen, K. H. and Kakinaka, M. (2018). “Renewable energy consumption, carbon emissions, and development stages: Some evidence from panel cointegration analysis”. Renewable Energy. 132: 1049-1057. doi:10.1016/j.renene.2018.08.069 Pautrel, X., (2009). “Pollution and life expectancy: How environmental policy can promote growth”. Ecological Economics, 68: 1040-1051. Piciu, G.C. and Trică, C.L. (2012). “Trends in the Evolution of Environmental Taxes“. Procedia Economics and Finance, 3: 716-721. DOI: 10.1016/S2212-5671(12)00219-5 Radulescu, M., Sinisi, C.I., Popescu, C., Iacob, S.E. and Popescu, L. (2017). “Environmental Tax Policy in Romania in the Context of the EU”. Sustainability, 9(11): 1-20. DOI: 10.3390/su9111986 Sanyé-Mengual, E., Secchi, M, Corrado, S., Beylot, A. and Sala, S. (2019). “Assessing the decoupling of economic growth from environmental impacts in the European Union: A consumption-based approach”. Journal of Cleaner Production, 236: 1-16. DOI:10.1016/j.jclepro.2019.07.010 Sasmaz, M.U. (2016). “Validity of double dividend hypothesis in EU-15 countries”. Global Journal on Humanities & Social Sciences, 4: 30-36. Stram, B.N. (2014). “A new strategic plan for a carbon tax”. Energy Policy, 73: 519–523. DOI: 10.1016/j.enpol.2014.05.023 Tantau, A.D., Maassen, M.A., and Fratila, L. (2018). “Models for Analyzing the Dependencies between Indicators for a Circular Economy in the European Union“. Sustainability 10(7): 1-13. DOI: 10.3390/su10072141 Vukadinović, S. and Ješić, J. (2019). “Green jobs: Potential for employment in the Republic of Serbia”. The Annals of the Faculty of Economics in Subotica, 55(41): 115-129. Vera Mitrović, Branimir Kalaš, Nada Milenković 103 Wesseh, P.K., Jr., Lin, B. and Atsagli, P. (2017). “Carbon taxes, industrial production, welfare and the environment”. Energy, 123: 305–313. Wesseh, P. K. and Lin, B. (2019). “Environmental policy and “double dividend” in a transitional economy”. Energy Policy, 134: 1-7. DOI:10.1016/j.enpol.2019.110947 Withana, S., ten Brink, P., Illies, A., Nanni, S. and Watkins, E. (2014). “Environmental Tax Reform in Europe: Opportunities for the future”. Institute for European Environmental Policy, Yang, J., Chen, M.-L., Fu, C.-Y., and Chen, X.-D. (2019). “Environmental policy, tax, and the target of sustainable development”. Environmental Science and Pollution Research, 27: 12889-12898. DOI: 10.1007/s11356-019-05191-1 Zhou, Z., Zhang, W., Pan, X., Hu, J., and Pu, G. (2020). “Environmental Tax Reform and the “Double Dividend” Hypothesis in a Small Open Economy”. International Journal of Environmental Research and Public Health, 17(1): 1-21. DOI: 10.3390/ijerph17010217 Article history: Received: April 24, 2020 Accepted: April 29, 2021