Showing detailed description of variables.
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More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
\n'}],latestNews:[{slug:"intechopen-maintains-position-as-the-world-s-largest-oa-book-publisher-20201218",title:"IntechOpen Maintains Position as the World’s Largest OA Book Publisher"},{slug:"all-intechopen-books-available-on-perlego-20201215",title:"All IntechOpen Books Available on Perlego"},{slug:"oiv-awards-recognizes-intechopen-s-editors-20201127",title:"OIV Awards Recognizes IntechOpen's Editors"},{slug:"intechopen-joins-crossref-s-initiative-for-open-abstracts-i4oa-to-boost-the-discovery-of-research-20201005",title:"IntechOpen joins Crossref's Initiative for Open Abstracts (I4OA) to Boost the Discovery of Research"},{slug:"intechopen-hits-milestone-5-000-open-access-books-published-20200908",title:"IntechOpen hits milestone: 5,000 Open Access books published!"},{slug:"intechopen-books-hosted-on-the-mathworks-book-program-20200819",title:"IntechOpen Books Hosted on the MathWorks Book Program"},{slug:"intechopen-s-chapter-awarded-the-guenther-von-pannewitz-preis-2020-20200715",title:"IntechOpen's Chapter Awarded the Günther-von-Pannewitz-Preis 2020"},{slug:"suf-and-intechopen-announce-collaboration-20200331",title:"SUF and IntechOpen Announce Collaboration"}]},book:{item:{type:"book",id:"371",leadTitle:null,fullTitle:"Abiotic Stress in Plants - Mechanisms and Adaptations",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",reviewType:"peer-reviewed",abstract:"World population is growing at an alarming rate and is anticipated to reach about six billion by the end of year 2050. On the other hand, agricultural productivity is not increasing at a required rate to keep up with the food demand. The reasons for this are water shortages, depleting soil fertility and mainly various abiotic stresses. The fast pace at which developments and novel findings that are recently taking place in the cutting edge areas of molecular biology and basic genetics, have reinforced and augmented the efficiency of science outputs in dealing with plant abiotic stresses. In depth understanding of the stresses and their effects on plants is of paramount importance to evolve effective strategies to counter them. This book is broadly dived into sections on the stresses, their mechanisms and tolerance, genetics and adaptation, and focuses on the mechanic aspects in addition to touching some adaptation features. The chief objective of the book hence is to deliver state of the art information for comprehending the nature of abiotic stress in plants. We attempted here to present a judicious mixture of outlooks in order to interest workers in all areas of plant sciences.",isbn:null,printIsbn:"978-953-307-394-1",pdfIsbn:"978-953-51-4431-1",doi:"10.5772/895",price:139,priceEur:155,priceUsd:179,slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",numberOfPages:442,isOpenForSubmission:!1,isInWos:1,hash:"588466f487e307619849d72389178a74",bookSignature:"Arun Shanker and B. Venkateswarlu",publishedDate:"September 22nd 2011",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",numberOfDownloads:145933,numberOfWosCitations:330,numberOfCrossrefCitations:158,numberOfDimensionsCitations:490,hasAltmetrics:1,numberOfTotalCitations:978,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 17th 2010",dateEndSecondStepPublish:"December 15th 2010",dateEndThirdStepPublish:"April 21st 2011",dateEndFourthStepPublish:"May 21st 2011",dateEndFifthStepPublish:"July 20th 2011",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,8,9",editedByType:"Edited by",kuFlag:!1,editors:[{id:"58592",title:"Dr.",name:"Arun",middleName:null,surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker",profilePictureURL:"https://mts.intechopen.com/storage/users/58592/images/1664_n.jpg",biography:"Arun K. Shanker is serving as a Principal Scientist (Plant Physiology) with the Indian Council of Agricultural Research (ICAR) at the Central Research Institute for Dryland Agriculture in Hyderabad, India. He is working with the ICAR as a full time researcher since 1993 and has since earned his Advanced degree in Crop Physiology while in service. He has been awarded the prestigious Member of the Royal Society of Chemistry (MRSC), by the Royal Society of Chemistry, London in 2015. Presently he is working on systems biology approach to study the mechanism of abiotic stress tolerance in crops. His main focus now is to unravel the mechanism of drought and heat stress response in plants to tackle climate change related threats in agriculture.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"4",institution:{name:"Indian Council of Agricultural Research",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:{id:"153612",title:"Dr.",name:"Bandi",middleName:null,surname:"Venkateswarlu",slug:"bandi-venkateswarlu",fullName:"Bandi Venkateswarlu",profilePictureURL:"https://mts.intechopen.com/storage/users/153612/images/system/153612.jpg",biography:"Dr. B.Venkateswarlu has started his career as a Research Associate in ICRISAT\nin 1976 with biological nitrogen fixation as the initial research subject. He joined\nagricultural research service (ARS) of ICAR in 1977 and posted as Scientist S-1 at\nCentral Arid Zone Research Institute (CAZRI), Jodhpur. He initiated research for the\nfirst time on desert microbiology and quantified the impact of sand dune stabilization\non soil microflora dynamics in the desert eco system. He also developed several\nstrains of nitrogen fixing and P-solubilizing microorganisms for arid legumes. He\nmoved to Central Research Institute for Dryland Agriculture (CRIDA) in 1986 as\nSenior Scientist and pursued research in the areas of soil fertility management,\nbiofertilizers and bio-pesticides. He was appointed as Principal Production System\nScientist (PPSS) of the National Agricultural Technology Project (NATP) in 2001in\nwhich he served upto 2006. Under this project, more than 100 production system\nresearch projects were coordinated by him in the rainfed agro-eco-system across the\ncountry. He joined as Head of the Division of Crop Sciences in 2006 and then\nappointed as Director of the Institute in July, 2008. He is now holding this research\nmanagement position directing and coordinating the research programmes of\nCRIDA on rainfed agriculture, two coordinated projects on Dryland Agriculture and\nAgrometeorology and one network project viz. Climate Change. His current areas\nof research include, rainfed agriculture, rural livelihoods, NRM and climate change.\nDr.Venkateswarlu is the follow of National Academy of Agricultural Sciences\n(NAAS), Fellow of Indian Society of Oilseeds Research, President of Indian Society\nof Dryland Agriculture Research, Member, New York Academy of Sciences and life\nmember of several Academic and Professional Societies in India. He is on the\nBoard of AP Horticulture University, Academic Council Member of MPKVV, Rahuri,\nSteering Committee member of Expert group on Integrated Watershed Management\nProject (IWMP) of Ministry of Rural Development, Government of India and Expert\nPanel Member of National Disaster Management Authority. He served as the\nMember of the Sub-group of ICAR to prepare the Mission on Sustainable Agriculture\nDocument under the National Action Plan on Climate Change. He visited several\ncountries on bilateral programmes and as scientific expert. He published over 100\nresearch papers, 10 books and holds one patent.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Central Research Institute for Dryland Agriculture",institutionURL:null,country:{name:"India"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"407",title:"Agricultural Microbiology",slug:"agricultural-microbiology"}],chapters:[{id:"18395",title:"Imaging of Chlorophyll a Fluorescence: A Tool to Study Abiotic Stress in Plants",doi:"10.5772/22281",slug:"imaging-of-chlorophyll-a-fluorescence-a-tool-to-study-abiotic-stress-in-plants",totalDownloads:5101,totalCrossrefCites:8,totalDimensionsCites:16,signatures:"Lucia Guidi and Elena Degl’Innocenti",downloadPdfUrl:"/chapter/pdf-download/18395",previewPdfUrl:"/chapter/pdf-preview/18395",authors:[{id:"47052",title:"Dr.",name:"Lucia",surname:"Guidi",slug:"lucia-guidi",fullName:"Lucia Guidi"},{id:"59510",title:"Dr.",name:"Elena",surname:"Degl'Innocenti",slug:"elena-degl'innocenti",fullName:"Elena Degl'Innocenti"}],corrections:null},{id:"18396",title:"Salinity Stress and Salt Tolerance",doi:"10.5772/22331",slug:"salinity-stress-and-salt-tolerance",totalDownloads:21029,totalCrossrefCites:43,totalDimensionsCites:110,signatures:"Petronia Carillo, Maria Grazia Annunziata, Giovanni Pontecorvo, Amodio Fuggi and Pasqualina Woodrow",downloadPdfUrl:"/chapter/pdf-download/18396",previewPdfUrl:"/chapter/pdf-preview/18396",authors:[{id:"47290",title:"Prof.",name:"Giovanni",surname:"Pontecorvo",slug:"giovanni-pontecorvo",fullName:"Giovanni Pontecorvo"},{id:"47803",title:"Dr.",name:"Pasqualina",surname:"Woodrow",slug:"pasqualina-woodrow",fullName:"Pasqualina Woodrow"},{id:"47804",title:"Prof.",name:"Petronia",surname:"Carillo",slug:"petronia-carillo",fullName:"Petronia Carillo"},{id:"47808",title:"Prof.",name:"Amodio",surname:"Fuggi",slug:"amodio-fuggi",fullName:"Amodio Fuggi"},{id:"47809",title:"Dr.",name:"Maria Grazia",surname:"Annunziata",slug:"maria-grazia-annunziata",fullName:"Maria Grazia Annunziata"}],corrections:null},{id:"18397",title:"Abiotic Stress in Harvested Fruits and Vegetables",doi:"10.5772/22524",slug:"abiotic-stress-in-harvested-fruits-and-vegetables",totalDownloads:7234,totalCrossrefCites:1,totalDimensionsCites:21,signatures:"Peter M.A. Toivonen and D. 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Conversations on emission and its effects on the economy and environment are increasing especially in developed countries. Among the key issues surrounding discussions on emission is the impact of taxation on carbon emission and environmental sustainability. There is unanimity among researchers on the effect of emissions on the environment. That is to say, emissions cause environmental degradation, diseases, reduces household welfare and are detrimental to economic growth and development [1, 2, 3]. In this light, it is evident that climate change has become a global problem [4]. This global problem has awakened the need for governments worldwide to invent techniques to minimise environmental issues and emissions. Some of the methods include subsidies, ecological laws, taxes, environmental policies and awareness programs [5]. Of particular importance are taxes which are an integral instrument in dealing with emission [6]. The significance of taxation on emission and environmental degradation has captured the attention of researchers and policymakers in developing policies and recommendations on minimising emission.
There is a noticeable increase in taxation on emissions and environmental sustainability in the European Union (EU). Taxation takes the form of energy tax, environment and transports tax especially, in Slovenia, Poland, France, Portugal, Finland, Latvia, Ireland and Denmark [7]. The main purpose of these taxes is to minimise emissions up to an acceptable level of 5 percent [8]. Furthermore, the government introduced environmental and emission taxes to reduce negative externalities caused by third parties in production and consumption since nobody takes responsibility for creating them [9]. The negative externalities include pollution, land degradation and the greenhouse effect that tends to cause diseases, low standards of living, low quality of products, reduction in income and energy consumption [10]. Since firms do not take any responsibility, the EU has taken the responsibility of reducing emissions to an acceptable standard [11]. Thus, fiscal authorities have imposed a certain amount of $50–100 per ton on production for any environmental misuse and emission [11]. Tax experts argue that the $50–100 per ton tax that is not shown in the final price of goods and services covers the social costs suffered by the third party [2]. Furthermore, environmental and emission taxes increase government revenue and contribute to economic growth significantly. A survey conducted by Sterner and Kohlin [12] found that environmental and emission tax contributes 8 percent of the government revenue and 3 percent of economic growth in the European Union region.
The introduction of environment and emission taxes has sparked heated debates among scholars. The main crust of these debates is whether taxation is an effective way of reducing environmental emissions. Noteworthy is the complementary school of thought which contends that tax on environmental emission addresses market failures to an acceptable standard and reduces health diseases [3, 8]. This means that taxation on emissions brings about efficiency and effectiveness in the production of goods and services since firms get to develop new regulations that foster efficiency and reduce the cost of production. Also, environmental tax improves the quality of the products produced in production processes [13]. On the other, the substitutive school of thought argues that taxes on emission are inclined to fiscal policies rather than environmental policies [14]. The substitutive school of thought recognises that environmental and emission taxes focus more on raising government revenue than reducing emissions as such taxes tend to be regressive as prices of goods and services change [15]. In this sense, the substitutive school of thought concludes that taxation does more harm than good because it causes a greater degree of the loss of welfare as compared to emission. Therefore, this study envisaged contributing to the current debate on tax on emissions and environmental sustainability.
Central to the problem is that environmental pressures are a global phenomenon. The European Union is not exempted from this problem. Environmental pressures have become an issue of concern as the emission threat has increased over the past years. Another factor that has become a cause for concern is the forecast by economists that emissions are likely to increase to 35 percent, and this poses a threat to environmental sustainability [16]. Of importance is that these environmental pressures pose a risk to people’s health, welfare, and economy. Astuti and Maryono [17] note that emissions cause health diseases such as eye irritation, asthma, and pneumonia. Emissions and environmental pressures do not only undermine the environment and health faculties but affect the economic operations of a country as well. There is no doubt that these challenges should be addressed. The economic theory prescribes many methods of solving these challenges. Such methods include environmental tax, fuel tax, awareness programs, subsidies to mention but a few. Relevant to this study is environment taxation and tax emission, which are the main focus of this study. Hence, this study investigated the influence of emission on selected EU countries.
The purpose of the study is to contribute to the existing literature on environmental accounting significantly. Most of the studies have focused on the effects of tax on carbon emission [2, 6, 18, 19]. However; this study takes a different stance by examining the environmental influence of tax structures in selected EU economies by taking into account both short-run and long-run dynamics. The study focused on other variables that are immensely important to environmental issues and yet are barely used by other researchers. These variables include research and development, production scores, eco-innovation ratings and the different types of tax such as energy, transport, and environmental tax. The authors of this study conducted a thorough search of the relevant literature. They found no study that combined all the variables in one study to investigate the environmental influence of tax structures in selected EU economies. Hence, the current paper covers this research gap to find robust results that are important to policymakers. Furthermore, the results and the nature of the research provide a niche for future researchers focusing on few limitations of the study. The study also contributes to the body of existing knowledge on natural environmental studies.
Therefore, this paper is organised as follows. The literature review is summarised in the next section. The methodology and variables used in the study are discussed in Section 3. This also includes the source of the data and prior expectations. The empirical results and analysis are discussed in Section 4, while Section 5 consists of the summary, conclusion, recommendations, and limitations of the study.
The introduction of environment tax in the European Union can be traced back to 1990 [20]. Since then, it has received attention from various governments intending to minimise environmental degradation. The idea was to charge polluters a certain fee per unit of the damage they have caused to third parties. In line with this objective, the European Union introduced four types of environment tax, namely energy, transport, pollution and resources tax [12]. For the purposes of this study, researchers focused on energy tax and transport tax as they are widely used in the European Union. Eurostat [21] defined energy tax as a certain amount paid by the energy sector for causing negative externalities. Energy tax target polluters who make use of petrol, diesel, biofuels, electricity consumption and carbon fuels [21]. The energy tax is mainly used in Italy, Germany, Netherlands, France, Sweden and Finland as they use heavy power plants and consumes much electricity compared to other countries [22]. This also implies that these countries receive more tax revenue from electricity tax while Sweden and Denmark get more revenue from fuel tax. Second is the transport tax, which is an amount paid for making use of vehicles and vehicle ownership [23]. It includes the importation of motor vehicles, flight tickets, toll gates, car registrations and insurances [21]. This form of tax was introduced to raise revenue and minimise greenhouse gas emissions. The European Commission [24] reports that 25 percent of greenhouse gas emissions are caused by the transport sector of which road transport contributes 75 percent to these transport emissions followed by civil aviation and navigation respectively. This type of emission is common in Norway, Netherlands, Finland, Greece, Spain and Denmark.
Noteworthy is that energy tax is widely used in the region to reduce greenhouse gas emission. There has been an increase in the use of tax that leads to an increase in the energy tax revenue since 2000–2018. The increase in revenue has also led to the rise in the Gross Domestic Product. The contribution of environmental tax to GDP was experienced a decade later after the introduction of the environment tax in 1990. Notably is the 5 percent contribution from 2013 to 2019. Despite the use of environmental tax, the Eurostat [21] found contrasting results in the European Union. On one hand, it is a significant increase in greenhouse emission in countries such as Germany, France and Italy. On the other hand, it is a significant decrease in greenhouse emission in countries such as Lithuania, Latvia and Romania [25]. From the discussions, the environment tax influences greenhouse gas emission differently in the European Union individual countries depending on the environment policies used by each country towards eradicating the environment hazards. The question still remains: Does environmental tax reduces greenhouse emission and improves environmental sustainability since its implementation is influenced by price elasticity of energy and transport demand?
This section is divided into two parts. The first part examines how tax and other variables influence carbon emissions in selected economies. The second part evaluates how tax frameworks affect environmental sustainability in countries studied.
The influence of emission tax cannot be separated from past studies on taxation, economy and environmental economics. For instance, a survey carried out by Miller and Vella [19] investigated whether taxes are effective in dealing with pollution. The study examined if taxes on emission help to produce quality products. The study targeted 50 countries across all the regions and used panelised dynamic regression models. The results of the study revealed that taxes reduce carbon emission in all the countries. Also, the study showed that the quality of products is improved if the polluters are taxed. Similarly, Metcalf [6] achieved the same results that carbon tax reduces carbon emissions in Britain, Columbia and the United States of America. Metcalf [6] further observed that taxation on emission improves employment and economic growth. Worthy of note is that the preceding studies present a negative relationship between carbon tax and carbon emission. Thus, taxation on emission is the most effective way of reducing emissions to an acceptable level. The studies concur that taxes reduce environmental pollution despite their difference in geographical location.
In South Africa, carbon tax also has an inverse relationship with emission. This result was concluded by [2] who examined the effects of carbon tax on the economy. The study employed the dynamic Computable General Equilibrium modeling methodology and found an inverse relationship between carbon tax and emission. The study further showed that carbon tax is negatively related to economic growth. Thus, the more firms pay carbon tax the fewer goods and services they produce, thereby compromising economic growth. Klier and Linn [26] concur with these results as they reach the same conclusion after using the panel regression analysis in Sweden, France, and Germany. The authors’ objective was to investigate the relationship between vehicle carbon taxation and carbon vehicle emission. This relationship was prevalent in France compared to other countries. Since firms were taxed for emission, a decrease in emissions from vehicles was experienced in all the countries. The common denominator between these two studies is that taxation has a negative effect on economic growth despite the use of different methodologies and geographical locations. A salient point to note on the carbon tax is that it discourages firms to be innovative and this leads to a decrease in investment and eventually a decrease in economic growth.
Lin and Li [18] using a panel regression analysis, examined the impact of carbon tax on carbon emission in selected European countries. The authors found three sets of results: a negative relationship between carbon tax and emission in Finland; a positive relationship between carbon tax and emission in Norway and no relationship was identified in Netherlands, Denmark, and Sweden. Since Norway is one of the heavy carbon polluters in Europe, taxing the firms reduced emission. The same result was achieved by Di Cosmo and Hyland [27] who concluded that carbon tax is an effective way of reducing emissions in Norway. On the other hand, in the Netherlands, Denmark and Sweden carbon tax did not influence carbon emission. This result is contrary to the findings of Lin and Li [18] who found an inverse relationship between carbon tax and emissions. The authors further propounded that fiscal authorities should increase tax on emitters for carbon tax to be effective. Moreover, an interesting result is the positive relationship between carbon tax and carbon emission found in Norway. This result is not common in the Organization for Economic Co-operation and Development (OECD) since all the governments joined hands to reduce emissions through the Piogiouvot method.
Anderson [28] inquired whether a carbon tax is the solution to greenhouse emissions. The author used 11 European Union countries as his case study. To achieve the aim of the study, the author employed a quasi-experiment and found that tax curtailed emissions by 11 percent. The study confirmed the economic theory that prescribes that carbon tax deals with negative externalities whilst also reducing emissions. A similar result was found in Norway by Bruvoll and Larsen [29]. The authors employed simulations and a diverse index from 1990 to 1999 and the study revealed an emission reduction of 2.3 percent. Revoredo-Giha et al. [30] examined the impact of carbon taxes on greenhouse emissions in the United Kingdom. The study showed that carbon tax reduces greenhouse emissions. Gonzalez [31] and Haites [32] concur with the above-mentioned studies by reiterating that carbon tax is the best instrument to reduce greenhouse emissions and the most effective approach in reducing emissions.
Concerning the relationship between economic growth and emission, Ameyaw and Yao [33] analysed the impact of economic growth on carbon emission in West African countries from 2007 to 2014 using panel regression. The results show an unidirectional cause from GDP to carbon emission. Thus, an economy that taxes emissions is likely to improve economic growth. The same result was also achieved by Asongu et al. [34] who investigated carbon emissions and economic growth and found a relationship running from economic growth to carbon emission to energy consumption. An interesting result was found by [35] who examined the effects of economic growth on emission in developing countries. The study used panel analysis and found a negative relationship between economic growth and emissions while [36] found no link. The study examined the link between energy consumption, emissions and economic growth in the Middle East and North Africa (MENA). The rationale behind this finding is that taxation discourages firms to produce more goods and services due to increased cost of production.
Other authors emphasised the fact that carbon tax on emission is regressive in nature and leads to loss of welfare [14, 15]. For instance, Devarajan et al. [15] found that taxes on carbon emission reduce household welfare by 40 percent, whilst also reducing carbon emission by 15 percent. In other words, carbon tax works better in reducing household welfare than in minimising emission, its main objective. The study further found that carbon tax is regressive as poor households spend more than 50 percent of their salaries on taxed goods and services. This result was also found by [14]. Marx and Slamang [37] and Sterner [38] examined the relationship between energy and carbon tax on emissions in European Union countries. The study concluded that transport taxes, energy and carbon taxes are regressive.
Liobikiene et al. [39] investigated the role of energy taxes on climate change in the European Union. The main focus was to check if environmental tax influences environmental sustainability. The authors applied panel data methods and found that environmental tax influences environmental sustainability in a positive way. The same results were found by Nerudova et al. [40] who examined the tax system and environmental sustainability in the European Union and found a positive relationship between the two. Park and Yoon [41] studied the link between environment tax and sustainable development in China, Japan and Korea using a survey. The study revealed a positive relationship between the two in all these countries. It seems the above-mentioned studies point to a positive relationship between taxation and environmental sustainability. Thus, taxation on environmental pollution improves environmental sustainability. A study by Radulescu et al. [42] in Romania employed the Ordinary Least Square and Vector Error Correction Model. The authors found a negative relationship between environmental sustainability and environmental tax. The authors argued that fiscal authorities should use other methods other than taxation to achieve environmental sustainability.
Streimikiene et al. [43] added economic growth as a variable that was not examined by [39, 42] by investigating the role of green tax on sustainable energy development in Baltic countries. The study found a positive relationship between environmental tax, economic growth and environmental sustainability. The authors propounded that taxation ensures environmental sustainability that has a direct influence on economic growth. Kurniawan and Managi [44] and Moisesca [45] arrived at the same conclusion by examining the relationship between economic growth and sustainable development in Indonesia from 1990 to 2014. The study used the inclusive wealth framework and found that economic growth influences environmental sustainability in a positive way. From all the studies that examined the link between economic growth and environmental sustainability, a positive relationship was achieved therein.
Urbaniec [46] conducted a study on eco-innovation and environmental sustainability. The main objective was to assess the role played by eco-innovation on environmental sustainability. The study concluded that eco-innovation minimises environmental damage. Similar results were also concluded by [47] who carried out a study on the role of eco-innovation and environmental sustainability in Malaysia. The findings of both studies point to the fact that an increase in environmental compliance improves the environment. Another common denominator is that both studies used the same methodology: the theoretical structural model and found similar results. The eco-innovation is also positively linked to Research and Development, thus Powe [48] found that research and development have a positive impact on environmental sustainability. The authors argued that Research and Development yields results in big sectors, while in small sectors a link was not found. The same results were also found by [49] who examined the green economy and sustainable development worldwide from 2002 to 2010. The study found that research and development have a positive impact on environmental sustainability. However, Sauvé et al. [50] found a negative relationship between Research and Development and environmental sustainability. The authors arrived at this conclusion after employing an ordinary least square first difference.
Kim and Yoon [51] examined the relationship between environmental sustainability and production in manufacturing firms. The objective of the study was to check the impact of production on environmental sustainability. The results reveal that production has a positive influence on environmental sustainability. The same results were also found by [52] who examined environmental sustainability and production. The preceding results differ from those achieved in the study done by [53] who examined the relationship between sustainable environment and production using the trend and content analysis. The study found that production causes environmental hazards. The author concluded that production in developing countries over utilises resources with the objective of combating poverty. On the other hand, production in developed countries over utilises resources for export purposes.
Saud et al. [54] examined the link between energy use, government expenditure and financial development in Venezuela from 1971 to 2013. The study employed an autoregressive distributed lag (ARDL) model and found a positive link between energy use and environmental degradation. The study further revealed a negative relationship between land degradation and government expenditure. A study carried out by Uwazi [55] and You and Haung [56] examined the link between green growth and environmental sustainability in the OECD. The study looked at 30 provinces using panel data. The results show a positive relationship between government spending and green growth. A similar study was done by Oyebanji et al. [57] who conducted a study on green growth and environmental sustainability in Nigeria. The study considered energy depletion, forestry, carbon dioxide and employed the ARDL model. The study found a negative relationship between carbon emission, environmental depletion, and greenhouse energy. On the other hand, a positive relationship was found between green growth and deforestation.
From the empirical literature reviewed, there is no consensus on how taxes influence emission. Certain authors support a positive relationship between the variable, others see no link, while others support a negative relationship. Given such a scenario, the study, therefore, contributes to the existing literature by examining the influence of tax on emission.
This paper is based on associations among tax structures, environmental variables, income, production, transport, eco-innovation and green investments in a panel of 28 economies over a period of 7 years, that is, 2010 to 2017. The 7-year period was deemed sufficient due to data availability and sufficient cross-sections. These variables were chosen as they have a potential impact of reducing or increasing greenhouse gas emissions and environmental sustainability. The generalised below equations form the basis of the hypothesis.
And more specifically,
And also,
Where,
LogGHG shows greenhouse gas emissions.
An environmental tax is a certain amount that is imposed to environment polluters [21]. For the purposes of this study, environment tax includes the energy tax and transport tax and it is expected to reduce greenhouse gas emissions and increase environment sustainability depending with the price elasticity demand of energy and transport. The rationale is that environmental tax should create awareness to switch to energy efficiency and turn to other clean alternative fuels. Energy tax is the tax that is levied on the energy sector for polluting the environment [58]. Energy tax includes the consumption of petrol, diesel, petrol, diesel, biofuels, electricity consumption and carbon fuels [21]. Transport tax is a tax that pertains to the use of all vehicles in the European Union [23]. The aforementioned taxes are expected to reduce the green house emission at the same time promote environmental sustainability. Energy consumption is the energy used in both industries and at household level which is measured in tonnes of oil [59]. The study expects energy consumption to increase greenhouse gas emissions and reduce environmental sustainability.
Green Research and Development is defined as new innovations introduced to minimise emissions and climate change in the European Union [60]. A positive relationship between Green Research and Development and environment sustainability is expected while an inverse relationship on greenhouse gas emission is expected. The rationale is that new innovations provide better ways of energy use that minimises climate change. Likewise, eco-innovation includes all ideas from stakeholders to develop new products and processes that reduces environmental degradation [61]. Eco-innovation reduces the greenhouse emissions and increases the environmental sustainability.
Production is a scientific procedure of turning all the inputs into consumable goods and services of a certain good and service [62]. Since production makes use of energy, the variable is expected to positively contribute to greenhouse gas emission and reduces the environmental sustainability in the European Union. Gross Domestic Product entails the value of all goods and services produced in the European Union countries over a specified period [63]. The priori expectation is that GDP increases greenhouse emission and decreases environment sustainability in the short-run while betters environment sustainability in the long-run. Government spending is the money spent by the government in acquiring public goods and services [64]. Government expenditure is expected to increase greenhouse expenditure if less or no expenditure is done on reducing climate change. On the other hand, the greenhouse expenditure is likely to reduce if the government spent much on improving climate change.
From Table 1, the logarithm of greenhouse gas along with logarithm of adjusted net savings (excluding particulate emission damage) depicts the dependent variables. The remaining variables are all explanatory variables. All the variables were extracted from the Eurostat database with the exception of the logarithm of adjusted net savings (excluding particulate emission damage) which is the only variable gathered from the World Development Indicators (World Bank) database.
Variable | Definition | Unit | Source |
---|---|---|---|
LogETT | Logarithm of Environmental Tax | Percentage of gross domestic product (GDP) | Eurostat |
LogENT | Logarithm of Energy Tax | Percentage of gross domestic product (GDP) | Eurostat |
LogTRT | Logarithm of Transport Tax | Percentage of gross domestic product (GDP) | Eurostat |
LogGHG | Logarithm of Greenhouse gas emissions | Greenhouse gas emissions per capita | Eurostat |
LogEC | Logarithm of Energy consumption | Thousand tonnes of oil equivalent | Eurostat |
LogGRD | Logarithm of Green Research & Development | Percentage of gross domestic product (GDP) | Eurostat |
LogGDP | Logarithm of GDP | Current prices, million units of national currency | Eurostat |
LogGE | Logarithm of Government Expenditure | Percentage of gross domestic product (GDP) | Eurostat |
LogECO | Logarithm of Eco-innovation Index | Yearly scores against the EU = 100 averaged score. | Eurostat |
LogPDN | Logarithm of production | Yearly scores based on Index, 2015 = 100 | Eurostat |
LogANS | Logarithm of adjusted net savings, excluding particulate emission damage | Current US$ | World Development Indicators (World Bank) |
Showing detailed description of variables.
Note: The Logarithm of Greenhouse gas emissions and Logarithm of adjusted net savings, excluding particulate emission damage indicates the dependent variable. The remaining variables are all explanatory variables.
The paper deployed the panel dynamic Generalised Method of Moments (GMM) as the main approach to address problems connected with, heteroskedasticity serial correlation and heterogeneity [65]. The GMM captures several common estimators that offers a valuable basis for comparison purposes [66]. It is considered as one of the best methods since it not biased, consistent compared to Fixed effects, Pooled Estimates and Ordinary Least Squares [67]. Furthermore, the model allows researchers to make use of many independent variables without facing the endogeneity problems. Thus, the model provides the robust coefficients through the automatic correction of biasness. Several researchers such as Leve and Kapingura [68], Meraya et al. [69] and Nayan et al. [70] have employed the GMM.
For the purposes of this study, it is apparent that Eq. (1) is comprised of country time effects as well as country fixed effects which is inevitably generates the problem of unobserved country-specific heterogeneity. Thus, Arellano and Bond [71] highlights that GMM is able to transform such particular equations through first difference estimators. Research also shows that the GMM approach is largely suitable in surveys where the cross-section identifiers are greater in quantity (in this study, N = 28) against small time periods (in this article, T = 7 years) [72]. Overall, panel regression problems such as heterogeneity, heteroskedasticity along with serial correlation can be significantly addressed by using a panel GMM technique [73, 74].
This part of the survey outlines the findings of the study which includes the descriptive statistics, panel unit root test and the GMM results. The following section discusses the descriptive statistics.
Table 2 illustrates a detailed view of the statistical characteristics of the variables used in this study. It is apparent that the mean of the considered variables is located between their own minimum and maximum values. As well, most of these factors are negatively skewed (63.6%) but only 36.4% demonstrates positive skewness. In this case, transport tax, energy consumption, green research and development, government expenditure, eco-innovation index, production, and environmental sustainability are negatively skewed. On the other hand, environmental tax, energy tax, greenhouse gas emissions, and economic growth are positively skewed. The positive values generated through kurtosis imply that all the variables have leptokurtic attributes.
Variable | Min. | Max. | Mean | Std. Dev. | Skewness | Kurtosis | Observation |
---|---|---|---|---|---|---|---|
LogETT | 0.196 | 0.617 | 0.405 | 0.102 | 0.114 | 2.254 | 224 |
LogENT | 0.033 | 0.521 | 0.286 | 0.103 | 0.246 | 2.575 | 224 |
LogTRT | −1.301 | 0.190 | −0.393 | 0.353 | −0.670 | 2.867 | 224 |
LogGHG | 0.699 | 1.423 | 0.959 | 0.143 | 0.637 | 3.319 | 224 |
LogEC | 2.589 | 5.315 | 4.206 | 0.620 | −0.323 | 2.902 | 224 |
LogGRD | −0.420 | 0.572 | 0.128 | 0.256 | −0.157 | 2.009 | 224 |
LogGDP | 3.820 | 7.584 | 5.517 | 0.868 | 0.074 | 2.325 | 224 |
LogGE | 1.420 | 1.814 | 1.654 | 0.066 | −0.389 | 3.2358 | 224 |
LogECO | 1.301 | 2.173 | 1.915 | 0.1728 | −0.709 | 3.046 | 224 |
LogPDN | 1.203 | 2.124 | 1.926 | 1.926 | −4.948 | 25.678 | 224 |
LogANS | 0 | 11.7289 | 8.969 | 3.535 | −2.040 | 5.464 | 224 |
Statistical summary of variables.
Source: Authors compilation.
Table 3 shows that when the Augmented Dickey-Fuller test (ADF) tests; Levin, Lin, and Chu (LLC) and the Im-Pesaran-Shin (IPS) were employed the time series is not affected by the presence of unit roots. As such, through deploying a null hypothesis that a specific time series is non-stationary all the variables demonstrates that they are stationary at the first-order differenced series for all ADF, LLC and IPS tests (at 1% significant level) employing the first-generation panel unit-roots. Although variables such as transport tax, production, and environmental sustainability were not confirmed using the IPS test the other two remaining tests argument in favor of the general findings of the paper.
At Level | At 1st Difference | |||||
---|---|---|---|---|---|---|
Variable | ADF statistic | LLC Statistic | IPS Statistic | ADF statistic | LLC Statistic | IPS Statistic |
LogETT | 1.963 (0.025)** | −7.686 (0.000)*** | 0.886 (0.8122) | 9.339 (0.000)*** | −13.951 (0.000)*** | −3.378 (0.000)*** |
LogENT | 2.467 (0.007)*** | −8.548 (0.000)*** | 1.483 (0.931) | 9.068 (0.000)*** | −10.568 (0.000)*** | −3.431 (0.000)*** |
LogTRT | 2.861 (0.002)*** | −8.234 (0.000)*** | — | 19.540 (0.000)*** | −23.409 (0.000)*** | — |
LogGHG | 8.940 (0.000)*** | −8.525 (0.000)*** | −1.817 (0.035)** | 5.490 (0.000)*** | −9.777 (0.000)*** | −2.454 (0.007)*** |
LogEC | 7.125 (0.000)*** | −11.099 (0.000)*** | −1.622 (0.052)* | 9.722 (0.000)*** | −19.600 (0.000)*** | −2.532 (0.006)*** |
LogGRD | 4.486 (0.000)*** | −6.545 (0.000)*** | −0.060 (0.476) | 19.727 (0.000)*** | −10.522 (0.000)*** | −3.990 (0.000)*** |
LogGDP | −1.634 (0.949) | 9.158 (1.000) | 10.826 (1.000) | 2.395 (0.008)*** | −16.523 (0.000)*** | −0.606 (0.272) |
LogGE | 7.899 (0.000)*** | −3.947 (0.000)*** | 1.734 (0.9586) | 10.764 (0.000)*** | −15.177 (0.000)*** | −3.398 (0.000)*** |
LogECO | 3.003 (0.001)*** | −3.321 (0.004)*** | −1.948 (0.026)** | 23.576 (0.000)*** | −13.886 (0.001)*** | −4.826 (0.000)*** |
LogPDN | −2.484 (0.994) | 5.508 (1.0000) | — | 10.630 (0.000)*** | −9.284 (0.000)*** | — |
LogANS | 9.972 (0.0000)*** | −2.517 (0.006)*** | — | 18.614 (0.000)*** | −20.013 (0.000)*** | — |
Showing the panel unit root test results.
Notes: ***;**;* mean significant at 1%, 5%, 10% level of significance respectively. Numbers in brackets are p-values.
Using logarithm of greenhouse gas emissions as the dependent variable and total environmental tax as the main independent variable Table 4 outlines the results of the research about the Pooled Ordinary Least Square (OLS) model, Fixed Effect (FE) and Random Effect (RE) models widely regarded as the static models. The details in Table 4 demonstrates that Hausman test produces a chi-square value of 270.32 which is also significant at 5% (p = 0.000 < 0.05). This shows that we will reject the null hypothesis which illustrates that the RE model is suitable in favor of the alternative hypothesis which explains that the FE model is suitable. The dynamic nature of the FE model is further analysed using the two-step GMM model.
Pooled Model | Random Effect Model | Fixed Effect Model | ||||
---|---|---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | Coefficient | Standard Error | |
LogETT | 0.018 (0.851) | 0.093 | −0.032 (0.599) | 0.062 | −0.094 (0.078)* | 0.053 |
LogEC | 0.028 (0.241) | 0.024 | 0.417 (0.000)*** | 0.060 | 0.563 (0.000)*** | 0.086 |
LogGRD | 0.298 (0.000)*** | 0.056 | −0.028 0.442 | 0.037 | −0.076 (0.017)** | 0.032 |
LogGDP | −0.065 (0.000)*** | 0.016 | −0.336 (0.000)*** | 0.041 | −0.707 (0.000)*** | 0.054 |
LogGE | −0.367 (0.041)** | 0.178 | −0.046 0.489 | 0.066 | −0.224 (0.000)*** | 0.060 |
LogECO | −0.031 (0.667) | 0.074 | 0.026 0.399 | 0.030 | −0.025 (0.339) | 0.026 |
LogPDN | −0.062 (0.011)** | 0.024 | 0.194 (0.001)*** | 0.060 | 0.678 (0.000)*** | 0.078 |
Constant | 1.942 (0.0000)*** | 0.292 | 0.729 (0.005)*** | 0.260 | 1.654 (0.000)*** | 0.449 |
R2 | 0.239 | 0.012 | 0.003 | |||
Wald (χ2) | 86.07 | |||||
F statistic | 9.70 | 34.14 | ||||
Breusch-Pagan test (χ2) | 654.5 (0.000)*** | |||||
Hausman test (χ2) | 270.3 (0.000)*** | |||||
No. of observations | 224 | 224 | 224 |
Estimates of static panel data for total environmental tax: Case of Greenhouse Emissions.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
The results found in Table 4 are also generally congruent with outcomes found in Table 5. For example, the Hausman test generates a chi-square estimate of 15.24 which is also significant at 5% (p = 0.0330 < 0.05) supports the FE model which permits the study to use the two-step GMM analysis procedure.
Pooled Model | Random Effect Model | Fixed Effect Model | ||||
---|---|---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | Coefficient | Standard Error | |
LogETT | 3.719 (0.076)* | 2.088 (0.230) | 3.199 | 2.666 | 1.963 (0.516) | 3.017 |
LogEC | 1.889 (0.000)*** | 0.531 (0.385) | 1.230 | 1.414 | −11.462 (0.021)** | 4.917 |
LogGRD | 4.266 (0.001)*** | 1.240 (0.881) | −0.227 | 1.517 | −3.132 (0.087)* | 1.818 |
LogGDP | 0.893 (0.013)** | 0.357 (0.127) | 1.478 | 0.968 | −1.589 (0.606) | 3.077 |
LogGE | −13.285 (0.001)*** | 3.977 (0.018)** | −6.706 | 2.824 | −6.407 (0.061)*** | 3.401 |
LogECO | 0.200 (0.899) | 1.653 (0.072)* | 2.400 | 1.330 | 0.981 (0.507) | 1.477 |
LogPDN | −0.582 (0.278) | 0.535 (0.948) | 0.091 | 1.398 | 10.747 (0.016)** | 4.403 |
Constant | 16.742 (0.011)** | 6.513 (0.942) | 0.710 | 7.025 | 53.571 (0.038)** | 25.632 |
R2 | 0.382 | 0.324 | 0.301 | |||
Wald (χ2) | 26.43 | |||||
F statistic | 19.07 | 3.69 | ||||
Breusch-Pagan test (χ2) | 489.70 (0.000)*** | |||||
Hausman test (χ2) | 15.24 (0.033)** | |||||
No. of observations | 224 | 224 | 224 |
Estimates of static panel data for total environmental tax: Case of Environmental Sustainability.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
The findings generated in Tables 4 and 5 are also generally confirmed with results in Table 6 (although in this case energy tax and transport tax are the main independent variables). For instance, the Hausman test shows a chi-square estimate of 195.27 which is also significant at 5% (p = 0.000 < 0.05) favoring the FE model. As such, the two-step GMM analytical process will be applied.
Pooled Model | Random Effect Model | Fixed Effect Model | ||||
---|---|---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | Coefficient | Standard Error | |
LogENT | 0.109 (0.215) | 0.087 | −0.056 (0.293) | 0.054 | −0.067 (0.148) | 0.046 |
LogTRT | −0.100 (0.001)*** | 0.029 | 0.032 (0.419) | 0.039 | −0.015 (0.685) | 0.036 |
LogEC | 0.015 (0.498) | 0.023 | 0.411 (0.000)*** | 0.060 | 0.564 (0.000)*** | 0.087 |
LogGRD | 0.245 (0.000)*** | 0.056 | −0.029 (0.433) | 0.037 | −0.075 (0.022)*** | 0.032 |
LogGDP | −0.060 (0.000)*** | 0.016 | −0.334 (0.000)*** | 0.040 | −0.703 (0.000)*** | 0.054 |
LogGE | −0.060 (0.752) | 0.190 | −0.045 (0.501) | 0.066 | −0.226 (0.000)*** | 0.060 |
LogECO | 0.058 (0.447) | 0.076 | 0.022 (0.467) | 0.031 | −0.025 (0.347) | 0.026 |
LogPDN | −0.092 (0.000)*** | 0.025 | 0.191 (0.001)*** | 0.059 | 0.672 (0.000)*** | 0.078 |
Constant | 1.290 (0.000)*** | 0.337 | 0.768 (0.003)*** | 0.262 | 1.618 (0.000)*** | 0.451 |
R2 | 0.284 | 0.010 | 0.003 | |||
Wald (χ2) | 87.09 | |||||
F statistic | 10.68 | 29.53 | ||||
Breusch-Pagan test (χ2) | 659.64 (0.000)*** | |||||
Hausman test (χ2) | 195.27 (0.000)*** | |||||
No. of observations | 224 | 224 |
Estimates of static panel data for total energy tax and transport tax: Case of Greenhouse-gas Emissions.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
In Table 7, the Hausman test generates a chi-square estimate of 18.41 which is also significant at 5% (p = 0.0184 < 0.05) thereby supporting the FE model.
Pooled Model | Random Effect Model | Fixed Effect Model | ||||
---|---|---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | Coefficient | Standard Error | |
LogENT | 4.516 (0.025)** | 1.999 | 0.839 (0.717) | 2.318 | −1.207 (0.639) | 2.571 |
LogTRT | 0.382 (0.564) | 0.662 | 2.106 (0.113) | 1.327 | 5.084 (0.012)** | 2.008 |
LogEC | 1.787 (0.001)*** | 0.522 | 1.182 (0.412) | 1.44 | −12.918 (0.009)*** | 4.896 |
LogGRD | 4.484 (0.001)*** | 1.286 | −0.362 (0.813) | 1.525 | −3.436 (0.059)** | 1.805 |
LogGDP | 0.902 (0.012)** | 0.3572 | 1.397 (0.159) | 0.992 | −0.837 (0.784) | 3.047 |
LogGE | −13.352 (0.002)*** | 4.334 | −6.780 (0.016)** | 2.827 | −6.056 (0.073)* | 3.357 |
LogECO | 0.422 (0.809) | 1.742 | 2.122 (0.116) | 1.352 | 0.578 (0.696) | 1.475 |
LogPDN | −0.737 (0.197) | 0.569 | 0.370 (0.786) | 1.438 | 9.717 (0.027)** | 4.355 |
Constant | 17.462 (0.024)** | 7.699 | 3.327 (0.647) | 7.264 | 60.900 (0.017)** | 25.302 |
R2 | 0.3883 | 0.274 | 0.304 | |||
Wald (χ2) | 27.19 | |||||
F statistic | 17.06 | 4.06 | ||||
Breusch-Pagan test (χ2) | 482.89 (0.000)*** | |||||
Hausman test (χ2) | 18.41 (0.0184)** | |||||
No. of observations | 224 | 224 |
Estimates of static panel data for total energy tax and transport tax: Case of Sustainability.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
Table 8 presents the outcomes acquired by running the two-step GMM analytical method within the short-run context with regards to total environmental tax as the main independent variable. We begin first by evaluating greenhouse gas emissions as the dependent variable. To begin, the lagged factor
LogGHG | LogANS | |||
---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | |
0.218 (0.004)*** | 0.075 | |||
0.235 (0.000)*** | 0.009 | |||
LogETT | 0.222 (0.006)*** | 0.0803589 | 2.877 (0.000)*** | 0.681 |
LogEC | 0.731 (0.000)*** | 0.1221115 | 5.556 (0.000)*** | 1.159 |
LogGRD | 0.362 (0.000)*** | 0.084 | −0.753 (0.053)* | 0.389 |
LogGDP | −0.403 (0.000)*** | 0.083 | −1.324 (0.094)* | 0.790 |
LogGE | −0.815 (0.000)*** | 0.184 | −10.793 (0.000)*** | 0.877 |
LogECO | −0.004 (0.091)* | 0.038 | −1.542 (0.000)*** | 0.109 |
LogPDN | −0.396 (0.000)*** | 0.131 | 2.910 (0.000)*** | 0.681 |
Constant | 1.862 (0.000)*** | 0.377 | 5.028 (0.000)*** | 2.380 |
Wald (χ2) | 88.56 (0.000) | 11340.75 (0.000) | ||
Arellano-Bond test for AR(1) in first differences | z = −0.97 Pr > z = 0.003 | z = −1.15 Pr > z = 0.025 | ||
Arellano-Bond test for AR(2) in first differences | z = −0.52 Pr > z = 0.600 | z = 0.29 Pr > z = 0.769 | ||
Hansen test of overidentifying. Restrictions | Chi-square = 30.79 Prob > chi2 = 0.683 | Chi-square = 21.06 Prob > chi2 = 1.000 | ||
Sargan test of overidentifying. Restrictions | Chi-square = 16.49 Prob > chi2 = 0.284 | Chi-square = 106.77 Prob > chi2 = 0.2 | ||
No. of observations | 196 | 196 |
Findings of GMM short-run results as the dynamic regression approaches: In case of total environmental tax.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
Secondly, the total environmental tax shows a positive and highly significant association with greenhouse gas emissions. In this context, a single rise in total environmental tax leads to a 0.22 increase in greenhouse gas emissions. However, this study finding conflicts with [76] who noticed significantly small and even negative carbon leakage after unilateral environmental tax reforms were integrated in Europe between the studied periods 1995 to 2005. Third, a 1% increase in energy consumption also results in a significant 0.73% rise in emissions thereby agreeing with [77] analysis on 116 countries over the period 1990 to 2014. Fourth, a percentage rise in green research and development in the short-run is also leading to a 0.36% increase in greenhouse gas emissions. However, this finding contradicts Fernández, López and Blanco’s [78] survey on 15 European Union countries, the United States and China between 1990 and 2013 and spotlights that green research and development adds positively to a decline in emissions in developed countries.
However, other remaining variables indicates negative and significant links to greenhouse gas emissions. For example, a percentage increase in economic growth leads to a 0.40% significant decrease in emissions. Nonetheless, this study outcomes disagrees with Salahuddin et al. [79] research on Kuwait for the period 1980–2013 by applying the autoregressive distributed lag (ARDL) bounds testing approach and adds that economic growth motivates emissions in both short-run and long-run. In another context, a 1% rise in government expenditure significantly lowers greenhouse gas emissions by 0.815%. However, [80] studied the Venezuelan context over the period from 1971 to 2013 and contributes that government expenditure has a positive effect on environmental degradation-emissions. In addition, the eco-innovation rating is also responsible for decreasing emissions significantly by 0.0039% in these studied EU countries in the short-run. Using the GMM technique on China’s 30 provinces during 2000–2013, [81] also contributes that environmental innovation resources along with green knowledge innovation are essential components for emissions reduction. The results of this study also demonstrates that a 1% increase in production will also likely reduce emissions by a significant 0.40%. However, Ganda [82] survey on the BRICS (Brazil, Russia, India, China, and South Africa) using panel data from 1992 to 2014 express that production practice, through industrial initiative adds to emissions.
The second part of this section will examine the short-run results by examining environmental sustainability as the dependent variable. In this case, a 1% rise in past adjusted net savings, excluding particulate emission damage, which is the proxy for environmental sustainability (
Fourth, when short-run green research and development increased by 1% then environmental sustainability will significantly decrease by 0.75%. This finding conflicts with [85] study on US electric generators who adds that short-run decisions to integrate green technologies also provide significant emission reduction opportunities even before new technologies have been fully integrated on a broadened scale. Furthermore, income is also found to be lowering environmental sustainability in the short-run for the studied EU countries. In this context, a percentage increase in economic development significantly decreases sustainability by 1.32%. Nevertheless, Ganda [86] study on OECD economies also highlights that disagrees with these outcomes as income is ascertained to increase environmental sustainability by 17.8% in the short-run. Another variable, government expenditure is also ascertained to significantly lower environmental sustainability by 10.79% when it increases by a single percent. Then, a 1% rise in eco-innovation is also accountable to a significant decrease estimated at 1.54% of environmental sustainability. However, a 1% increase in production will significantly heighten environmental sustainability by 2.91%. As such, Severo, de Guimarães, Dorion and Nodari [87] having explored the Brazilian Metal-Mechanic industry posits that cleaner production positively influences environmental sustainability.
Table 9 also depicts the results obtained by implementing a two-step GMM analysis process. The presentation disaggregates total environmental tax by identifying energy tax and transport tax as the main independent factors in this analysis. As previously done in the previous section, we commence by initially assessing greenhouse gas emissions as the dependent variable. In this context, it is evident that the lagged variable factor
LogGHG | LogANS | |||
---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | |
0.286 (0.000)*** | 0.062 | |||
0.163 (0.000)* ** | 0.019 | |||
LogENT | 0.100 (0.066)* | 0.055 | −4.369 (0.011)** | 1.719 |
LogTRT | −0.130 (0.001)*** | 0.038 | 5.740 (0.000)*** | 1.397 |
LogEC | 0.466 (0.000)*** | 0.059 | 0.539 (0.644) | 1.166 |
LogGRD | −0.149 (0.001)*** | 0.043 | 1.750 (0.099)* | 1.062 |
LogGDP | −0.280 (0.000)*** | 0.050 | 1.304 (0.056)* | 0.684 |
LogGE | 0.176 (0.008)*** | 0.066 | −12.552 (0.000)*** | 3.015 |
LogECO | 0.113 (0.000)*** | 0.019 | 0.341 (0.008)*** | 0.128 |
LogPDN | 0.155 (0.012)*** | 0.062 | −5.987 (0.001)*** | 1.848 |
Constant | −0.615 (0.010)*** | 0.244 | 33.271 (0.000)*** | 8.032 |
Wald (χ2) | 411.85 (0.000) | 3202.15 (0.000) | ||
Arellano-Bond test for AR(1) in first differences | z = −2.09 Pr > z = 0.036 | z = −1.10 Pr > z = 0.022 | ||
Arellano-Bond test for AR(2) in first differences | z = 0.32 Pr > z = 0.752 | z = 0.60 Pr > z = 0.547 | ||
Hansen test of overidentifying. Restrictions | Chi-square = 19.82 Prob > chi2 = 0.898 | Chi-square = 20.10 Prob > chi2 = 0.890 | ||
Sargan test of overidentifying. Restrictions | Chi-square = 43.9 Prob > chi2 = 0.38 | Chi-square = 38.51 Prob > chi2 = 0.111 | ||
No. of observations | 196 |
Findings of GMM short-run results as the dynamic regression approaches: In case of energy tax and transport tax.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
In addition, energy tax demonstrates a positive and significant connection with greenhouse gas emissions. As such, a 1% rise in energy tax is sufficient to increase emissions by 0.10%. However, Solaymani [88] study on Malaysia found out that energy tax can reduce emissions although carbon tax was found to be a more effective tax instrument for emissions reduction programs. Furthermore, the paper outcomes show that transport tax shows a negative and highly significant association with greenhouse gas emissions. In this context, a single rise in transport tax leads to a 0.13% decrease in greenhouse gas emissions. González and Hosoda [89] also conducted a study in Japan between 2004 and 2013 using the Bayesian structural time series model and they highlight that the integration of fuel tax has unequivocally minimised aircraft emissions.
As well, the research illustrates that a 1% increase in energy consumption also results in a significant 0.47% rise in emissions thereby agreeing with findings presented in Table 8. Conversely, the results in Table 9 further indicates that a percentage rise in green research and development generates a 0.15% decrease in greenhouse gas emissions thereby supporting [79] study on 15 European Union countries. Furthermore, economic growth has a negative and significant association with emissions. As such, a 1% increase in income stimulates a 0.28% reduction in emissions. However, Magazzino [90] study on Italy over the period 1970 to 2006 demonstrates a bidirectional causality link between economic growth and emissions.
The other outstanding variables indicate positive and significant links to greenhouse gas emissions. For instance, a percentage increase in government expenditure leads to a 0.176% significant rise in emissions. Contradicting with these findings [91] study on a panelised data of 94 countries between 1970 and 2008 illustrates that government expenditure exercise a significant direct influence in reducing the amount of emissions. As well, the eco-innovation rating is also responsible for rising emissions significantly by 0.11%. However, Costantini et al. [92] exploration of European industries confirm that both indirect and direct impacts of eco-innovations assist lessening environmental degradation although the strength varied throughout the industry value chain. The outcomes of the research also confirm that as production in the short-run increases by 1% emissions also heightens by 0.15%. Likewise, Phalan et al.’s [93] survey on the Brazilian beef industry expresses that production is highly unlikely to help lower emissions, and is possibly likely to exacerbate deforestation.
The remaining segment of this section will evaluate the GMM findings through scrutinising environmental sustainability as the dependent variable. Thus, from Table 9, if lagged environmental sustainability (
The paper results also demonstrate that a 1% increase in energy consumption significantly rises environmental sustainability by 0.54%. Furthermore, it can be ascertained that if green research and development increased by 1% then environmental sustainability will significantly increase by 1.75%. Moreover, a percentage rise in income motivates a 1.30% rise in environmental sustainability. Hatfield-Dodds et al. [95] study on Australia also contributes that it is quite difficult to decouple economic growth and environmental outcomes and mobilisation of technologies and engagement of environmental incentives are essential for advancement towards sustainable prosperity. The research outcomes also show that a 1% increase in government expenditure is also ascertained to significantly lower environmental sustainability by 12.6%. In addition, a 1% rise in eco-innovation is also accountable to a significant increase estimated at 0.34% of environmental sustainability. Nevertheless, a 1% increase in production will significantly lessen environmental sustainability by 5.99%.
Table 8 which was presented earlier in this section outline the regression findings in the short-run scenario in case where environmental tax was identified as the main independent variable. Table 10 above extends the discussion by examining the association involving environmental tax as the primary independent factor to both emissions and environmental sustainability but on a long-run setting. In detail, it is evident that environmental tax form a positive relationship with both greenhouse gas emissions and environmental sustainability (although it is significant in this context). Likewise, energy consumption shows a significantly positive link with both emissions and environmental sustainability. Green research and development produce a positive link with emissions but its connection with environmental sustainability is significantly negative. The results further prove that economic growth, government expenditure, and eco-innovation show significant negative relationships to both emissions and environmental sustainability in the long-term. Lastly, production generates a significantly negative link with emissions but its association with environmental sustainability is significantly positive.
LogGHG | LogANS | |||
---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | |
LogETT | 0.004 (0.970) | 0.102 | 2.642 (0.000)*** | 0.674 |
LogEC | 0.513 (0.000)*** | 0.145 | 5.320 (0.000)*** | 1.157 |
LogGRD | 0.144 (0.241) | 0.123 | −0.988 (0.012)** | 0.394 |
LogGDP | −0.622 (0.000)*** | 0.110 | −1.560 (0.049)** | 0.792 |
LogGE | −1.034 (0.000)*** | 0.209 | −11.028 (0.000)*** | 0.881 |
LogECO | −0.222 (0.025)** | 0.099 | −1.778 (0.000)*** | 0.108 |
LogPDN | −0.614 (0.000)*** | 0.164 | 2.675 (0.000)*** | 0.685 |
Findings of GMM long-run results as the dynamic regression approach: in case of total environmental tax.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
Table 9 of this part of the study produced short-run associations by disintegrating total environmental tax through isolating energy tax and transport tax as the main independent variables. Table 11 expand this analysis by identifying the association of these explanatory variables against both emissions and environmental sustainability within a long-run basis. In brief, energy tax, government expenditure and production produces a significantly negative connection with both emissions and environmental sustainability. Other findings confirm that transport tax, green research and development, economic growth and eco-innovation demonstrate negative and positive associations with both emissions and environmental sustainability. The relationship involving energy use to both emissions and environmental sustainability is positive in both cases.
LogGHG | LogANS | |||
---|---|---|---|---|
Coefficient | Standard Error | Coefficient | Standard Error | |
LogENT | −0.185 (0.021)** | 0.080 | −4.532 (0.008)*** | 1.713 |
LogTRT | −0.416 (0.000)*** | 0.074 | 5.577 (0.000)*** | 1.400 |
LogEC | 0.180 (0.058)* | 0.095 | 0.376 (0.745) | 1.157 |
LogGRD | −0.435 (0.000)*** | 0.078 | 1.587 (0.136)* | 1.064 |
LogGDP | −0.566 (0.000)*** | 0.058 | 1.142 (0.099)* | 0.692 |
LogGE | −0.110 (0.292)* | 0.104 | −12.714 (0.000)*** | 3.005 |
LogECO | −0.173 (0.005)*** | 0.061 | 0.178 (0.156) | 0.126 |
LogPDN | −0.131 (0.193)* | 0.101 | −6.150 (0.000)*** | 1.842 |
Findings of GMM long-run results as the dynamic regression approach: In case of energy tax and transport tax.
Notes: ***; **; * mean significant at 1%, 5% and 10% significance level, respectively. Numbers in brackets are p-values.
This section presents a detailed analysis of the study also highlights the implications of the research.
Table 12 provide useful insights about the context involving the association between total environmental tax and both greenhouse gas emissions along with environmental sustainability. Total environmental tax appears to be increasing emissions both on the short-and long-run scenario although it is found to be also simultaneously increasing environmental sustainability. This implies that while overall natural environmental effect as a result of imposing environmental tax improves there is also a need for EU economies to introduce specific green taxes which directly focus on particular environmental indicators so that emission reduction is effectually achieved. Moreover, there is a need to transform or remove particular environmental taxes which are not effectively achieving zero-emission targets. As well, taxes can be modified by adding regulatory instruments so that they are aligned with natural environmental objectives and goals. It is also apparent that energy consumption has been increasing the level of emissions and environmental sustainability. In this case, EU economics should continue expanding the integration of renewable energy and oppose further consumption of fossil fuels. There is evidence of renewable energy use in EU economies [13, 60] in pursuit of lower emissions which can possibly explain the improved environmental sustainability context. However, there is also a need to upgrade energy systems of green energy technologies so that they do not add to heightening emissions.
Environmental tax | Energy tax and Transport tax | |||||||
---|---|---|---|---|---|---|---|---|
LogGHG | LogANS | LogGHG | LogANS | |||||
Short-Run | Long-Run | Short-Run | Long-Run | Short-Run | Long-Run | Short-Run | Long-Run | |
LogETT | + | + | + | + | ||||
LogEC | + | + | + | + | + | + | + | + |
LogGRD | + | + | — | — | — | — | + | + |
LogGDP | — | — | — | — | — | — | + | + |
LogGE | — | — | — | — | + | — | — | — |
LogECO | — | — | — | — | + | — | + | + |
LogPDN | — | — | + | — | + | — | — | — |
LogENT | + | — | — | — | ||||
LogTRT | — | — | + | + |
Summary of GMM short-and long-run results.
Green research and development is found to be highly effective when environmental taxes are emphasising of particular environmental measures instead of adopting a holistic environmental tax policy. For instance, when environmental tax was disaggregated the tax tools used managed to motivate green research and development to lower emissions and simultaneously raise environmental sustainability. Economic growth is quite effective in lowering the level of greenhouse gases whether environmental tax is aggregated and/or disaggregated. Of note is that economic growth effectively improve environmental sustainability in the short and long-run when EU economies use specific environmental taxes when adopting a comprehensive environmental tax instrument.
On the one hand, government expenditure is very efficient in lowering emissions in the short and long-run but is also not able to promote environmental sustainability during these periods in case where aggregate environmental tax is employed. On the other hand, the situation is also predominantly noticeable when environmental tax has been disaggregated (energy tax and transport tax) except that it increases emissions in the short-run. This indication shows that government expenditure in EU economies needs to focus on an inclusive approach which supports all issues related to sustainability instead of putting much emphasis on emissions alone. In this case, government expenditure should also include environmental standards and regulations and measures which heighten environmental sustainability.
It is also observable that eco-innovation is capable of lowering emissions whether environmental tax is aggregated or disintegrated. However, in the case where environmental tax is not aggregated, that is, specific eco-innovation improves environmental sustainability but it worsens environmental sustainability in case of total environmental tax. This shows the importance of introducing specific eco-innovation regulatory standards that fits different parts of the production and ultimate distribution of manufactured goods and services.
Although production in EU economies manage to lower emissions in cases where environmental is aggregated and/or not is has not been able to improve environmental sustainability. In this case, while production has managed emissions reduction targets the impacts of this procedure on other natural environmental components require to be upgraded.
Lastly, it is apparent that energy tax has been lessening environmental sustainability but transport tax has been effective in creating required environmental sustainability scenarios. Both these taxes are also effective in the long-run in lowering emissions although energy tax is found to ineffective in lowering emissions in the short-run. It is evident that the transport tax appears to be a more effective instrument to meet environmental goals when compared to energy tax in EU economies. In this case, there is a need to revise energy policy and regulatory instruments that deal with energy in these countries so that such tools are harmonising with sustainability goals and objectives.
The first findings presented regression results when the aggregate environmental tax was employed. These outcomes show that total environmental tax, energy consumption, green research and development significantly heightened emissions in the short-run scenario. The results further demonstrate that in the short-term economic growth, government expenditure, eco-innovation rating and production scores significantly lowered emissions. The results also confirm that total environmental tax, energy consumption and production significantly increase environmental sustainability in the short-run. Conversely, green research and development, economic growth, government expenditure, and eco-innovation significantly lower environmental sustainability in the short-run. The long-run results demonstrate that environmental tax and energy consumption develop a positive relationship with both greenhouse gas emissions and environmental sustainability respectively. In addition, green research and development generates a positive connection with emissions although its link with environmental sustainability is significantly negative. Economic growth, government expenditure, and eco-innovation illustrates a significant negative relationships to both emissions and environmental sustainability in the long-term. In the long-run, production produces a significantly negative association with emissions but a significantly positive relationship with environmental sustainability.
The second part of the results section outlined regression when disaggregated environmental tax (energy tax and transport tax) was deployed. Thus, in the short-term, energy tax, energy consumption, government expenditure, eco-innovation rating, and production scores spur a significant rise in emissions. However, transport tax, green research and development, and income influence lessens emissions in the short-run. Furthermore, energy tax and production significantly reduce environmental sustainability in the short-term. Nonetheless, transport tax, energy consumption, green research and development, income and eco-innovation significantly increase environmental sustainability in the short-run. The long-run findings proves that energy tax, government expenditure and production produces a significantly negative relationship with both emissions and environmental sustainability. As well, transport tax, green research and development, economic growth along with eco-innovation produce negative and positive associations with both emissions and environmental sustainability. Lastly, energy use shows a significantly positive link to both emissions and environmental sustainability.
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\n\nA Conflict of Interest is a situation in which a person's professional judgment may be influenced by a range of factors, including financial gain, material interest, or some other personal or professional interest. For IntechOpen as a publisher, it is essential that all possible Conflicts of Interest are avoided. Each contributor, whether an Author, Editor, or Reviewer, who suspects they may have a Conflict of Interest, is obliged to declare that concern in order to make the publisher and the readership aware of any potential influence on the work being undertaken.
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\n\nAll Authors, Academic Editors, and Reviewers are required to declare all possible financial and material Conflicts of Interest in the last five years, although it is advisable to declare less recent Conflicts of Interest as well.
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\n\nAuthors should declare if they were or they still are Academic Editors of the publications in which they wish to publish their work.
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\n\nPolicy last updated: 2016-06-09
\n"}]},successStories:{items:[]},authorsAndEditors:{filterParams:{sort:"featured,name"},profiles:[{id:"105746",title:"Dr.",name:"A.W.M.M.",middleName:null,surname:"Koopman-van Gemert",slug:"a.w.m.m.-koopman-van-gemert",fullName:"A.W.M.M. Koopman-van Gemert",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/105746/images/5803_n.jpg",biography:"Dr. Anna Wilhelmina Margaretha Maria Koopman-van Gemert MD, PhD, became anaesthesiologist-intensivist from the Radboud University Nijmegen (the Netherlands) in 1987. She worked for a couple of years also as a blood bank director in Nijmegen and introduced in the Netherlands the Cell Saver and blood transfusion alternatives. She performed research in perioperative autotransfusion and obtained the degree of PhD in 1993 publishing Peri-operative autotransfusion by means of a blood cell separator.\nBlood transfusion had her special interest being the president of the Haemovigilance Chamber TRIP and performing several tasks in local and national blood bank and anticoagulant-blood transfusion guidelines committees. Currently, she is working as an associate professor and up till recently was the dean at the Albert Schweitzer Hospital Dordrecht. She performed (inter)national tasks as vice-president of the Concilium Anaesthesia and related committees. \nShe performed research in several fields, with over 100 publications in (inter)national journals and numerous papers on scientific conferences. \nShe received several awards and is a member of Honour of the Dutch Society of Anaesthesia.",institutionString:null,institution:{name:"Albert Schweitzer Hospital",country:{name:"Gabon"}}},{id:"83089",title:"Prof.",name:"Aaron",middleName:null,surname:"Ojule",slug:"aaron-ojule",fullName:"Aaron Ojule",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Port Harcourt",country:{name:"Nigeria"}}},{id:"295748",title:"Mr.",name:"Abayomi",middleName:null,surname:"Modupe",slug:"abayomi-modupe",fullName:"Abayomi Modupe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/no_image.jpg",biography:null,institutionString:null,institution:{name:"Landmark University",country:{name:"Nigeria"}}},{id:"94191",title:"Prof.",name:"Abbas",middleName:null,surname:"Moustafa",slug:"abbas-moustafa",fullName:"Abbas Moustafa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94191/images/96_n.jpg",biography:"Prof. Moustafa got his doctoral degree in earthquake engineering and structural safety from Indian Institute of Science in 2002. He is currently an associate professor at Department of Civil Engineering, Minia University, Egypt and the chairman of Department of Civil Engineering, High Institute of Engineering and Technology, Giza, Egypt. He is also a consultant engineer and head of structural group at Hamza Associates, Giza, Egypt. Dr. Moustafa was a senior research associate at Vanderbilt University and a JSPS fellow at Kyoto and Nagasaki Universities. He has more than 40 research papers published in international journals and conferences. He acts as an editorial board member and a reviewer for several regional and international journals. His research interest includes earthquake engineering, seismic design, nonlinear dynamics, random vibration, structural reliability, structural health monitoring and uncertainty modeling.",institutionString:null,institution:{name:"Minia University",country:{name:"Egypt"}}},{id:"84562",title:"Dr.",name:"Abbyssinia",middleName:null,surname:"Mushunje",slug:"abbyssinia-mushunje",fullName:"Abbyssinia Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Fort Hare",country:{name:"South Africa"}}},{id:"202206",title:"Associate Prof.",name:"Abd Elmoniem",middleName:"Ahmed",surname:"Elzain",slug:"abd-elmoniem-elzain",fullName:"Abd Elmoniem Elzain",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Kassala University",country:{name:"Sudan"}}},{id:"98127",title:"Dr.",name:"Abdallah",middleName:null,surname:"Handoura",slug:"abdallah-handoura",fullName:"Abdallah Handoura",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"École Supérieure des Télécommunications",country:{name:"Morocco"}}},{id:"91404",title:"Prof.",name:"Abdecharif",middleName:null,surname:"Boumaza",slug:"abdecharif-boumaza",fullName:"Abdecharif Boumaza",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Abbès Laghrour University of Khenchela",country:{name:"Algeria"}}},{id:"105795",title:"Prof.",name:"Abdel Ghani",middleName:null,surname:"Aissaoui",slug:"abdel-ghani-aissaoui",fullName:"Abdel Ghani Aissaoui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/105795/images/system/105795.jpeg",biography:"Abdel Ghani AISSAOUI is a Full Professor of electrical engineering at University of Bechar (ALGERIA). He was born in 1969 in Naama, Algeria. He received his BS degree in 1993, the MS degree in 1997, the PhD degree in 2007 from the Electrical Engineering Institute of Djilali Liabes University of Sidi Bel Abbes (ALGERIA). He is an active member of IRECOM (Interaction Réseaux Electriques - COnvertisseurs Machines) Laboratory and IEEE senior member. He is an editor member for many international journals (IJET, RSE, MER, IJECE, etc.), he serves as a reviewer in international journals (IJAC, ECPS, COMPEL, etc.). He serves as member in technical committee (TPC) and reviewer in international conferences (CHUSER 2011, SHUSER 2012, PECON 2012, SAI 2013, SCSE2013, SDM2014, SEB2014, PEMC2014, PEAM2014, SEB (2014, 2015), ICRERA (2015, 2016, 2017, 2018,-2019), etc.). His current research interest includes power electronics, control of electrical machines, artificial intelligence and Renewable energies.",institutionString:"University of Béchar",institution:{name:"University of Béchar",country:{name:"Algeria"}}},{id:"99749",title:"Dr.",name:"Abdel Hafid",middleName:null,surname:"Essadki",slug:"abdel-hafid-essadki",fullName:"Abdel Hafid Essadki",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"École Nationale Supérieure de Technologie",country:{name:"Algeria"}}},{id:"101208",title:"Prof.",name:"Abdel Karim",middleName:"Mohamad",surname:"El Hemaly",slug:"abdel-karim-el-hemaly",fullName:"Abdel Karim El Hemaly",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/101208/images/733_n.jpg",biography:"OBGYN.net Editorial Advisor Urogynecology.\nAbdel Karim M. A. El-Hemaly, MRCOG, FRCS � Egypt.\n \nAbdel Karim M. A. El-Hemaly\nProfessor OB/GYN & Urogynecology\nFaculty of medicine, Al-Azhar University \nPersonal Information: \nMarried with two children\nWife: Professor Laila A. Moussa MD.\nSons: Mohamad A. M. El-Hemaly Jr. MD. Died March 25-2007\nMostafa A. M. El-Hemaly, Computer Scientist working at Microsoft Seatle, USA. \nQualifications: \n1.\tM.B.-Bch Cairo Univ. June 1963. \n2.\tDiploma Ob./Gyn. Cairo Univ. April 1966. \n3.\tDiploma Surgery Cairo Univ. Oct. 1966. \n4.\tMRCOG London Feb. 1975. \n5.\tF.R.C.S. Glasgow June 1976. \n6.\tPopulation Study Johns Hopkins 1981. \n7.\tGyn. Oncology Johns Hopkins 1983. \n8.\tAdvanced Laparoscopic Surgery, with Prof. Paulson, Alexandria, Virginia USA 1993. \nSocieties & Associations: \n1.\t Member of the Royal College of Ob./Gyn. London. \n2.\tFellow of the Royal College of Surgeons Glasgow UK. \n3.\tMember of the advisory board on urogyn. FIGO. \n4.\tMember of the New York Academy of Sciences. \n5.\tMember of the American Association for the Advancement of Science. \n6.\tFeatured in �Who is Who in the World� from the 16th edition to the 20th edition. \n7.\tFeatured in �Who is Who in Science and Engineering� in the 7th edition. \n8.\tMember of the Egyptian Fertility & Sterility Society. \n9.\tMember of the Egyptian Society of Ob./Gyn. \n10.\tMember of the Egyptian Society of Urogyn. \n\nScientific Publications & Communications:\n1- Abdel Karim M. El Hemaly*, Ibrahim M. Kandil, Asim Kurjak, Ahmad G. Serour, Laila A. S. Mousa, Amr M. Zaied, Khalid Z. El Sheikha. \nImaging the Internal Urethral Sphincter and the Vagina in Normal Women and Women Suffering from Stress Urinary Incontinence and Vaginal Prolapse. Gynaecologia Et Perinatologia, Vol18, No 4; 169-286 October-December 2009.\n2- Abdel Karim M. El Hemaly*, Laila A. S. Mousa Ibrahim M. Kandil, Fatma S. El Sokkary, Ahmad G. Serour, Hossam Hussein.\nFecal Incontinence, A Novel Concept: The Role of the internal Anal sphincter (IAS) in defecation and fecal incontinence. Gynaecologia Et Perinatologia, Vol19, No 2; 79-85 April -June 2010.\n3- Abdel Karim M. El Hemaly*, Laila A. S. Mousa Ibrahim M. Kandil, Fatma S. El Sokkary, Ahmad G. Serour, Hossam Hussein.\nSurgical Treatment of Stress Urinary Incontinence, Fecal Incontinence and Vaginal Prolapse By A Novel Operation \n"Urethro-Ano-Vaginoplasty"\n Gynaecologia Et Perinatologia, Vol19, No 3; 129-188 July-September 2010.\n4- Abdel Karim M. El Hemaly*, Ibrahim M. Kandil, Laila A. S. Mousa and Mohamad A.K.M.El Hemaly.\nUrethro-vaginoplasty, an innovated operation for the treatment of: Stress Urinary Incontinence (SUI), Detursor Overactivity (DO), Mixed Urinary Incontinence and Anterior Vaginal Wall Descent. \nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/ urethro-vaginoplasty_01\n\n5- Abdel Karim M. El Hemaly, Ibrahim M Kandil, Mohamed M. Radwan.\n Urethro-raphy a new technique for surgical management of Stress Urinary Incontinence.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/\nnew-tech-urethro\n\n6- Abdel Karim M. El Hemaly, Ibrahim M Kandil, Mohamad A. Rizk, Nabil Abdel Maksoud H., Mohamad M. Radwan, Khalid Z. El Shieka, Mohamad A. K. M. El Hemaly, and Ahmad T. El Saban.\nUrethro-raphy The New Operation for the treatment of stress urinary incontinence, SUI, detrusor instability, DI, and mixed-type of urinary incontinence; short and long term results. \nhttp://www.obgyn.net/urogyn/urogyn.asp?page=urogyn/articles/\nurethroraphy-09280\n\n7-Abdel Karim M. El Hemaly, Ibrahim M Kandil, and Bahaa E. El Mohamady. Menopause, and Voiding troubles. \nhttp://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly03/el-hemaly03-ss\n\n8-El Hemaly AKMA, Mousa L.A. Micturition and Urinary\tContinence. Int J Gynecol Obstet 1996; 42: 291-2. \n\n9-Abdel Karim M. El Hemaly.\n Urinary incontinence in gynecology, a review article.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/abs-urinary_incotinence_gyn_ehemaly \n\n10-El Hemaly AKMA. Nocturnal Enuresis: Pathogenesis and Treatment. \nInt Urogynecol J Pelvic Floor Dysfunct 1998;9: 129-31.\n \n11-El Hemaly AKMA, Mousa L.A.E. Stress Urinary Incontinence, a New Concept. Eur J Obstet Gynecol Reprod Biol 1996; 68: 129-35. \n\n12- El Hemaly AKMA, Kandil I. M. Stress Urinary Incontinence SUI facts and fiction. Is SUI a puzzle?! http://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly/el-hemaly-ss\n\n13-Abdel Karim El Hemaly, Nabil Abdel Maksoud, Laila A. Mousa, Ibrahim M. Kandil, Asem Anwar, M.A.K El Hemaly and Bahaa E. El Mohamady. \nEvidence based Facts on the Pathogenesis and Management of SUI. http://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly02/el-hemaly02-ss\n\n14- Abdel Karim M. El Hemaly*, Ibrahim M. Kandil, Mohamad A. Rizk and Mohamad A.K.M.El Hemaly.\n Urethro-plasty, a Novel Operation based on a New Concept, for the Treatment of Stress Urinary Incontinence, S.U.I., Detrusor Instability, D.I., and Mixed-type of Urinary Incontinence.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/urethro-plasty_01\n\n15-Ibrahim M. Kandil, Abdel Karim M. El Hemaly, Mohamad M. Radwan: Ultrasonic Assessment of the Internal Urethral Sphincter in Stress Urinary Incontinence. The Internet Journal of Gynecology and Obstetrics. 2003. Volume 2 Number 1. \n\n\n16-Abdel Karim M. El Hemaly. Nocturnal Enureses: A Novel Concept on its pathogenesis and Treatment.\nhttp://www.obgyn.net/urogynecolgy/?page=articles/nocturnal_enuresis\n\n17- Abdel Karim M. El Hemaly. Nocturnal Enureses: An Update on the pathogenesis and Treatment.\nhttp://www.obgyn.net/urogynecology/?page=/ENHLIDH/PUBD/FEATURES/\nPresentations/ Nocturnal_Enuresis/nocturnal_enuresis\n\n18-Maternal Mortality in Egypt, a cry for help and attention. The Second International Conference of the African Society of Organization & Gestosis, 1998, 3rd Annual International Conference of Ob/Gyn Department � Sohag Faculty of Medicine University. Feb. 11-13. Luxor, Egypt. \n19-Postmenopausal Osteprosis. The 2nd annual conference of Health Insurance Organization on Family Planning and its role in primary health care. Zagaziz, Egypt, February 26-27, 1997, Center of Complementary Services for Maternity and childhood care. \n20-Laparoscopic Assisted vaginal hysterectomy. 10th International Annual Congress Modern Trends in Reproductive Techniques 23-24 March 1995. Alexandria, Egypt. \n21-Immunological Studies in Pre-eclamptic Toxaemia. Proceedings of 10th Annual Ain Shams Medical Congress. Cairo, Egypt, March 6-10, 1987. \n22-Socio-demographic factorse affecting acceptability of the long-acting contraceptive injections in a rural Egyptian community. Journal of Biosocial Science 29:305, 1987. \n23-Plasma fibronectin levels hypertension during pregnancy. The Journal of the Egypt. Soc. of Ob./Gyn. 13:1, 17-21, Jan. 1987. \n24-Effect of smoking on pregnancy. Journal of Egypt. Soc. of Ob./Gyn. 12:3, 111-121, Sept 1986. \n25-Socio-demographic aspects of nausea and vomiting in early pregnancy. Journal of the Egypt. Soc. of Ob./Gyn. 12:3, 35-42, Sept. 1986. \n26-Effect of intrapartum oxygen inhalation on maternofetal blood gases and pH. Journal of the Egypt. Soc. of Ob./Gyn. 12:3, 57-64, Sept. 1986. \n27-The effect of severe pre-eclampsia on serum transaminases. The Egypt. J. Med. Sci. 7(2): 479-485, 1986. \n28-A study of placental immunoreceptors in pre-eclampsia. The Egypt. J. Med. Sci. 7(2): 211-216, 1986. \n29-Serum human placental lactogen (hpl) in normal, toxaemic and diabetic pregnant women, during pregnancy and its relation to the outcome of pregnancy. Journal of the Egypt. Soc. of Ob./Gyn. 12:2, 11-23, May 1986. \n30-Pregnancy specific B1 Glycoprotein and free estriol in the serum of normal, toxaemic and diabetic pregnant women during pregnancy and after delivery. Journal of the Egypt. Soc. of Ob./Gyn. 12:1, 63-70, Jan. 1986. Also was accepted and presented at Xith World Congress of Gynecology and Obstetrics, Berlin (West), September 15-20, 1985. \n31-Pregnancy and labor in women over the age of forty years. Accepted and presented at Al-Azhar International Medical Conference, Cairo 28-31 Dec. 1985. \n32-Effect of Copper T intra-uterine device on cervico-vaginal flora. Int. J. Gynaecol. Obstet. 23:2, 153-156, April 1985. \n33-Factors affecting the occurrence of post-Caesarean section febrile morbidity. Population Sciences, 6, 139-149, 1985. \n34-Pre-eclamptic toxaemia and its relation to H.L.A. system. Population Sciences, 6, 131-139, 1985. \n35-The menstrual pattern and occurrence of pregnancy one year after discontinuation of Depo-medroxy progesterone acetate as a postpartum contraceptive. Population Sciences, 6, 105-111, 1985. \n36-The menstrual pattern and side effects of Depo-medroxy progesterone acetate as postpartum contraceptive. Population Sciences, 6, 97-105, 1985. \n37-Actinomyces in the vaginas of women with and without intrauterine contraceptive devices. Population Sciences, 6, 77-85, 1985. \n38-Comparative efficacy of ibuprofen and etamsylate in the treatment of I.U.D. menorrhagia. Population Sciences, 6, 63-77, 1985. \n39-Changes in cervical mucus copper and zinc in women using I.U.D.�s. Population Sciences, 6, 35-41, 1985. \n40-Histochemical study of the endometrium of infertile women. Egypt. J. Histol. 8(1) 63-66, 1985. \n41-Genital flora in pre- and post-menopausal women. Egypt. J. Med. Sci. 4(2), 165-172, 1983. \n42-Evaluation of the vaginal rugae and thickness in 8 different groups. Journal of the Egypt. Soc. of Ob./Gyn. 9:2, 101-114, May 1983. \n43-The effect of menopausal status and conjugated oestrogen therapy on serum cholesterol, triglycerides and electrophoretic lipoprotein patterns. Al-Azhar Medical Journal, 12:2, 113-119, April 1983. \n44-Laparoscopic ventrosuspension: A New Technique. Int. J. Gynaecol. Obstet., 20, 129-31, 1982. \n45-The laparoscope: A useful diagnostic tool in general surgery. Al-Azhar Medical Journal, 11:4, 397-401, Oct. 1982. \n46-The value of the laparoscope in the diagnosis of polycystic ovary. Al-Azhar Medical Journal, 11:2, 153-159, April 1982. \n47-An anaesthetic approach to the management of eclampsia. Ain Shams Medical Journal, accepted for publication 1981. \n48-Laparoscopy on patients with previous lower abdominal surgery. Fertility management edited by E. Osman and M. Wahba 1981. \n49-Heart diseases with pregnancy. Population Sciences, 11, 121-130, 1981. \n50-A study of the biosocial factors affecting perinatal mortality in an Egyptian maternity hospital. Population Sciences, 6, 71-90, 1981. \n51-Pregnancy Wastage. Journal of the Egypt. Soc. of Ob./Gyn. 11:3, 57-67, Sept. 1980. \n52-Analysis of maternal deaths in Egyptian maternity hospitals. Population Sciences, 1, 59-65, 1979. \nArticles published on OBGYN.net: \n1- Abdel Karim M. El Hemaly*, Ibrahim M. Kandil, Laila A. S. Mousa and Mohamad A.K.M.El Hemaly.\nUrethro-vaginoplasty, an innovated operation for the treatment of: Stress Urinary Incontinence (SUI), Detursor Overactivity (DO), Mixed Urinary Incontinence and Anterior Vaginal Wall Descent. \nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/ urethro-vaginoplasty_01\n\n2- Abdel Karim M. El Hemaly, Ibrahim M Kandil, Mohamed M. Radwan.\n Urethro-raphy a new technique for surgical management of Stress Urinary Incontinence.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/\nnew-tech-urethro\n\n3- Abdel Karim M. El Hemaly, Ibrahim M Kandil, Mohamad A. Rizk, Nabil Abdel Maksoud H., Mohamad M. Radwan, Khalid Z. El Shieka, Mohamad A. K. M. El Hemaly, and Ahmad T. El Saban.\nUrethro-raphy The New Operation for the treatment of stress urinary incontinence, SUI, detrusor instability, DI, and mixed-type of urinary incontinence; short and long term results. \nhttp://www.obgyn.net/urogyn/urogyn.asp?page=urogyn/articles/\nurethroraphy-09280\n\n4-Abdel Karim M. El Hemaly, Ibrahim M Kandil, and Bahaa E. El Mohamady. Menopause, and Voiding troubles. \nhttp://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly03/el-hemaly03-ss\n\n5-El Hemaly AKMA, Mousa L.A. Micturition and Urinary\tContinence. Int J Gynecol Obstet 1996; 42: 291-2. \n\n6-Abdel Karim M. El Hemaly.\n Urinary incontinence in gynecology, a review article.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/abs-urinary_incotinence_gyn_ehemaly \n\n7-El Hemaly AKMA. Nocturnal Enuresis: Pathogenesis and Treatment. \nInt Urogynecol J Pelvic Floor Dysfunct 1998;9: 129-31.\n \n8-El Hemaly AKMA, Mousa L.A.E. Stress Urinary Incontinence, a New Concept. Eur J Obstet Gynecol Reprod Biol 1996; 68: 129-35. \n\n9- El Hemaly AKMA, Kandil I. M. Stress Urinary Incontinence SUI facts and fiction. Is SUI a puzzle?! http://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly/el-hemaly-ss\n\n10-Abdel Karim El Hemaly, Nabil Abdel Maksoud, Laila A. Mousa, Ibrahim M. Kandil, Asem Anwar, M.A.K El Hemaly and Bahaa E. El Mohamady. \nEvidence based Facts on the Pathogenesis and Management of SUI. http://www.obgyn.net/displayppt.asp?page=/English/pubs/features/presentations/El-Hemaly02/el-hemaly02-ss\n\n11- Abdel Karim M. El Hemaly*, Ibrahim M. Kandil, Mohamad A. Rizk and Mohamad A.K.M.El Hemaly.\n Urethro-plasty, a Novel Operation based on a New Concept, for the Treatment of Stress Urinary Incontinence, S.U.I., Detrusor Instability, D.I., and Mixed-type of Urinary Incontinence.\nhttp://www.obgyn.net/urogyn/urogyn.asp?page=/urogyn/articles/urethro-plasty_01\n\n12-Ibrahim M. Kandil, Abdel Karim M. El Hemaly, Mohamad M. Radwan: Ultrasonic Assessment of the Internal Urethral Sphincter in Stress Urinary Incontinence. The Internet Journal of Gynecology and Obstetrics. 2003. Volume 2 Number 1. \n\n13-Abdel Karim M. El Hemaly. Nocturnal Enureses: A Novel Concept on its pathogenesis and Treatment.\nhttp://www.obgyn.net/urogynecolgy/?page=articles/nocturnal_enuresis\n\n14- Abdel Karim M. El Hemaly. 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