Investigating the environmental Kuznets curve (EKC) hypothesis by
Investigating the environmental Kuznets curve (EKC)hypothesis by utilizing the ecological footprint as an indicator of environmental degradation
Usama Al-mulali a ,*,Choong Weng-Wai b ,1,Low Sheau-Ting c ,1,Abdul Hakim Mohammed d ,2
a
Faculty of Business,Multimedia University,75450Melaka,Malaysia
b Department of Real Estate,Faculty of Geoinformation &Real Estate,Universiti Teknologi Malaysia,81310Johor Bahru,Malaysia c
Centre of Real Estate Studies,Department of Real Estate,Faculty of Geoinformation &Real Estate,Universiti Teknologi Malaysia,81310Johor Bahru,Malaysia d
Centre of Real Estate Studies,Department of Real Estate,Faculty of Geoinformation &Real Estate,Universiti Teknologi Malaysia,81310Johor Bahru,Malaysia
A R T I C L E I N F O Article history:
Received 2January 2014
Received in revised form 3June 2014Accepted 24August 2014
Keywords:
Ecological footprint GDP growth
Financial development
Environmental Kuznets curve (EKC)hypothesis
A B S T R A C T
This study investigates the environmental Kuznets curve (EKC)hypothesis using a country ’s ecological footprint as an indicator of environmental degradation.Ninety-three countries were examined,categorized by income.The ?xed effects and the generalized method of moments results clearly showed an inverted U-shaped relationship between the ecological footprint and GDP growth,which represents the EKC hypothesis in upper middle-and high-income countries but not in low-and lower middle-income countries.This relationship only occurs in a stage of economic development in which technologies are available that improve energy ef ?ciency,energy saving and renewable energy,which are not accessible for countries with low income due to their high cost.Moreover,energy consumption,urbanization,and trade openness increase environmental damage through their positive effect on the ecological footprint of most countries across all income groups.However,?nancial development reduces environmental degradation in lower middle-,upper middle-and high-income countries.This relationship con ?rms that loans from banks are primarily given to ?rms that establish investments in projects that are mostly environmentally friendly.From the results of this study,a number of recommendations can be provided for the investigated countries.
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1.Introduction
Over the last few decades,the world has witnessed a substantial growth in its social and economic development and human welfare,which,in turn,has increased the global demand for energy (fossil fuels in particular).Regardless of the large efforts made by different countries to increase the role of renewable energy,energy ef ?ciency and energy conservation,fossil fuels still represent the dominant source of energy,representing 80%of the
total energy used globally (World Development Indicators,2013);therefore,the world has also witnessed a large environmental degradation problem,which is one of the major concerns that countries around the globe are currently facing.Thus,this dilemma has attracted the attention of many researchers in exploring the relationship between macroeconomic variables (especially GDP (gross domestic product)growth),energy consumption and pollution in different countries and regions utilizing different econometric methodologies.Despite the wide-ranging literature that has investigated this relationship,most of the studies have focused on utilizing CO 2emissions as an indicator of environmental pollution which represents a portion of it.Thus,to have a better understanding of the relationship between environmental degradation,energy consumption and GDP growth,this study will utilize the ecological footprint as an indicator of environmental degradation.In addition,this study
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E-mail addresses:usama81za@https://www.360docs.net/doc/df8672733.html, (U.Al-mulali),cwengwai@utm.my (C.Weng-Wai),lowsheauting@https://www.360docs.net/doc/df8672733.html, (L.Sheau-Ting),abdhakim@utm.my (A.H.Mohammed).1
Tel.:+60167186819.2
Tel.:+60197502150.https://www.360docs.net/doc/df8672733.html,/10.1016/j.ecolind.2014.08.029
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Ecological Indicators 48(2015)315–323
Contents lists available at ScienceDirect
Ecological Indicators
j o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /e c o l i n
d
will investigate ninety-three countries,categorizing them by income level because the ecological footprint varies between countries based on their income levels.Thus,the results of this study reveal the similarities and the differences between the countries in various income groups.
2.Literature review
The nexus of relationships between GDP growth(on an aggregate and disaggregate level),energy consumption(on an aggregate and disaggregate level)and pollution has been thoroughly studied by different researchers.These studies have utilized different econometric methodologies and have investigat-ed different countries and regions;Table A1(Appendix A1)reviews a summary of the previous studies that have explored the relationship between energy consumption,GDP growth and CO2 emissions.A large number of studies have concluded that energy consumption,GDP growth and CO2emissions are co-integrated. Therefore,the existence of a long-run relationship between the variables was con?rmed in79%of the studies.In addition,different types of Granger causality tests have been used in previous studies to examine the causal relationship between the variables.A number of studies found a feedback causality between energy consumption,GDP growth and CO2emissions,while a unidirec-tional causality running from energy consumption and CO2 emissions to GDP growth and a one-way causality from GDP growth to energy consumption and CO2emissions were also concluded by various distinct studies.However,a few studies found no causal relationship between the variables,while many other researchers reached different conclusions from their Granger causality test results.
From Table A1,it is clear that the results from the previous studies reached different conclusions;essentially,the results were mixed.In addition,most of the aforementioned studies used CO2 emissions as an indicator of environmental degradation,which represents only a small portion of total environmental damage.To provide a more complete perspective,the main objective of this study is to utilize a country’s ecological footprint as an indicator of pollution in examining the nexus of relationships between energy consumption,GDP growth and environmental degradation.The ecological footprint can reveal the effect of a country or a nation on the environment in terms of air,soil and water.The second objective of this study is to separate countries based on their income levels,as a country’s ecological footprint increases with higher levels of income.The next objective of this study is to examine the validity of the environmental Kuznets curve(EKC) hypothesis,which has been explored by a number of researchers such as Halicioglu(2009)in Turkey,Lean and Smyth(2010)and Saboori and Sulaiman(2013a,b)in the Association of Southeast Asian Nations(ASEAN),Pao and Tsai(2010)in the BRIC(Brazil, Russia,India,China)countries,Ang(2007)in France,Apergis and Payne(2009)in Central America,Jalil and Mahmud(2009)in China,Hamit-Haggar(2012)in Canada and Marrero(2010)in Europe.All of these studies have found an inverted U-shaped relationship between CO2emissions and income;during a country’s early stages of development,the increase in income will increase pollution until the country’s income reaches a certain point of economic development(when more technologies are available that improve energy ef?ciency,energy saving and renewable energy)where the relationship between income and pollution is negative.Thus,this study will investigate whether the inverted U-shaped relationship(EKC hypothesis)will occur in the investigated income groups.Based on the EKC hypothesis,the chances of the inverted U-shaped relationship will be higher as the income of the country increases.Moreover,the countries are grouped into income categories as the ecological footprint changes with the countries’income.Furthermore,grouping these countries by income can show the similarities and differences between the countries at the income level.
Despite the assumption that the EKC hypothesis is not applicable for poor countries,there have been no studies that empirically con?rmed this supposition.The EKC hypothesis explains that the poor countries are still in the early stages of economic development;thus these countries have not yet reached to the turning point where the relationship between income and pollution is negative.Consequently,this study will examine the EKC hypothesis for the low-income countries to con?rm whether the hypothesis holds.Moreover,the identi?cation of the factors that determine the environmental degradation can help provide policy suggestions and recommendations for the low-income countries to reduce the environmental pressure that these countries are experiencing.
3.Data and methodology
Annual data from1980–2008are utilized for the panel data analysis,to achieve the previously mentioned goals of this study,a panel model is established,de?ning the dependent variable as a country’s ecological footprint as an indicator of pollution.This dependent variable is dependent on a number of independent variables,namely GDP,energy consumption,trade openness and ?nancial development.These indicators have been used as major determinants of pollution(CO2emissions)by some of the previous studies reviewed in Table A1.The relationship between ecological footprint,GDP,energy consumption,urbanization,trade openness, and?nancial development can be speci?ed as follows:
LECO it?b1i LGDP ittb2i LGDP2ittb3i LEC ittb4i TD it
tb5i LUR ittb6i LFD ittv itz itte it(1)
LECO it?b1i LGDP ittb2i LGDP2ittb3i LEC ittb4i LTD it
tb5i LUR ittb6i LFD itta LECOeità1Ttv itz tte it(2) The?rst equation is the panel model that contains the?xed country and time effect,while the second equation is the GMM equation,which is essentially a dynamic panel equation that contains dynamic effects(LECO ità1),country-?xed effects(v), time-?xed effects(&)and an error term(e).t represents the time period t(1980–2008),and i is the cross section(16low-income countries,26lower middle-income countries,26upper middle-income countries,31high-income countries).The b1i......b6i represent the slope coef?cients,a is the constant,and e is the error term.LECO is the log of ecological footprints,which represents environmental limits and the amount that humanity exceeds them;it is essentially the sum of the cropland,grazing,?shing, forest,CO2emissions and Infrastructure footprints.In other words, it the area of land and ocean needed to support the country’s consumption measured in hectares.This means the higher a country’s ecological footprint is,the higher is the environmental damage that the country is causing.LGDP is the log of the gross domestic product measured in millions of2000-constant US dollars,LEC is the log of total primary energy consumption measured in Quadrillion,LTD is log of total trade of goods and services,which is the sum of total exports and imports of goods and services measured in millions of2000-constant US dollars, LUR is the log of urban population as an indicator of urbanization measured in thousands of people,and LFD is the log of domestic credit to the private sector measured in millions of2000-constant US dollars as an indicator of?nancial development.
The data source for GDP,total exports of goods and services, total imports of goods and services,urban population and domestic credit to the private sector was the World Development Indicators
316U.Al-mulali et al./Ecological Indicators48(2015)315–323
(2013a).However,the data source for energy consumption was the Energy Information Administration(EIA)(2013).The data source for ecological footprint was the Global Footprint Network,2013.
Because this study attempts to examine the EKC hypothesis,this study included the GDPP square for each model.If we conclude that the slope coef?cient for the GDPP is positively signi?cant (b1i>0)and the slope coef?cient for the GDPP square is negatively signi?cant(b2i<0),an inverted U-shaped relationship between GDPP and the ecological footprint will result,which represents the EKC hypothesis.Ninety-three countries will be examined and categorized by income level as low-income,lower middle-income, upper middle-income and high-income countries(World Bank country and lending groups,2013).Table1reviews the countries under investigation based on their income levels.World Bank country and lending groups,2013
3.1.Panel unit root test
The most essential step in an econometric analysis is to test the stationarity of the variables,as a variable cannot be used in the analysis if it is not stationary.A variable is said to be stationary if its mean and autocovariances do not depend on time.
Because this study utilizes a panel analysis,the panel unit root test is utilized because recent literature has suggested that panel unit root tests have a higher power compared to the unit root tests for individual time series(Baltagi,2009).The panel unit root tests are simply multiple-series unit roots that are modi?ed for the panel structure in which the presence of cross-sections is generated from a single series.Three types of unit root tests are used,namely,Im,Pesaran and Shin(IPS)(2003)Fisher-type ADF and PP unit root tests proposed by Maddala and Wu(1999)and Choi(2001).These tests have been used in the previous literature when utilizing panel analysis(Lean and Smyth,2010;Pao and Tsai, 2010,2011a,b;Wang et al.,2011;Sharma,2011;Zilio and Recalde, 2011;Hamit-Haggar,2012;Al-mulali and Foon Tang,2013).
The IPS,ADF and PP tests allow for individual unit root processes so that the autoregressive coef?cients may vary across cross-sections.These tests are all considered in the merging of individual unit root tests to derive panel results.The IPS,ADF and PP tests work under the null hypothesis of a panel unit root and the alternative hypothesis of no panel unit root.
3.2.The panel regression
There are two classes of panel estimator approaches that can be employed in this study namely the?xed and the random effects models.The?xed and random effects models are two well-known models used in modelling panel data.The?xed effects model portions of speci?cations are controlled using orthogonal forecasts. These forecasts of projections remove the speci?c means from the cross-sections and the period from the dependent variables and the exogenous regressors and then utilizes the quanti?ed regression using the demeaned data(Baltagi,2009).The important bene?t of the?xed effects model is that it can eliminate the bias problems arising from the omitted variables that do not change over time. Meanwhile,the random effects model assumes that the equivalent effects of the cross-section effect vectors and the time period effect vectors are essentially uncorrelated.In other words,the random effects model accepts that the effects are uncorrelated with the residuals.To determine the optimal model,the Hausman(1978)test was used,as the test compares the random and?xed effects estimates of coef?cients.The Hausman test is based on Chi-square statistics;if the Chi-square statistic is signi?cant,the random effects model is not reliable,and the?xed effects model should be utilized. However,both the?xed and the random effect are weak in controlling the correlation and the heterogeneity between the instruments'variables and disturbance.Therefore,the generalized method of moments(GMM)is utilized,
The GMM is a common method for estimating parameters in statistical https://www.360docs.net/doc/df8672733.html,ually it is applied in the setting of semi parametric models,where the parameter of interest is?nite-dimensional,whereas the full shape of the distribution function of the data may not be known,and therefore the maximum likelihood estimation is not applicable.The GMM belongs to a number of estimators,recognized as M-estimators,which can be identi?ed by minimizing a number of the functions of a criterion.The model is essentially a robust estimator that does not require information about the precise distribution of the disturbances;it provides a number of estimates that can eliminate the correlation and the heterogeneity between the instruments’variables and distur-bance.This study uses the lagged difference and the constant for the variables as instruments control multicollinearity;moreover, the validity of the instruments’variables for the GMM models are examined by utilizing the Sargan test.This test is essentially a Chi-square test that determines whether the residuals are correlated with the instrument variables.If we cannot reject the null hypothesis of the Sargan test,there is no indication of instrument misspeci?cation;therefore,the instruments are valid (Arellano and Bond,1991).
4.Econometrics results
The?rst step in the analysis is to examine the stationarity of the variables,therefore,the IPS,ADF and PP unit root tests are applied. Table2shows the panel unit root test results,namely,the IPS,ADF and PP.Similar to the time series unit root test results,the variables were all stationary in the countries of all income groups but at different levels.
As the variables are observed to be stationary,the next step in the analysis is to examine the correlation between the dependent and independent variables by utilizing the generalized method of moments(GMM)and the?xed effects or random effects model.
Table3reviews the results of the panel regressions for the low-, lower middle-,upper middle-and high-income countries.The Hausman test was performed to con?rm whether the?xed effects or the random effects model is the optimal model for our panel regression.Because the Chi-square is signi?cant at the1%level for countries in all the income groups(see Table3),the?xed effects
Table1
List of countries under investigation categorized based on their income level.
Low-income countries Bangladesh,Benin,Burkina Faso,Chad,Congo,Ethiopia,Gambia,Kenya,Mozambique,Rwanda,Sierra Leone,Tanzania,Togo,Uganda, Zimbabwe
Lower middle-income countries Bolivia,Cameroon,China,Colombia,Congo,Cote d'Ivoire,Dominican Republic,Ecuador,Egypt,El Salvador,Guatemala,Honduras,India, Indonesia,Morocco,Nicaragua,Pakistan,Peru,Philippines,Senegal,Sri Lanka,Sudan,Swaziland,Syria,Tunisia,Yemen,Zambia.
Upper middle-income countries Algeria,Argentina,Belize,Botswana,Brazil,Bulgaria,Chile,Costa Rica,Gabon,Iran,Jordan,Malaysia,Mexico,Mauritius,Panama,Poland, Romania,South Africa,Thailand,Turkey,Uruguay,Venezuela
High-income countries Australia,Austria,Bahamas,Belgium,Canada,Cyprus,Denmark,Finland,France,Germany,Greece,Hungary,Iceland,Italy,Japan,South Korea,Luxembourg,Malta,Netherlands,New Zealand,Norway,Portugal,Singapore,Spain,Sweden,Switzerland,Trinidad and Tobago,United
Kingdom,United States of America
U.Al-mulali et al./Ecological Indicators48(2015)315–323317
318U.Al-mulali et al./Ecological Indicators48(2015)315–323
Table2
Panel unit root tests results.
Panel I:Im,Pesaran and Shin(IPS)
Variables Level First difference
Intercept Intercept and trend Intercept Intercept and trend Low-income countries LECO 2.64476à1.20339à14.4244à13.1165
LGDPP9.29664 1.51485à8.02887aà8.84002a
LGDPP29.56169 1.79838à7.79933aà8.76873a
LEC 4.23520à0.37289à12.5290aà11.2630a
LTD 5.586930.62382à7.40626aà6.82877a
LFDà1.43011à1.34419cà10.0044aà8.41193a
LUR 2.00664à8.78219aà1.84382bà1.84382c Lower middle-income countries LECO 5.74790à1.78378bà16.9606aà14.7705a
LGDPP10.42350.09256à9.06489aà7.62319a
LGDPP210.84280.42195à8.86399aà7.55030a
LEC 3.84865à0.06900à12.9318aà10.9704a
LTD9.67356à0.05215à10.5782aà8.42525a
LFD 1.91019 1.67547à8.97166aà6.67614a
LUR 2.03722à3.53477aà0.82408à0.77357 Upper middle-income countries LECO 4.62872à2.13598bà16.3873aà13.5319a
LGDPP9.06934à0.78071à9.99510aà8.34602a
LGDPP29.44906à0.56045à9.89076aà8.30127a
LEC 3.94671à1.43052cà14.3506aà12.0834a
LTD 6.84119à2.34192aà11.0693aà8.85082a
LFDà2.03786bà0.96323à12.5372aà10.6209a
LURà7.62476a 2.89705 1.894150.60965
High-income countries LECOà1.64964bà5.96889aà30.7272aà28.6165a
LGDPP 4.38051à1.43310cà9.84382aà8.29897a
LGDPP2 4.66600à1.49887cà9.87842aà8.23265a
LEC 4.94624 3.06859à11.3581aà9.95067a
LTD7.91347à1.45513cà13.2047aà9.96581a
LFD 3.81900 2.43186à8.89302aà7.13926a
LUR7.96207à5.54822aà3.08166aà1.16167
Panel II:Fisher-type ADF
Low-income countries LECO20.839439.7866236.138a202.523a
LGDPP 3.9483437.8467129.550a136.392a
LGDPP2 3.8731035.4929125.959a135.280a
LEC25.584440.1740202.257a168.462a
LTD17.419134.3503116.559a103.870a
LFD41.878742.3904162.102a130.753a
LUR37.6574366.850a51.6157b51.6157b
Lower middle-income countries LECO20.971171.7880b345.020a279.632a
LGDPP 5.4304567.7040b178.332a150.894a
LGDPP2 4.8570164.2526c174.333a149.604a
LEC24.861952.7479257.813a206.744a
LTD 6.6078966.8340c210.914a161.545a
LFD39.754235.6538181.752a137.212a
LUR57.1036102.231a61.517090.8352a
Upper middle-income countries LECO16.903372.9637b338.595a259.178a
LGDPP8.2614952.4439199.071a162.755a
LGDPP27.2838063.0327196.779a161.883a
LEC31.290271.5894294.056a232.770a
LTD14.882075.2958a220.684a171.294a
LFD88.6044a69.1993c251.518a203.271a
LUR83.1677a58.9926a35.928246.8052
High-income countries LECO27.225167.9630320.522a275.644a
LGDPP32.311077.5093c215.517a182.370a
LGDPP230.010678.1311c216.218a180.755a
LEC101.190a159.931a668.855a656.692a
LTD10.317780.8535c294.003a215.695a
LFD64.312462.2768202.969a161.635a
LUR31.4709355.853a111.740a77.1076a
Panel III:Phillips–Perron
Low-income countries LECO37.823870.0256a351.847a1362.28a
LGDPP 2.9429527.3464215.558a311.983a
LGDPP2 2.8351326.0550211.663a321.960a
LEC51.1413b103.824a202.257a839.020a
LTD14.234844.1197c228.911a448.023a
LFD43.731229.0124259.217a554.587a
LUR108.052a34.7100a279.235a279.235a
Lower middle-income countries LECO32.3755111.310a613.163a1560.23a
LGDPP13.652250.7847287.511a308.994a
LGDPP212.219549.8269282.788a307.142
LEC44.733471.2169b486.546a688.259a
LTD 5.5814353.7244349.958a329.688a
LFD48.740050.9816362.222a617.742a
LUR432.289133.412a42.821626.5801
model is the optimal model for the analysis.The problem with the ?xed effects model is that it is weak in controlling heterogeneity and serial correlation.Therefore,is it important to make the?xed effects model robust in terms of serial correlation and heteroge-neity,which can be done by computing standard errors that are robust to serial correlation and heterogeneity(Arellano1987; White1980).The?xed effects results for the low-income countries show that the coef?cients for LGDP and LGDP2are both positive and signi?cant(b1i and b2i>0),which indicates an upper trend relationship with the ecological footprint.Thus,the environmental Kuznets curve(EKC)does not exist for low-income countries because these countries are in the early stages of development (income equality is lower than income inequality).Therefore,with higher income comes higher environmental damage(ecological footprint).Moreover,it was found that urbanization,trade openness and?nancial development have no signi?cant effect on the ecological footprint because urbanization,trade openness and?nancial development in low-income countries are low compared to those of countries in other income groups.In addition, it was found that energy consumption increases environmental damage.
The results for the lower middle-income countries show that LGDP has a positive and signi?cant effect on the ecological footprint,while the LGDP square is negative,which supports the EKC hypothesis,but because the LGDP square is insigni?cant,we have to reject the hypothesis.Similar to the low-income countries, urbanization,trade openness and?nancial development do not have a signi?cant effect on the ecological footprint of lower middle-income countries.However,energy consumption has a signi?cant and positive effect on the ecological footprint;thus, energy consumption increases environmental degradation.
Moreover,the?xed effects results for the upper middle-and high-income countries reveal the existence of an un-inverted U-shaped relationship between LGDP,LGDP2and LECO,thus validating the EKC hypothesis for the upper middle-income group countries.In addition,energy consumption and urbanization are the sources of environmental damage in upper middle-income countries due to their positive signi?cant effect on the ecological footprint.On the other hand,?nancial development has a negative effect on the ecological footprint,which indicates that?nancial development reduces environmental damage in these countries.
Before utilizing the GMM model,this study used the Sargan test to explore the validity of the GMM instruments,and as shown by the results in Table3,the instruments used in the GMM model are valid for all income groups.The results for the low-and lower middle-income countries reveal that the EKC hypothesis is not valid in these countries.Moreover,similar to the?xed effects model,energy consumption is the only variable that has a signi?cant positive effect on the ecological footprints of low-income countries,while it was found that energy consumption including urbanization positively increases the ecological footprints of lower middle-income coun-tries.In addition,?nancial development reduces environmental degradation through its signi?cant negative effect on the ecological footprint,while it has no signi?cant impact on the ecological footprints of low-income countries.
The GMM results for the upper middle-and the high-income countries revealed the existence of the EKC hypothesis in both income groups.Moreover,it was found that urbanization,trade openness and energy consumption are the main sources of environmental degradation based on their positive impact on the ecological footprint,while?nancial development reduces environmental damage due to the negative impact on the ecological footprints of countries in these two groups.
The asterisks a,b and c indicate statistical signi?cance at the1%, 5%and10%levels,respectively.
5.Conclusion and discussion of results
The major weakness in the previous literature is that most previous studies utilized CO2emissions when investigating the environmental Kuznets curve(EKC)hypothesis,which represents only a small portion of total environmental degradation.Therefore, the main objective of this study is to investigate the EKC hypothesis in ninety-three countries based on their income levels:low-income,lower middle-,upper middle-and high-income countries. To realize the aims of this research,a panel model was contrasted using a country's ecological footprint as the dependent variable. The ecological footprint can provide a more complete perspective of environmental damage.From the results of the?xed effects and the generalized method of moments(GMM)models,it was found that the EKC hypothesis is not valid for low-and lower middle-income countries.However,the EKC hypothesis is valid for upper-middle and high-income countries.The reason for this result is the fact that low-and lower-middle income countries are in the early stages of economic development.Therefore,environmental damage worsens as countries'economic growth tends to increase. On the other hand,when countries reach a high level of economic development in which the relationship between income and environmental damage becomes negative,an inverted U-shaped relationship results.This shape of the relationship only occurs when technologies are available that improve energy ef?ciency, energy saving and renewable energy,which are not accessible for low-income countries due to their high cost.Therefore,the validity of the EKC hypothesis increases as a country's income increases,
Table2(Continued)
Panel I:Im,Pesaran and Shin(IPS)
Variables Level First difference
Intercept Intercept and trend Intercept Intercept and trend
Upper middle-income countries LECO21.4076130.127a615.551a1248.80a
LGDPP9.8594366.1888c270.055a236.998a
LGDPP27.9842558.4521267.612a236.736a
LEC27.056791.1514640.105a1052.80a
LTD9.8643941.3796288.482a254.282a
LFD61.759245.1957379.356a349.263a
LUR432.680a100.266a34.180446.6992
High-income countries LECO101.416a400.485a714.739a1803.35a
LGDPP31.802437.7553249.188a193.836a
LGDPP229.347038.9596250.342a193.474a
LEC32.809986.3749b517.246a1046.45a
LTD9.1616658.4280391.619a363.121a
LFD65.541957.0240381.914a492.722a
LUR124.669a31.580675.3984a56.6794a
U.Al-mulali et al./Ecological Indicators48(2015)315–323319
which is the case for the upper middle-and high-income countries studied in this paper.This conclusion is in line with the conclusions of Halicioglu (2009)in Turkey,Lean and Smyth (2010)and Saboori and Sulaiman (2013a,b)in ASEAN,Pao and Tsai (2010)in the BRIC countries,Ang (2007)in France,Apergis and Payne (2009)in Central America,Jalil and Mahmud (2009)in China,Hamit-Haggar (2012)in Canada and Marrero (2010)in Europe.
Moreover,the results also show that energy consumption is an important source of environmental damage in all income groups.There are several scholars,such as Chang (2009),Lean and Smyth (2010),Pao and Tsai (2010),Apergis and Payne (2009),Hamit-Haggar (2012),Marrero (2010),Shahbaz et al.(2013a,b)that reached the same conclusion.Moreover,most of the world energy consumption comes from fossil fuels which represent over 67%of total energy consumption (World Development Indicators,2013)which is well known to cause global warming and climate change.In addition,urbanization and trade openness cause more environmental degradation through their positive effect on the ecological footprints of lower middle-,upper middle-and high-income countries.This relationship is expected as urbanization can cause many environmental problems such as urban domestic sewage,industrial ef ?uent,solid waste,airborne smoke,soot,dust,and liquid droplets from fuel combustion.Moreover,these results were in the line with Sharma (2011),Jafari et al.(2012),and Hossain (2011).Furthermore,?nancial development has no effect on the ecological footprints of low-income countries because the level of ?nancial development in these countries is poor compared to the levels in upper middle-and high-income countries (World Development Indicators,2013).However,?nancial development lessens environmental damage through its signi ?cant negative effect on the ecological footprints of lower middle-,upper middle-and high-income countries,which is because the improvements in environmental quality and a well-developed ?nancial sector are a positively correlated with economic progress in general.Moreover,the ?nancial sector obviously is much less capital-intensive than industrial production and therefore generates less pollution.
From the results of this study,it is recommended that the countries investigated in this study prioritize energy ef ?ciency projects to improve energy saving and enhance the role of renewable energy in reducing the ecological footprint arising from the consumption of energy,most of which comes from fossil fuels.Moreover,it is important for upper middle-and high-income countries to take trade-related actions and strategies to increase environmental protection because total trade increases the ecological footprints of countries in these income groups.Because urbanization increases the ecological footprints of lower middle-,upper middle-and high-income countries,it is important for policymakers in urban planning to reduce these urbanization levels,which can help reduce the environmental damage produced by urbanization.
Moreover,recommendations for political measure is important such as reinforcing the environmental regulations in the investi-gated countries on the polluted industries in particular to follow these regulations which can help to reduce their pressure on the environment.This can be achieved by a better corruption control.Furthermore,a better democracy is essential since a better governess can improve the aim of the environmental interest groups by stimulating the political freedom and independency of information circulation.This will,in turn,elevate the public awareness as well as the support for the environmental legislation.Thus,the rise in public awareness towards the environment will increase the public demand for improving the environmental quality.
Since this study did not implement Granger causality to examine the causal relationship between the economic indicators utilized in the model and the ecological footprint,we recommend
T a b l e 3T h e r e g r e s s i o n r e s u l t s .
L E C O a s t h e d e p e n d e n t v a r i a b l e
F i x e d e f f e c t r e g r e s s i o n r e s u l t s
G M M r e g r e s s i o n r e s u l t s
V a r i a b l e s
L o w -i n c o m e c o u n t r i e s
L o w e r m i d d l e -i n c o m e
c o u n t r i e s
U p p e r m i d d l e -i n c o m e c o u n t r i e s
H i g h -i n c o m e c o u n t r i e s
L o w -i n c o m e c o u n t r i e s
L o w e r m i d d l e -i n c o m e c o u n t r i e s
U p p e r m i d d l e -i n c o m e c o u n t r i e s H i g h -i n c o m e c o u n t r i e s
L G D P 1.029025c (1.989478)0.191474c (1.986071)0.072617b (2.091281)1.552650a (6.416952)0.154125c (1.826600)0.187745b (2.541383)
0.144529a (3.546050)0.822847b (2.174235)L G D P 2
0.129425b (2.226944)-0.004831(-1.233224)à0.001684a (à2.392093)-0.013216b (à2.493935)1.649788c (2.646375)à0.005170(à0.656687)à0.229539c (1.736575)à0.025653b (à2.718606)L E C 0.241464c (1.955480)0.025429c (1.677626)0.933005b (2.516403)0.225171b (2.420187)0.033328b (2.315380)
0.065476a (3.567165)
0.031366b (2.803213)0.556040a (6.530433)L T D à0.008697(à0.149139)0.037020(1.551623)0.261579a (5.714779)0.138777a (3.606072)0.000888(0.008287)0.006470(0.244470)0.048349b (2.455231)à0.261226a (à3.188791)L F D 0.053720(0.685702)à0.000224(à1.223088)à0.119002a (à5.393247)à0.000794a (-4.899955)0.000752(0.808457)à0.056317c (à1.830178)-0.001198a (-4.114255)-0.000543a (-3.610594)L U R 0.066472(1.367875)0.061958(1.351317)0.043876a (3.454908)
0.182168a (3.639384)
0.138191(0.513601)0.150279a (3.507712)
0.135896b (2.669472)
-0.342955b (-2.314862)
A d j u s t e d R 2
0.9463760.9394010.9261450.944954––––D W s t a t i s t i c s 1.9930272.1009522.0488161.992619––––H a u s m a n C h i -s q u a r e 24.937427a 33.579849a
94.708152a
21.856339a
––––
S a r g a n t e s t p -v a l u e
––––0.9378895
0.691141350.748375320.3586957
T h e u n i t r o o t t e s t s w e r e c o n d u c t e d w i t h i n d i v i d u a l t r e n d s a n d i n t e r c e p t s f o r e a c h v a r i a b l e .T h e o p t i m a l l a g l e n g t h w a s s e l e c t e d a u t o m a t i c a l l y u s i n g S c h w a r z i n f o r m a t i o n c r i t e r i a (S I C ).T h e a s t e r i s k s a ,b a n d c i n d i c a t e s t a t i s t i c a l s i g n i ?c a n c e a t t h e 1%,5%a n d 10%l e v e l s ,r e s p e c t i v e l y .
320
U.Al-mulali et al./Ecological Indicators 48(2015)315–323
for the future studies to investigate the causality between these variables.The results from this examination could provide a better understanding of the interrelation between the economic indica-tors and the ecological footprint which depicts the overall damage to the environment.
Acknowledgments
This study was supported by UTM Flagship project with Vote No.Q.J130000.2527.03H24.We also appreciate the anonymous referees for their constructive comments.Any errors are our own.
Appendix A.
See Table A1.
Table A1
Summary of studies that have investigated the nexus of relationships between energy consumption,economic growth and CO2emissions.
Author Period of
study
Country/region Methodology Results
Chang(2009)1981–2006China Johansen co-integration VECM Granger
causality Energy consumption,GDP growth and CO2emission are co-integrated$GDP growth-CO2emission-energy consumption
Halicioglu (2009)1960–2005Turkey ARDL bound testingJohansen co-
integration VECM Granger causality
Energy consumption,GDP growth and CO2emission are co-integratedCO2
emission$energy consumptionCO2emission$GDP growth
Khan et al. (2013)1975–2011Pakistan Johansen co-integrationToda and
Yamamoto Granger causality variance
decomposition
Energy consumption,GDP per capita of energy use and pollution are co-
integrated energy consumption!pollution greenhouse gas emissions,
combustible renewables and waste are the largest contributors to changes
in energy consumption
Lean and Smyth (2010)1980–2007ASEAN Johansen Fisher panel co-integration test.
Panel dynamic OLSVECM Granger
causality
Energy consumption,GDP growth and CO2emission are co-integrated
energy consumption and GDP growth have a long-run positive
relationship with CO2emission energy consumption and CO2
emission!GDP growthCO2emission!energy consumption
Saboori and Sulaiman (2013a,b)1971–2009ASEAN ARDL bound testing VECM Granger
causality
Energy consumption,GDP growth and CO2emission are co-
integrated$GDP growth-CO2emission-energy consumption in
Indonesia,Malaysia,Philippines and ThailandEnergy consumption$CO2
emission in SingaporeGDP growth$CO2emission in Singapore
Pao and Tsai (2010)1971–2005BRIC Pedroni,Kao and Johansen Fisher panel co-
integrationVECM Granger causality
Energy consumption,GDP growth and CO2emission are co-integrated.
Energy consumption$CO2emissionsEnergy consumption$GDP
growthCO2emission!GDP growth
Wang et al. (2011)1995–2007China Pedroni,panel co-integrationVECM
Granger causality
Energy consumption,GDP growth and CO2emission are co-integrated.
Energy consumption$CO2emissionsEnergy consumption$GDP
growthGDP growth!CO2emission.
Ang(2007)1960–2000France ARDL bound testingJohansen co-
integration VECM Granger causality Energy consumption,GDP growth and CO2emission are co-integrated. GDP growth!CO2emissionGDP growth$energy consumption
Apergis and Payne(2009)1971–2004Central
America
Pedroni,panel co-integration fully
modi?ed OLSVECM Granger causality
Energy consumption,GDP growth and CO2emission are co-integrated.
Energy consumption and GDP growth have a long-run positive effect on
CO2emission.Energy consumption$GDP growth energy
consumption$CO2emissionGDP growth!CO2emission
Sharma(2011)1985–200569countries
categorized by
income Panel GMM model GDP growth increases CO2emission in middle-and low-income countries
energy consumption and electricity consumption have a long-run positive
relationship with CO2emission only in high-income countries
Saboori and Sulaiman (2013a,b)1980–2009Malaysia ARDL bound testingJohansen co-
integration VECM Granger causality
Energy consumption,GDP growth and CO2emission are co-
integrated$GDP growth,energy consumption and CO2emission
Shahbaz et al. (2013a,b)1975–2011Indonesia ARDL bound testing VECM Granger
causality
Energy consumption,GDP growth and CO2emission are co-integrated.$
GDP growth,energy consumption and CO2emissionGDP growth and
energy consumption increases CO2emissionTrade and?nancial
development decreases CO2emission
Alam et al. (2011)1972–2006Bangladesh ARDL bound testingJohansen co-
integration VECM Granger causality
Energy consumption,GDP growth and CO2emission are co-integrated.
Energy consumption$GDP growth energy consumption$CO2
emissionCO2emission!GDP growth
Jafari et al.
(2012)
1971–2007Indonesia Toda and Yamamoto Granger causality?GDP growth,energy consumption and CO2emission Soytas and Sari
(2009)
1960–2000Turkey Toda and Yamamoto Granger causality CO2emission!energy consumption
Menyah and Wolde-Rufael (2010)1965–2006South Africa ARDL bound testingGranger causality Energy consumption,GDP growth and CO2emission are co-integrated.
Energy consumption!GDP growthCO2emission!GDP growth energy
consumption!CO2emissionOver50%of the variance of CO2emission
comes from energy consumption
Jalil and Mahmud (2009)1975–2005China ARDL bound testingARDL ECM
estimatesPairwise Granger causality
Energy consumption,GDP growth and CO2emission are co-integrated
Energy consumption and GDP growth have a positive long-run effect on
CO2emission GDP growth!CO2emission
Al-mulali et al. (2013)1980–2008Latin America
and the
Caribbean
Canonical co-integrating regression A positive bi-directional relationship between energy consumption,CO2
emission and GDP growth in60%of the countries
Al-mulali(2012)1990–2009Middle East Pedroni co-integration fully modi?ed
OLSVECM Granger causality Energy consumption,foreign direct investment,GDP growth,total trade and CO2emission are co-integrated energy consumption,foreign direct investment,GDP growth and total trade have a positive long-run effect on CO2emission$energy consumption,foreign direct investment,GDP growth,total trade and CO2emission
U.Al-mulali et al./Ecological Indicators48(2015)315–323321
Reference
Alam,M.J.,Begum,I.A.,Buysse,J.,Rahman,S.,Van Huylenbroeck,G.,2011.Dynamic modeling of causal relationship between energy consumption,CO2emissions and economic growth in India.Renew.Sust.Energ.Rev.15(6),3243–3251. Arellano,M.,https://www.360docs.net/doc/df8672733.html,puting robust standard errors for within-groups estimators.
Oxford Bull.Econ.Stat.49,431–434.
Arellano,M.,Bond,S.,1991.Some tests of speci?cation for panel data:Monte Carlo evidence and an application to employment equations.Rev.Econ.Stud.58, 277–297.
Al-mulali,U.,2012.Factors affecting CO2emission in the Middle East:a panel data analysis.Energy44(1),564–569.
Al-mulali,U.,Foon Tang,C.,2013.Investigating the validity of pollution haven hypothesis in the gulf cooperation council(GCC)countries.Energy Policy60(0), 813–819.
Al-mulali,U.,Lee,J.Y.M.,Hakim Mohammed,A.,Sheau-Ting,L.,2013.Examining the link between energy consumption,carbon dioxide emission,and economic growth in Latin America and the Caribbean.Renew.Sust.Energy Rev.26(0), 42–48.
Ang,J.B.,2007.CO2emissions,energy consumption,and output in France.Energy Policy35(10),4772–4778.Apergis,N.,Payne,J.E.,2009.CO2emissions,energy usage,and output in Central America.Energy Policy37(8),3282–3286.
Baltagi,B.,2009.Econometric Analysis of Panel Data.John Wiley and Sons Ltd.,UK. Chandran Govindaraju,V.G.R.,Tang,C.F.,2013.The dynamic links between CO2 emissions,economic growth and coal consumption in China and India.Appl.
Energy104(0),310–318.
Chandran,V.G.R.,Tang,C.F.,2013.The impacts of transport energy consumption, foreign direct investment and income on CO2emissions in ASEAN-5economies.
Renew.Sust.Energy Rev.24(0),445–453.
Chang, C.C.,2009.A multivariate causality test of carbon dioxide emissions, energy consumption and economic growth in China.Appl.Energy87, 3533–3537.
Choi,I.,2001.Unit root tests for panel data.J.Int.Money Finance20,249–272. Energy Information Administration,2013.International Energy Statistics.Wash-ington,DC,[Online](acessed25.07.13.).Available from:https://www.360docs.net/doc/df8672733.html,/ countries/data.cfm.
Global Footprint Network,2013.Ecological footprint.Oakland,USA;[Online] (acessed20.09.13)Available from September2013;https://www.360docs.net/doc/df8672733.html,/en/index.php/GFN/.
Halicioglu,F.,2009.An econometric study of CO2emissions,energy consumption, income and foreign trade in Turkey.Energy Policy37(3),1156–1164.
Table A1(Continued)
Author Period of
study
Country/region Methodology Results
Hamit-Haggar (2012)1990–2007Canada Pedroni co-integration VECM Granger
causality
Energy consumption,GDP growth and CO2emission are co-integrated
energy consumption and GDP growth have a positive long run effect on
CO2emission energy consumption$CO2emissionGDP growth!energy
consumption and CO2emission
Marrero(2010)1990–2006Europe Panel OLS,?xed effect and GMM model Energy consumption and GDP growth have a positive effect on CO2
emission in most of the models
Al-mulali and Tang(2013)1980–2009GCC countries Pedroni co-integration fully modi?ed
OLSVECM Granger causality
Energy consumption,GDP growth and CO2emission are co-integratedGDP
growth and energy consumption have a positive long-run effect on CO2
emission while foreign direct investment has a negative long-run effect on
CO2emission$GDP growth,energy consumption,foreign direct
investment and CO2emission
Pao and Tsai (2011a,b)1980–2007Brazil Johansen co-integration VECM Granger
causality
Energy consumption,GDP growth and CO2emission are co-
integrated$GDP growth,energy consumption and CO2emission
Pao et al.(2011)1990–2007Russia Johansen co-integration VECM Granger
causality Energy consumption,GDP growth and CO2emission are co-integrated$GDP growth,energy consumption and CO2emission
Pao and Tsai (2011a,b)1980–2007BRIC Pedroni,Kao&Johansen Fisher panel co-
integration VECM Granger causality
Energy consumption,GDP growth,foreign direct investment and CO2
emission are co-integrated energy consumption$GDP growthCO2
emission$GDP growth energy consumption!CO2emission foreign
direct investment$CO2emission
Sharif Hossain (2011)1971–2007newly
industrialized
countries
Johansen Fisher panel co-integration
VECM Granger causality GMM model
Energy consumption,GDP growth and CO2emission are co-integratedGDP
growth!energy consumption and CO2emission energy consumption
and GDP growth have a positive effect on CO2emission
Chandran Govindaraju and Tang, 20131965–2009China and India Bayer and Hanck co-integrationVECM
Granger causality for ChinaVAR Granger
causality for India
Energy consumption,GDP growth and CO2emission are co-integrated in
China only GDP growth!CO2emission in China and IndiaGDP
growth$energy consumption in ChinaCO2emission$energy
consumption in China and IndiaGDP growth!energy consumption in
India
Shahbaz et al. (2013a,b)1965–2008South Africa ARDL bound testing pairwise Granger
causality
Energy consumption,GDP growth and CO2emission are co-integrated
GDP growth and energy consumption increases CO2emissionTrade and
?nancial development decreases CO2emission
Jalil and Feridun (2011)1953–2006China ARDL bound testing pairwise Granger
causality
Energy consumption,GDP growth,?nancial development and CO2
emission are co-integratedGDP growth,energy consumption and trade
increases CO2emission,while?nancial development reduces itGDP
growth!CO2emission.
Chandran and Tang(2013)1971–2008ASEAN Johansen co-integration VECM Granger
causality
Energy consumption,GDP growth,foreign direct investment and CO2
emission are co-integrated only in Indonesia,Malaysia and Thailand
energy consumption and GDP growth increase CO2emission in the long
run while foreign direct investment has no effect on CO2emission GDP
growth$CO2emission in Indonesia and Thailand GDP growth!CO2
emission in Malaysia$energy consumption,foreign direct investment
and CO2emission in Thailand and Malaysia
Ozturk and Acaravci (2013)1960–2007Turkey ARDL bound testing VECM Granger
causality
Energy consumption,GDP growth,CO2emission,trade and?nancial
development are co-integrated energy consumption,GDP growth and
trade increases CO2emission,while?nancial development has no effect
on CO2emission.Financial development!GDP growth,energy
consumption and trade
Ozcan(2013)1990–2008Middle East Westerlund(2005)panel co-integration
test Fully modi?ed OLS VECM Granger
causality Energy consumption,GDP growth and CO2emission are co-integrated energy consumption has a long-run positive effect on CO2emission GDP growth has a negative long-run effect on CO2emission GDP
growth!energy consumption GDP growth and energy
consumption!CO2emission
The arrows show the direction of the causality:!indicates a one-way causality,$indicates a bi-directional causality and?shows no causality.GDP is gross domestic product,ELC is electricity consumption and RELC is renewable electricity consumption.
322U.Al-mulali et al./Ecological Indicators48(2015)315–323
Hamit-Haggar,M.,2012.Greenhouse gas emissions,energy consumption and economic growth:a panel cointegration analysis from Canadian industrial sector perspective.Energy Econ.34(1),358–364.
Hausman,J.A.,1978.Speci?cation tests in econometrics.Econometrica46, 1251–1272.
Im,K.S.,Pesaran,M.H.,Shin,Y.,2003.Testing for unit roots in heterogeneous panels.
J.Econ.115,53–74.
Jafari,Y.,Othman,J.,Nor,A.H.S.M.,2012.Energy consumption,economic growth and environmental pollutants in Indonesia.J.Policy Model.34(6),879–889. Jalil,A.,Feridun,M.,2011.The impact of growth,energy and?nancial development on the environment in China:a cointegration analysis.Energy Econ.33(2), 284–291.
Jalil,A.,Mahmud,S.F.,2009.Environment Kuznets curve for CO2emissions:a cointegration analysis for China.Energy Policy37(12),5167–5172.
Khan,M.A.,Khan,M.Z.,Zaman,K.,Khan,M.,Zahoor,H.,2013.Causal links between greenhouse gas emissions,economic growth and energy consumption in Pakistan:a fatal disorder of society.Renew.Sust.Energy Rev.25,166–176. Lean,H.H.,Smyth,R.,2010.CO2emissions,electricity consumption and output in ASEAN.Appl.Energy87(6),1858–1864.
Maddala,G.S.,Wu,S.A.,https://www.360docs.net/doc/df8672733.html,parative study of unit root tests with panel data and a new simple test.Oxford Bull.Econ.Stat.108,1–24.
Marrero,G.A.,2010.Greenhouse gases emissions,growth and the energy mix in Europe.Energy Econ.32(6),1356–1363.
Menyah,K.,Wolde-Rufael,Y.,2010.Energy consumption,pollutant emissions and economic growth in South Africa.Energy Econ.32(6),1374–1382.
Ozcan,B.,2013.The nexus between carbon emissions,energy consumption and economic growth in Middle East countries:a panel data analysis.Energy Policy 62(0),1138–1147.
Ozturk,I.,Acaravci,A.,2013.The long-run and causal analysis of energy,growth, openness and?nancial development on carbon emissions in Turkey.Energy Econ.36(0),262–267.
Pao,H.-T.,Tsai,C.-M.,2010.CO2emissions,energy consumption and economic growth in BRIC countries.Energy Policy38(12),7850–7860.
Pao,H.-T.,Tsai,C.-M.,2011a.Modeling and forecasting the CO2emissions,energy consumption,and economic growth in Brazil.Energy36(5),2450–2458. Pao,T.,Tsai,C.-M.,2011b.Multivariate Granger causality between CO2emissions, energy consumption,FDI(foreign direct investment)and GDP(gross domestic product):evidence from a panel of BRIC(Brazil,Russian Federation,India,and China)countries.Energy36(1),685–693.Pao,H.-T.,Yu,H.-C.,Yang,Y.-H.,2011.Modeling the CO2emissions,energy use,and economic growth in Russia.Energy36(8),5094–5100.
Saboori,B.,Sulaiman,J.,2013a.CO2emissions,energy consumption and economic growth in Association of Southeast Asian Nations(ASEAN)countries:a cointegration approach.Energy55(0),813–822.
Saboori,B.,Sulaiman,J.,2013b.Environmental degradation,economic growth and energy consumption:evidence of the environmental Kuznets curve in Malaysia.
Energy Policy60(0),892–905.
Shahbaz,M.,Hye,Q.M.A.,Tiwari,A.K.,Leit?o,N.C.,2013a.Economic growth,energy consumption,?nancial development,international trade and CO2emissions in Indonesia.Renew.Sust.Energy Rev.25(0),109–121.
Shahbaz,M.,Kumar Tiwar,A.,Nasir,M.,2013b.The effects of?nancial development, economic growth,coal consumption and trade openness on CO2emissions in South Africa.Energy Policy61(0),1452–1459.
Sharif Hossain,M.,2011.Panel estimation for CO2emissions,energy consumption, economic growth,trade openness and urbanization of newly industrialized countries.Energy Policy39(11),6991–6999.
Sharma,S.S.,2011.Determinants of carbon dioxide emissions:empirical evidence from69countries.Appl.Energy88(1),376–382.
Soytas,U.,Sari,R.,2009.Energy consumption,economic growth,and carbon emissions:challenges faced by an EU candidate member.Ecol.Econ.68(6), 1667–1675.
The World Bank World Development Indicators,2013.Washington,DC;[Online] (acessed14.01.13)Available from:https://www.360docs.net/doc/df8672733.html,/data-catalog/ world-development-indicators.
The World Bank,2013.country and lending groups.Washington,DC;[Online] (acessed25.10.13)Available from October2013;https://www.360docs.net/doc/df8672733.html,/ about/country-classi?cations/country-and-lending-groups.
Wang,S.S.,Zhou, D.Q.,Zhou,P.,Wang,Q.W.,2011.CO2emissions,energy consumption and economic growth in China:a panel data analysis.Energy Policy39(9),4870–4875.
Westerlund,J.,2005.News implements for panel cointegration.Econ.Rev.24, 297–316.
White,H.,1980.A heteroskedasticity-consistent covariance matrix and a direct test for heteroskedasticity.Econometrica48,817–838.
Zilio,M.,Recalde,M.,2011.GDP and environment pressure:the role of energy in Latin America and the Caribbean.Energy Policy39(12),7941–7949.
U.Al-mulali et al./Ecological Indicators48(2015)315–323323
常用英文缩写大全(全)
企业各职位英文缩写： GM(General Manager)总经理 VP(Vice President)副总裁 FVP(First Vice President)第一副总裁 AVP(Assistant Vice President)副总裁助理 CEO(Chief Executive Officer)首席执行官，类似总经理、总裁，是企业的法人代表。 COO(Chief Operations Officer)首席运营官，类似常务总经理 CFO(Chief Financial Officer)首席财务官，类似财务总经理 CIO(Chief Information Officer)首席信息官，主管企业信息的收集和发布CTO(Chief technology officer)首席技术官类似总工程师 HRD(Human Resource Director)人力资源总监 OD(Operations Director)运营总监 MD(Marketing Director)市场总监 OM(Operations Manager)运作经理 PM(Production Manager)生产经理 (Product Manager)产品经理 其他： CAO: Art 艺术总监 CBO: Business 商务总监 CCO: Content 内容总监 CDO: Development 开发总监 CGO: Gonverment 政府关系 CHO: Human resource 人事总监 CJO: Jet 把营运指标都加一个或多个零使公司市值像火箭般上升的人 CKO: Knowledge 知识总监 CLO: Labour 工会主席 CMO: Marketing 市场总监 CNO: Negotiation 首席谈判代表CPO: Public relation 公关总监 CQO: Quality control 质控总监 CRO: Research 研究总监 CSO: Sales 销售总监 CUO: User 客户总监 CVO: Valuation 评估总监 CWO: Women 妇联主席 CXO: 什么都可以管的不管部部长 CYO: Yes 什么都点头的老好人 CZO: 现在排最后，等待接班的太子 常用聊天英语缩写
网络中常用简称(在网络中常用的一些英文缩写及解释)
DARPA ：国防高级研究计划局 ARPARNET(Internet) ：阿帕网 ICCC ：国际计算机通信会议 CCITT ：国际电报电话咨询委员会 SNA ：系统网络体系结构(IBM) DNA ：数字网络体系结构(DEC) CSMA/CD ：载波监听多路访问/冲突检测(Xerox) NGI ：下一代INTERNET Internet2 ：第二代INTERNET TCP/IP SNA SPX/IPX AppleT alk ：网络协议 NII ：国家信息基础设施(信息高速公路) GII ：全球信息基础设施 MIPS ：PC的处理能力 Petabit ：10^15BIT/S Cu芯片: ：铜 OC48 ：光缆通信 SDH ：同步数字复用 WDH ：波分复用 ADSL ：不对称数字用户服务线 HFE/HFC：结构和Cable-modem 机顶盒 PCS ：便携式智能终端 CODEC ：编码解码器 ASK(amplitude shift keying) ：幅移键控法 FSK(frequency shift keying) ：频移键控法 PSK(phase shift keying) ：相移键控法 NRZ (Non return to zero) ：不归零制 PCM(pulse code modulation) ：脉冲代码调制nonlinear encoding ：非线性编程 FDM ：频分多路复用 TDM ：时分多路复用 STDM ：统计时分多路复用 DS0 ：64kb/s DS1 ：24DS0 DS1C ：48DS0 DS2 ：96DS0 DS3 ：762DS0 DS4 ：4032DS0 CSU(channel service unit) ：信道服务部件SONET/SDH ：同步光纤网络接口 LRC ：纵向冗余校验 CRC ：循环冗余校验 ARQ ：自动重发请求 ACK ：确认 NAK ：不确认
environment
environment, circumstances, conditions, surroundings 四个“环境” 为便于讨论，我把这四个词分为两组: environment与surroundings一组, conditions与cirsumstances一组。 surroundings 偏重于生活、居住的周围环境， environment则指对人的成长、情感、观念、伦理、道德、品行等产生影响的环境。 优美的周边环境 beautiful surroundings； 幸福的家庭环境：happy home environment； 遗传和环境；发展与环境，其中的环境只能用 environment。 破坏环境，保护环境中的环境当然也是environment。 这词的使用范围比sorroundings宽泛得多，延伸到人类活动的各种领域，如political/economic/cultural/demographic/natural/social/technological /legal/macroeconomic/microeconomic marketing/investment/language/learning/Chinese speaking/bilingual/multilingual/operating/global/international environment etc. Conditions 虽有"环境"的含义，不过更接近汉语“条件”——泛指改变、限制性因素，也指影响生活质量的种种因素。 circumstances则相当于“形势、情况”，往往指人力无法控制、驾驭的事件和事态的总和， weather/working/living/housing/production/natural/financial conditions, 其中有些条件人们可以创造、改变，但人们无法改变、创造circumstances。 Don't judge the crime until you know the circumstances. 指时间、地点、条件、情况等细节，不能用conditions替换。circumstances 还有一层意思，便是境遇、财力、经济状况，如经济宽余、生活安 逸 (in good/easy/comfortable/flourishing circumstances)，经济拮据、境遇不佳 (in bad/reduced/distressed/straitened circumstances)。两词有时也可通用，如 under present conditions/circumstances; national conditions/circumstances （国情）。 在习语中,词的搭配是固定的，不可互换，如in/under the circumstances, in/under no circumstances。中国政府在核武器问题上有句名言，不可不学：Time and again the Chinese government has solemnly declared thatat no time and under no circumstances will it be the first to use nuclear weapons。
environmental slogan 英文环保标语
Environmental Slogans 英文环保标语 One tree can make a million matches. One match can destroy a million trees. A drop of water is worth more than a sack of gold to a thirsty man Hug a tree, they have less issues than people Save water, it will save you later! Cu t a Tree, Cut a Tree and there’ll be no more left to see. Less pollution is the best solution Don’t let the water run in the sink, our life’s on the brink! Modern technology owes ecology an apology. Cool kids help a warm planet Let’s go green to get our gl obe clean Trees don’t grow on money either Get into the Green Scene Put a stop to the drop It’s the only Earth we got Want to hug a tree with me? When you refuse to reuse it’s our Earth you abuse Join the race to make the world a better place Give a Hoot, Don’t Pollute Water, water everywhere but not a drop to drink Don’t waste it, just taste it! When you conserve water, you conserve life! Save water! Save Life! Pollution isn’t cool, so don’t be a fool!
网路聊天常用缩略语和中文意思
招呼篇 GTSY：Glad To See You高兴认识你 PMJI：Pardon My Jumping In ＝PMFJI：Pardon Me For Jumping In 败势，加入你们的谈话 WB：Welcome Back 欢迎回来 LTNS：Long Time No See 好久不见 笑篇 BEG：Big Evil Grin （非常）邪恶的笑 C＆G：Chuckle And Grin 喀喀笑 GMBO：Giggling My Butt Off 笑掉我的屁屁 BWL：Bursting With Laughter 笑掉不行 CSG：Chuckle Snicker Grin 嘿嘿窃笑 KMA：Kiss My A$$ ＝MKB：Kiss My Butt 亲我的屁屁 LMAO：Laughing My A$$ Of ＝LMBO：Laughing My Butt Off ＝LMHO：Laughing My Head Off 笑死我了 LOL：Laughing Out Loud 放声笑 LSHMBB：Laughing So Hard My Belly Is Bouncing ＝LSHMBH：Laughing So Hard My Belly Hurts 笑到我肚子痛 告知篇 AFK：Away From Keyboard 离开键盘 BBL：Be Back Later ＝BBS：Be Back Soon ＝BRB：Be Right Back 稍待回来 CNP：Continue In Next Post 请看下一个留言 FYI：For Your Information 只给你知道 OIC：Oh，I See 喔，瞭 PS：Post Script 附注 QSL：Reply 回答 RTF：Read The FAQ 请看常见问题 AKA：Also Known As 又名为 FAQ：Frequently Asked Question 最常被问的问题 IC：I See 瞭 IGP：I Gotta Pee 我要去尿尿 POOF：I Have Left Chat 我已经离开聊天室啰 PM：Private Massage 私下寄消息。在聊天室常见的功能，你可以单独对有兴趣的人私下聊
环境类--雅思范文Environmental-problems
环境类--雅思范文 1. Environmental problems are too big for individual countries and individual people to address. We have reached the stage where the only way to protect the environment is to address it at an international level. To what extent do you agree or disagree? Nowadays, environmental problem has been the focus of a debate. Among these related problems, the issue of international efforts in combating environmental pollution is an extremely acute one. It is firmly believed that the benefits of large scale groups have remarkable impact on our society, especially on environment and animals aspects. First and foremost, environmental pollution is a problem that beyond national borders. This is because the destructive effects that it brought cannot be solved without the co-operation of all the countries in the world. A case in point is the occurrence of extreme weather condition, like La Nina in terms of heavy flood and drought; in addition to, global warming, acid rain that happen in many parts of the world. Due to its chronic and perpetual environment effect, it is necessary for the countries on the earth to form an association and join hands to protect our land from further environment deterioration. Another reason is that it is urgent to set up international alliance to prevent the shrinking space of animals' habitat. It is due to the fact that, local ecosystem has gradually been destroyed all over the world. For instance, Mountain Gorilla has loss its natural habitat to human beings, for being continually developing housing estate deep into the forest. Thus, the breaking down of ecosystem has pushed species closer to the brink of extinction. Hence, it is cleared that the prevention of declining the numbers of rare animals need the joint efforts from many administrative agencies in the world. In conclusion, I totally agree with the idea that international collaboration and cooperation in tackling environmental pollution is positively affects the sustainable development on earth. It is expected that environmental preservation can be greatly enhanced through cultivating environmental awareness around the people in every countries in the foreseeable future.
Environment 类
Environment 类 .NET Framework 4.5 其他版本 1（共 1）对本文的评价是有帮助 - 评价此主题 提供有关当前环境和平台的信息以及操作它们的方法。此类不能被继承。继承层次结构 System.Object System.Environment 命名空间：System 程序集： mscorlib（在 mscorlib.dll 中） 语法 C# C++ F#
VB 复制 [ComVisibleAttribute(true )] public static class Environment Environment 类型公开以下成员。 属性 名称 说明 CommandLine 获取该进程的命令行。 CurrentDirectory 获取或设置当前工作目录的完全限定路径。 CurrentManagedThreadId 获取当前托管线程的唯一标识符。 ExitCode 获取或设置进程的退出代码。 HasShutdownStarted 获取一个值，该值指示当前的应用程序域是否正在卸载或者公共语言运行时 (CLR) 是否正在关闭。 Is64BitOperatingSystem 确定当前操作系统是否为 64 位操作系统。 Is64BitProcess 确定当前进程是否为 64 位进程。 MachineName 获取此本地计算机的 NetBIOS 名称。 NewLine 获取为此环境定义的换行字符串。 OSVersion 获取包含当前平台标识符和版本号的 OperatingSystem 对象。 ProcessorCount 获取当前计算机上的处理器数。
英文网络聊天口语中非正式用语中的缩写和简写-推荐下载
duno=don't know u=you ur=your kinda=kind of sorta=sort of 2=two或to 4=for shoulda=should have congrat=congratulation thx=thanks X'mas=Christmas wat=what biz=business ad=advertisement ft.=featuring abt=about pls=please rgds=regards ---问好--- 1,hiho=hola=yo=hi=hey=hellow=你好，大家好 2,wuz up=sup=what's up=(原意：怎么样你？/有什么事儿嘛？)也可作为问好用(当然是比较熟的两个人之间的问候)，回答时有事说事，没事用"nothing/nothin much/not much/nm等回答就可以。 ---再见--- 1,cya=cu=see ya=see you=再见 2,laterz=later=cya later=see ya later=see you later=再见 3,gn=gn8=gnight=good night=晚安 4,nn=nite=晚安 说明：一般第一个人常说gnight/gn8,然后第二个人用nite,后面的用nn什么的都可以了。不要问我为什么，约定俗成而已。 ---惊叹赞扬--- 1,OMG=oh my god=我的天；**！ 2,OMFG=oh my f ucking god=我的老天；**靠； 3,wtf=what the f uck=怎么会事！？；*！； 4,n1=nice 1=nice one=漂亮 5, pwnz=ownz=牛比！(例句：pwnz demo!;lefuzee ownz all the others!) 6,rullz=强！(例句：lefuzee rullz!;you guyz rull!!!) 7,you rock!=你牛比！(口语中常用，irc中偶尔能看到。) ---笑--- 1,lol=laughing out loud /laugh out loud=大笑 2,lmao=laughing my ass off=笑的屁股尿流 3,rofl=roll on floor laughing=笑翻天了 排序:hehe 法律术语：Environment protection 环境保 护 1.An act that is destructive to the environment may be criminalized by statute. 破坏环境之行为可以被法律规定为犯罪。 2.Discharge pipes directly take pollutants away from the plant into the river. 排泄管道直接将污染物从工厂排入河流。 3.Environmental impact reports are required under many circumstances by federal and state law. 根据联邦和州的法律规定，在许多情况下都要求提供环境影响报告书。 4.Environmental law heavily intertwined with administrative law. 环保法与行政法紧密联系在一起。 5.Environmental problems directly affect the quality of people's lives. 环境问题直接影响人们的生活质量。 6.In 1970, a federal agency was created to coordinate governmental action to protect environment. 1970年，成立了一个联邦机构以协调政府的环保行为。 7.Most environmental litigation involves disputes with governmental agencies. 许多环保诉讼都涉及与政府机构的争端。 27. Some people believe that these environmental problems are too big for individuals to deal with, while others think that individuals should take some action. Discuss both views and give your opinions. Nowadays, there is a highly controversial issue relates to whether the environmental problems cannot be tackled through each individual, while others disagree about this. Therefore, both sides of this argument will be analyzed before a reasoned conclusion is found. It is felt by many that the benefits of international cooperation and coordination in combating environmental degradation are considerably outweighed its disadvantages. This is because environmental problem is beyond national broader and is seriously required the joints efforts from the countries from all over the world. As well as this, disastrous and perpetually environmental deterioration has led to extreme climate change globally. A case in point is the extreme weather condition like La Nina which has caused heavy flood or droughts; in addition to, the formation of global warming and acid rain in many parts of the world. Consequently, without the efforts from the governments, there is no way to solve the environmental deterioration. However, it is often argued that the works of individual is important in environmental preservation. It is proved that cars and industries are the main culprits in producing air contamination. For instance, along with being producing noise and water pollutions, vehicles and factories also generate destructive gases like carbon dioxide and carbon monoxide. As a result of unsubstantial use of resources, human has contributed to the chronic and accumulative effect of environmental deterioration. Hence, it is urgently to cultivate environmental awareness among individual people in order to become environmental friendly responsible. In conclusion, it is believed that both arguments have their merits. On balance, however, it is felt that environmental issue should be address at international level, as its benefits can clearly be seen. This is because without a doubt, international coordination and cooperation are necessary in order to alleviate the tedious environmental problems. 与外国人聊天常用缩略词 刚上线时一般的使用:----------------------------- 1. Hi 嗨 2. Hey 嘿 3. Yo 喂 4. WOW 哇 5. ICQ 我找你. I seek you. 6. TNS 好久不见. Long time no see. 7. VG 很好 Very good. 8. yep 是 <俚> yes. 9. yup 是 <俚> yes. 10. yeah 是 = yes. 11. RYOK 你好吧? Are you ok? 12. YR 对,是的. yeah,right. 中间有事离开一会儿:----------------------------- 13. bbiam 我很快回来 Be back in a minuta. 14. hang on 等一下. 15. bll 过一会儿回来. Be back late. 16. BRB 很快回来. Be right back. 17. RSN 马上 Real soon now. 19. afk 暂时离开(键盘) away from keyboard. 20. bak 回(键盘前)来了. back at keyboard. 21. BBIAB 马上回来. be back in a bit. 告诉对方欲下线:---------------------------- 22. TAFN 到此为止. That's all for now. 23. GTGB 得走了.再见. Got to go,Bye. 24. SRI 对不起. Sorry. 25. Gotta go 我得走了. Gotta go=have to go=I have to go. 告别:---------------------------------------------- 26. Bye 再见. 27. CU 再见. See you. 28. CU2 再见. See you too. 29. CUL 下次再会. See you later. 30. CUA 再会. See you again. 31. HTH 睡觉去了. Hit the hay (hay <俚> 床) 33. See ya. 再见. See ya = See you (ya 表示 you 或 young adult) 34. AMF 再会,我的朋友. Adios my friend. 网络聊天中常见英语缩写词 下面列举一些典型的网络英文潮语。 btw(by the way)：这个大多数人都会用，就是“顺便再说一句”的意思。 g2g(got to go)：要走了。原句是I've got to go。 ttyl(talk to you later)：下次再说。 brb(be right back)：很快回来。也就是I'll be right back 或I'm gonna be right back的简写。 jk(just kidding)：开玩笑，别当真。 omg(oh my god)：我的天啊！有时为了表达更强烈的情感，有人会打：OMGGGGGGG! lol(laugh out loud)：大声地笑。这个缩写已经快被用烂了。 Imao(laughing my arse/ass off)：笑死我了。遇到真正搞笑的事，可以这么说，不过有点粗俗。 rofl(rolling on the floor laughing)：笑到摔到地上。 roflmao(rolling on the floor laughing my ass of)：前两个的结合版，也就是超级搞笑的意思。 sth(something)：某事某物。 nth(nothing)：什么也没有。 plz(please)：请。please 字尾是z 音，所以按照读音缩写为plz。 thx(thanks)：谢谢。按照发音来看，thanks字尾的ks可以用字母X代替。 idk(I don't know)：我不知道。 imho, imo(in my humble opinion, in my opinion)：在我看来，常见于论坛。 以上这些网络潮语当然不是叫大家不顾场合，不看对象地乱用。写信给校长，总不能以"Yo! Wassup?" 开头问好吧。运用你的智慧，尽情享用这些最流行的英文潮语吧。 ASAP：As soon as possible尽快 BF：Boyfriend男朋友 BTW：By the way随便说一下 BBL：Be back later稍后回来 The Environmental Problems ------- Made by Tobias The brief introduction of myself When referring to this topic, what do you think of? Maybe you sign that we are facing so many environmental problems? Yes, absolutely right. But how much do you know about that? And there is a serious issue that it’s never enough just to know that, but why, why we have such problems and how should we do to protect our living garden, the earth? How much do you know about the environmental problems? Acid Rain（酸雨）Air Pollution Chemical Waste（化学废料）Contamination of Marine Habitats（海洋生物污染）Deforestation Diseases Extinction of Species（品种灭绝）Global Climate Change Overpopulation Water Quality In your perception, which is the most serious one that threatens our life? 网络英语聊天中常用缩写短语（很好很强大！！！）来源：郭年顺的日志 问好 hiho = hola = yo = hi = hey = hellow 你好，大家好 wuz up = sup = S’up What's up?原意:怎么样你?有什么事儿嘛?也可作为问好用(熟人之间候) 再见 cya = cu =see ya see you 再见 laterz = later = cya later = see ya later see you later 再见 gn = gn8 = gnight good night 晚安 nn = nite 晚安 说明：一般第一个人常说gnight/gn8,然后第二个人用nite,后面的用nn什么的都可以了。不要问我为什么，约定俗成而已。 惊叹赞扬 OMG oh my god 我的天 OMFG oh my f ucking god = 我的老天；**靠 wtf what the f uck = 怎么会事！？；我日！ n1 = nice 1 nice one 漂亮 pwnz = ownz 牛比！(例句：pwnz demo!;lefuzee ownz all the others!) rullz 强！(例句：lefuzee rullz!;you guyz rull!!!) you rock! 你牛比！(口语中常用，irc中偶尔能看到。) lol laughing out loud / laugh out loud 很好笑.因为lol像笑脸，和我们常用的^-^一样 lmao laughing my ass off 笑的屁股尿流 rofl roll on floor laughing 笑翻天了 其他简写 FU fuck you *你；滚 STFU Shut the fuck up! ***给我闭嘴！ k=ok=okay=okie 好的，恩 gimme give me 给我 em them 他们的宾格 thx thanks 谢谢 ty thank you 原本用的不多，不过现在又开始兴起来了 happy bday = happy b-day happy birthday! 生日快乐 dunno dont know 不知道 kinda a little bit 有点(例句：The game is kinda hard for me.i kinda think i should get it d one as soon as possible.) cmon = c'mon come on 加油/别吹了/快点/起来（这个词意思太多了，不赘述了） hax = hack = cheat 作弊，说谎(很地道时尚的词，老外用的比较多) 开场白：Morning, everyone. Today I will share something about the environment with you. 1、Look at this picture. Does it remind you of anything? You see that river, gently flowing by; you notice the leaves, rusting with the wind; you hear the birds; you hear the frogs; in the distance, you hear a cow, you feel the grass, the mud gives a little bit on the river bank. It‘s quiet, it‘s peaceful. And all of a sudden, it’s a great shift inside you, and it’s like taking a deep breath and going, (深吸一口气)oh, yeah, I almost forgot about this. 2、This is a picture of the earth from space that any of us ever saw; it was taken on Christmas Eve, 1968, during the Apollo8 mission. We can see the earth within relatively comfortable boundaries. But we are filling up that thin shell of atmosphere with pollution. 3、This is the central park of Bit. I took it by myself on November, 1, 2013. On the picture, we see the whole park is covered with heavily thick smog. It was right on that evening, I had been playing the badminton outside with my friends for three solid hours. Thank god, I’m still alive. Do you feel a little frustrated just the same as me? Yes, we are always missing something only when we do not own it anymore. 4、It comes to me another well-known wisdom that what gets us into trouble is not what we don’t know; it’s what we know for sure that just ain’t so. ----Mark Twain This is actually an important point believe it or not, because there is an assumption that a lot of people have in their mind right now about the air pollution. They just think so, the assumption sounds like this, the earth is so big, we can’t possibly have any lasting harmful impact on the earth environment. Maybe that was true at one time, but it’s not anymore. And one of the reasons it is not true anymo re is that the most vulnerable part of the earth ecological system is the atmosphere. Vulnerable, because it’s so thin. That is to say, anything what we had done can truly make a big difference to the environment. This is meant to be the end but we won’t end it here. 5、It’s so lucky for me that I toke this picture at the right same spot after I finished the preparation for today’s presentation. You see the blue sky; and the central park is filled up with warm sunshine and fresh air. Sometimes you feel some soft wind from nowhere. （放出第二张图片）Is it not beautiful? 结束语：thank you for listening.法律术语：Environmentprotection环境保护.doc
environmental problems are too big for individuals to deal with
与外国人聊天常用缩略词
网络聊天中常见英语缩写词
Top10 Environmental_Problems
网络英语聊天中常用缩写短语
environment,环境,英语演讲