Comparative Study On Measuring Environmental Efficiency

Currently, the environmental problem becomes a major obstacle to sustainabledevelopment of the world. How to solve environmental problems and how to preventfurther deterioration of ecological environment have already attracted great attentionfrom many global experts, scholars and government. Therefore, study and improvementon the measurement of environmental efficiency will push forward the development inthe subject and provide support for the implementation of binding emission reductiontargets in China’s “Twelfth Five Year Plan” period.Environmental efficiency has many definitions by some domestic and foreignresearchers, these definitions are divided into two kinds. The first kind of definitionadopt the ratio of environmental load to economic gross index to represent theenvironment efficiency. The second kind of definition takes the environmental pollutionas undesirable output into consideration, on the basis, environmental efficiency ismeasured in two ways. One is an economic value-to-environmental pollution ratio inthe remaining inputs, the ratio is the reciprocal of emission intensity. The other isoutput-to-input ratio, which means environmental total factor productivity orenvironmental comprehensive efficiency.The paper explore the environmental efficiency based on the second kinds ofdefinition, and comparatively study on these measurement methods of emissionintensity and environmental comprehensive efficiency, specifically from the researchmethods of pollution emission intensity, measure methods of environment staticefficiency (including the parameter and non parameter method) and of environmentdynamic efficiency. The paper analyses the merits and adaptability of these methods, amethod is improved and four new combined models are presented in the process ofcomparison. The author expects to gain the more optimal and meaningful methods.Based on these, taking the123countries of world and China as examples, the paperemploys the above mentioned optimal methods to measure their environment efficiency,and provide the theories and methods basis for the World and China. The main researchwork are as follows:First, this paper briefly reviews the theories of efficiency and defines the keyconcept: environmental efficiency (EE). The existing literatures on measuring EE focuson two indicators: EI and ECE. The calculation of the two indicators needs the indicator of pollution emission. So the author selects the social willingness to pay as weights toget the weighted emissions in view of many literatures, which not only considers dangerin different contaminants, but also provides more valuable data sources for measuringEE.Second, based on comparative analysis of structural decomposition analysis (SDA)and index decomposition analysis (IDA), the author has improved existing Laspeyresdecomposition of EI (a non-complete decomposition method) to a completedecomposition method. The author also finds that application of the SDA model islimited because the SDA model relies on the input-output tables; the IDA model has awider application due to easy availability of data.Third, this paper first presents combination method of minimum distance to thestrong efficiency frontier analysis (mSBM) and undesirable output model in summingup non-parametric data envelopment analysis (DEA), and compares with the other twofrequently-used EE measure models: directional distance function (DDF) and slackbased measure (SBM). The results show the calculated values by these three methodshave a significant rank consistency. Since the calculation of SBM and mSBM modeltakes "crowd" and "slack" into consideration, moreover DDF is a radial model and thecalculated efficiency is weakly effective, so the mSBM and SBM models are superior toDDF model. In comparison between SBM and mSBM model, the average improvementratio of SBM model is maximum, but of mSBM model is minimum, the effects ofimprovement are the same which are from ineffective to effective. Consequently,mSBM model achieves effective with less effort which is more suitable forpolicy-making.Fourth, in comparison of stochastic frontier analysis (SFA) and DEA, the resultsshow the calculated values by the two methods are significantly different, but have asignificant rank consistency. The DEA has the characteristics of diverse models andconvenience in handling undesirable output, so it is the preferred method to measureenvironmental efficiency.Fifth, the paper first presents three combined ML indexes: combination of SBMand meta-production (SBMGML), combination of mSBM and ML index (mSBMML),combination of mSBM and sequential ML index (mSBMSML). On this basis, this papercomparatively analyses the six non-metafrontier models (DDFML、 DDFSML、SBMML、 SBMSML、 mSBMML、 mSBMSML), the two metafrontier models(DDFGML and SBMGML). There are any model which can avoid the defect of technical regress and calculate the technical gap at present, so we choose the modelaccording to the following rules. if calculating the general ML index, the mSBMMLmodel is the best; if avoiding the defect of technical regress, the SBMSML model istemporary more advantageous; if taking the technical gap into account, the SBMGML ismore suitable.Finally, the author compares the two indexes: EI and ECE. The results shows thatthe two indicators show the negative correlation, also show different. From the spatialstatistics, EI has no spatial correlation, while ECE has a significant spatial correlation.Overall, there are both correlation and different between the two indicators which arestill the important indicators to measure environmental efficiency.