In this paper we examine levels and trends in conventional and regulation on CO2 emissions sensitive productivity over the period 1995 to 2007. Firstly, we estimate and compare two type TFP index from regulations on CO2 emissions to no regulations over current levels and test the difference of TFP in two kinds of conditions. The major conclusions are as follows: Under co2 emissions restrictions, the eastern region has the highest TFP Growth rate while the western region has the lowest TFP growth rate .With accounting for convention, sensitive productivity growth for 28 regions on average is slightly higher than that of regulations on CO2, and efficiency change is the main source. Out of 28 regions, eight different regions shifted the frontier at least once. Econometric analysis indicates a number of variables that has important effects on e regulation on CO2 emissions sensitive measures of productivity, including variables relating GDP per capita, technical in efficiency, capital labor ratio, the energy intensity and openness. We find that these variables have different effects. In addition, policy implications are discussed.
Although total factor productivity is not a country's economic prosperity, living standards and the only measure of competitiveness, but it is the last 20 years, widely accepted measure (Lall et al.2002). In recent years, resource-saving and environment-friendly, sustainable social development issues have become hot topics of general interest, so a lot of research has been concerned about the environmental controls for the impact of conventional total factor productivity (Jaffeetal, 1995) . traditional method of measuring TFP take into account only the desired output, without considering the undesirable outputs,such as CO2 emissions. Therefore, traditional methods of measuring total factor productivity growth makes the productivity measure has gone wrong. Malmquist productivity index was first used by Caves et al. (1982) defined, post by e et al. (1997) and other scholars continue to improve, to a distance function to describe the non-parametric method. Malmquist index defined Shephard input distance function,including two orientation and output orientation.Among them, the output-oriented distance function for
input elements in the premise of not increasing production to achieve the maximum expansion ratio,input-oriented distance function seeks to reduce the output elements is not achieved under the premise of
the maximum contraction ratio of input. However, if there is undesirable output, Malmquist productivity index can not calculate total factor productivity. To solve this problem, Chung et al. (1997) on the
Malmquist productivity index modified and Malmquist productivity index is known as Malmquist-Luenberger productivity index, the measure of the new method considers the output of undesirable the impact of productivity . This method has been widely used in the industrial sector (Fare et al. 2001, regional (Hailu, al. 2001 ) and the State (Lindenberg, 2004 ; Domazlick and Weber, 2004 [9 ];Yoruk and Zaim, 2005 ; Kumar, 200911]; Bing, Wu Yanrui, etc., 2008 ). At present, the existing research related to this article, only Bing, Wu Yanrui et al (2008), and Bing Wang, Wu Yanrui et al (2008), APEC is the object, this paper attempts from the following three aspects of the existing literature to develop: (1)Using Malmquist-Luenberger productivity index measure and compare the different control of CO2 emissions in the two cases in 28 districts in total factor productivity growth in 1995-2007; (2) test under the control of carbon emissions in all the different TFP differences; (3) impact of carbon controls on total factor productivity growth, an empirical study of factors.
In the traditional measure of total factor productivity, due to neglect of Africa desired output of the production process, making the measurement results to bias. In this paper, Malmquis-Luenberger
productivity index measurement method and compared the carbon emission control and no control of carbon emissions under the two cases, 28 provinces and autonomous regions to the relevant data for
1995-2007 as the sample application serial DEA technology, the whole factor productivity growth and the empirical analysis of influencing factors.We found that, when control of the carbon emissions of total factor productivity is the average annual increase of 1.8%, the average technical efficiency increased by 12.4%, 9.4% average annual technological progress, but no control carbon emissions, the total factor productivity increased by an average ratio of carbon emissions per year more than 1.6 percentage points during the control, 0.2 percentage point increase technical efficiency,technological progress, less 0.5 percentage points. Therefore, in an average
sense, considering the carbon control, the increased level of technological progress.We also analyzed in two different cases, affect the total factor productivity growth factors. The results showed that the per capita GDP, technical inefficiency, capital labor ratio, the energy intensity of total factor productivity factors.
