| Economic development has made a significant contribution for the progress of the human society, but the blind pursuit of high economic growth brought great pressure on the natural environment which related to the survival of human life. Whether the environmental pollution could be controlled is vital for sustainability of economic efficiency, economists have been aware of considering environmental factors into account. Data Envelopment Analysis (DEA) is used commonly for measuring economic efficiency. The method was initially used to assess the efficiency of input-output of micro-production unit. However, some economists apply the method to assess the efficiency of macroeconomic unit. Most results have proved that the method is feasible.For the traditional DEA model, the evaluation principle is more output with a unit of input, or less input with a unit of output. But in the process of production, not only do we get desire outputs but also undesired outputs such as environmental pollution with the input of labor, capital and other production elements. When constructing model to evaluate the economic efficiency, people always want to expand output or compress input with less undesired output as much as possible. Therefore, in theory, we must extend the traditional DEA model to a new DEA model which includes undesired output.Surender Kumar (2006) has examined conventionally and environmentally sensitive total factor productivity (TFP) in 41 developed and developing countries during 1971-1992. The study used directional distance function to derive Malmquist-Luenberger (ML) productivity index. The index could decompose the TFP into technical process and efficient change. They found that TFP index was not different when CO2 was freely disposable. However, the technical process and the efficiency which consist of the TFP had changed. The paper also studied the impact of openness on conventionally and environmentally sensitive measures of productivity. Domestic studies to evaluate the performance of economic growth rarely consider environmental factors into the input-output analysis framework. Bing Wang, Yanrui Wu and Pengfei Yan (2008)used the method of Malmquist-Luenberger index to measure TFP and its components in 17 APEC countries over the period of 1980 to 2004 under the condition of considering the emissions of CO2 . The paper has estimated and compared three type productivity indices according to three scenarios. Then it empirically examined the cause of productivity changes with environmental regulation. The main conclusions were, with environmental regulations, TFP growth for 17 APEC economies on average was slightly higher than that of without regulation, and the reason was technical progress. GDP per capita, industrialization, technical in efficiency, capital labor ratio, energy use per capita and the openness had a significant and positive effect on the productivity index with environmental regulations. The environmental factor in the two studies was only CO2, while environmental pollutions such as waste water, solid waste should be also included. Angang Hu, Jinghai Zheng (2008) re-ranked technical efficiency of Chinese provinces with directional distance function approach. The paper took account of environmental factors while implementing the DEA methodology. When measuring Chinese economic growth, the existing papers had not considered other factors which could affect the efficiency of Chinese economic growth.As for China the main pollutions are industrial water, waste gal, solid waste and emissions of sulfur and nitrogen compounds. For a vast territory, the major environmental pollutants in various regions are quite different. If we only consider one or two pollutants when measuring environment efficiency, the result will be distorted. Therefore, the paper adopts a principal of component analysis about a variety of environmental pollutants for each province every year with considering the environmental pollution. Then we construct pollution integrated variable with the major pollutants of each year. In this way, the results are more comparable.The study incorporates environmental undesired outputs into the model to measure technical efficiency, and uses the software of On Front 2.0 from Fare to calculate the technical efficiency of each DMU under both the case of considering environmental undesired outputs and not. We find that the number of DMUS with technical efficiency greatly increases after considering environmental undesired outputs. And we could see a lot of DMUS which have never appeared on the frontier of production. Judging from the time series, the number of occurrences of the unit has changed greatly, and even some new units appear on the frontier after considering undesired outputs such as Shandong and Hainan, appear on the frontier 19 times during the 20 years. In addition, Hebei, Liaoning, Zhejiang, Shandong, Henan, Shaanxi, Qinghai and Xinjiang, are the new members on the frontier which appear after considering undesired outputs. The existence of non-desired environmental output does affect the effectiveness of measuring technical efficiency.Based on measuring technical efficiency, the study also measures the productivity index of each DMU in both the cases of considering environmental factors and not. We also make a contrastive study. Without considering environmental constraints on productivity, the average growth rate is 3.2%, and the average productivity growth rate 8.6% constrained by environmental factors. The productivity growth improved greatly considering the environmental undesired outputs. The existence of environmental undesired outputs does affect the accuracy of measuring productivity index. We divide productivity index into efficiency change and technical progress. The DMUS are almost learners who have promoted the boundary of the productive frontier. But the innovators are monopolized by relatively developed provinces. Under the condition considering the environmental undesired outputs, the efficiency of the units whose value of the efficiency change is greater than 1 aggravates. And the units are out of the ranks of learners. Environmental pollution has restricted the improvement of technical efficiency of these units. Therefore, considering the environmental undesired outputs, innovators increase. The new DMUS has realized the importance of environmental protection while promoting economic growth. These DMUS promote technological innovation constrained by environmental factors as promoters.We had identified the factors affecting productivity growth through establishing fixed effects of variable intercept model. We found that the environmental performance index and per capita GDP had the quadratic inverted U-curve relationship, and the productivity growth will decline when the value of per capital GDP reaches the maximum, which indicates that productivity growth has a convergence trend. The coefficient of the proportion of industrial value is negative, while the square of its coefficient is positive, indicating a U-curve relationship exists between the two variables. When the proportion of industry surpasses the maximum level, productivity growth will accelerate. The relationship between environmental performance index and the capital - labor ratio is not statistically remarkably.The relation between Environmental Performance Index and foreign investment is positive. Foreign investment has contributed to regional economic growth in China recently. Environmental performance index and fixed capital investment have a negative relation, indicating that during the process of economic development, the investment should be adaptive with other economic resources, such as human capital. Only in this way can we promote productivity effectively. Environmental performance index and total energy consumption have positive relation. The environmental pollution caused by consuming energy does not restrict China's economic growth. On the contrary, the energy promotes rapidly economic development.The relationship between environmental Performance Index and per capita consumption was not significant. Whether growth of consumption can promote the growth of productivity or not, and how consumption is closely related to the actual level of economic development, which are different issue to decide. The relationship between Environmental Performance Index and the investment for environmental pollution controlling is not statistically remarkably. To increase investment in controlling environmental pollution, it provides sufficient investment for environmental developing, on the other hand, it influence investment for productive resources, so reducing the desired outputs. Therefore, for a DMU, the contribution of investment in controlling environmental pollution depends on the actual situation of its own. Nothing but putting a variety of factors together into account can we obtain a reasonable explanation.We also established a fixed effect variable coefficient model to study how these various factors affect Environmental Performance Index of DMUs in China's economic system, and analyzed the causations. Since the actual situation of economic development in each DMU is different, the style and degree of influence are varied. But they display some regularity in aspect of division of economic geography. As for developed provinces, the relationship between the factors and economic performance index is mostly positive. While in undeveloped areas, the relation is mostly negative. In economically developed provinces, environmental performance index and per capita GDP, the proportion of GDP, industrial added value and capital - labor ratio were tested to have inverted U-curve relationship. When the index surpasses the level on the inflection point, productivity growth will slow down, which explains productivity growth has convergence trend. In economically developed provinces, per capita consumption, environmental pollution control investment, foreign investment, fixed capital investment and the total energy consumption change along the same direction with environmental performance index. In the economically underdeveloped provinces, the situation is contrary; their own inherent defect of economic development is the main cause of this phenomenon.In summary, taken environmental factors into evaluating economic growth is reasonable and necessary. This paper has identified the main factors affecting productivity growth. The geographical location of the DMU, its natural resources, and human resource reserves, and other factors may impact on productivity growth. If these factors can be excluded one by one, the measurement of the growth rate must be mostly accurate which our future research topics are. |
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