"Economics" (quarterly) 2008 the third period

OF: Hu Angang, professor at Tsinghua University, Research Institute of Tsinghua University Dean of conditions; Zheng Jinghai, Department of Economics, University of Gothenburg; high Yuning, Department of Land Economy at Cambridge University; Zhang Ning, Chinese University of Hong Kong Department of Economics; Xu Hai, Zhejiang University College of Environment and Resources.

Abstract: In recent years, some productivity models have begun to consider the impact of environmental factors. Based on the provincial data of China, this paper uses the TFP model as the expression of the directional distance function to re-rank the "technical efficiency" indicators of the provincial productivity measurement in consideration of the environmental factors. Our experience shows that the model used in this paper not only takes into account the influence of environmental factors, but also inherits the systematic and structural framework of traditional productivity analysis technology, which has a relatively wide application compared with the popular method of calculating green GDP. prospect.

Keywords: technical efficiency, directional distance function, environmental protection

In this paper, the "technical efficiency" of China's 30 provinces and autonomous regions is re-ranked with the consideration of environmental factors, using the provincial data and the directional distance function productivity model. In recent years, distance function models (such as the DEA method) have been used by many authors to estimate the technical efficiency and total factor productivity growth of provincial production (Zheng and Hu, 2005; Zheng and Hu, 2006) The ranking of technical efficiencies given does not take into account the impact of environmental factors. In addition, according to the recently released World Bank data, China's green GDP time series data, the traditional TFP indicators under the traditional growth accounting framework can not accurately reflect the impact of environmental factors, while the use of provincial data and directional distance The function model has the following advantages:

First, many of the variables in the provincial cross-sectional data vary widely, so differences in growth patterns across the provinces and their potential for environmental impact are observed. The second is that the directional distance function model does not need the price data of pollution emission when calculating green TFP. Third, the directional distance function used in the measurement of technical efficiency standards, in the case of a given input to encourage the normal output to increase the direction of production front, while rewarding pollution to the front of the front to minimize the pollution reduction, which ratio Of the direct adoption of green GDP data through the Solow residual value method to estimate the green TFP more productive economics meaning. In recent years, the study on the influence of environmental factors on the measurement of productivity performance is gradually increasing, but there are not many domestic applications in this field. We have made a preliminary attempt to use CO2, COD, SO2, total wastewater discharge and total solid waste as an environmental indicator.

This paper first classifies the economic growth pattern of each province and city by the traditional growth accounting method. Secondly, we use standard DEA method to rank provincial technical efficiency without consideration of environmental factors, and try to find out the relationship between economic growth mode and technical efficiency rank. Finally, we use the directional distance function model to examine how the environmental factors affect the provincial technical efficiency rankings, and consider the relationship between the technical efficiency measures of environmental factors and economic growth patterns. In the first part, we introduce the research background through the work done by the World Bank on the basis of China's total economic data, and make a brief review of the literature on green GDP measurement. In the second part, , We do not consider the environmental factors, we do the growth accounting of the provincial data and the growth patterns of different regions are classified; the third part describes the environmental data and background information used in this paper; the fourth part introduces the directional distance function And the DEA method to achieve the technical efficiency of the estimation model; Part V of the model using different empirical estimates of the results of the analysis; Finally, we give some tentative conclusions in the sixth part.

Along with China's economic development, environmental factors for the impact of GDP has been more and more attention. In this paper, we use the total factor productivity model with the directional distance function as the expression, and the "technical efficiency" index in the productivity performance measurement of each region in China is analyzed under the circumstance factors.

From the estimation results, in the period of estimation, the eastern region considered the highest technical efficiency of environmental factors, followed by the central region, the western region the lowest. In the estimation of single environmental factors, the regional technical efficiency distribution shows that the technical efficiency is higher and the project area gap is often smaller, which indicates that the influence of environmental factors on technical efficiency is gradient, and the influence is small and easy to solve. (Such as SO2 and solid waste) in various regions of the technology, the investment gap is large, the technical efficiency (such as waste water) in various regions of the technology, the investment gap is small, the smaller the gap in technical efficiency; the other hand, the impact of large, difficult to solve projects, The gap is large. On the other hand, during the period of calculation, the central region continues to catch up with the eastern region, the technical efficiency level is improved, the gap is narrowed, and the technical efficiency level of the western region is declining and the gap with the eastern region is widening. This shows that after the implementation of the "Western Development" strategy, the western region, while growing rapidly, neglects the improvement of efficiency, and the growth pattern tends to be "extensive".

From the technical efficiency of the rankings, in considering and ignoring the environmental factors in the case of differences reflects the regional environmental factors on the impact of the strength of the output. In addition, considering the single environmental factor and considering the technical efficiency of the two environmental factors group is basically close to the rankings, while the technical efficiency rankings in the time dimension changes are generally much smaller than in different environmental factors (groups), the difference between environmental The influence of factors on the ranking of technical efficiency is relatively stable, and there are obvious biases between different environmental factors in different regions.

In addition to traditional high-tech efficiency areas, such as Shanghai, Jiangsu, including Liaoning, Anhui, Yunnan and other environmental factors in considering the various types of high-tech under the conditions of environmental factors, Efficiency regions, which also shows that, in the exclusion of environmental factors, can be more clearly understand the characteristics of regional productivity performance. At the same time, in the estimation of different environmental factors, there are some areas in considering the specific environmental factors (group) estimates, in the production frontier.

Three of the four combinations associated with solid waste in Hainan and Guizhou are at the frontier of production in SO2, indicating that productivity performance in a given region is directly related to the environmental characteristics of the region Which provides a way and tool for future productivity performance analysis.

Another important conclusion of this paper is that the regional efficiency of the consideration of environmental factors is closely related to the regional growth model. The closer the regional growth model is to the "intensive", the faster the technological efficiency progresses. The closer the regional growth model is close to the "extensive", the slower the progress of its technical efficiency. This conclusion has an important guiding role in guiding the choice of regional economic growth. In fact, in recent years, China's overall TFP growth in the context of slowing down, reversing the regional economy in general "extensive" growth model to improve regional technological efficiency progress, to maintain China's long-term sustainable growth is of great significance. Of course, further work is to quantify the impact of other factors that affect the efficiency of technological progress and the impact of regional growth model of the factors that contribute to regional economic growth to provide a more adequate policy analysis.