A Study On The Efficiency Of Urban Domestic Waste Charge System

Municipal Solid Waste(MSW) has become a big threat for the society and the ecosystem in China. Even though MSW is increasing at rates around 8-10% per year, its management is not as developed as needed. Efficient Refuse Charge, as an important Environmental Regulation Policy, is essential to solve the problem.This research aims at evaluating the efficency of Refuse Charge System (RCS) of the nation's major cities through the establishment of an appropriate DEA input-output model, and through group comparison of various geographical regions, some specific recommendations were given to improve the RCS'efficiency. In this study, a one-stage simultaneous stochastic frontier analysis model and a heteroscedastic, non-monotonic stochastic frontier analysis model were given to analysis the impact of environmental variables on the RCS's inefficiency. Environment variable for different observation object exists heteroscedasticity, the ability to accommodate non-montonic efficiency effects is important for the model seeking to understand the relationship between efficiency and the exogenous factors, which can be controlled to some extent to do the optimal decision making, aimed at improving the overall efficiency of RCS.The main research works and achievements in this study are shown as follows:(1) General overview of the theoretical basis, design principles of China's refuse charge policy. At the some time analyzing the current status of implementation of the garbage charging mode and the existing problems, in order to explore the directions of RCS reform, and to make the specific study focus.(2) As to the widely used fixed charging system, we use DEA approach to evaluate the efficiency of its implementation, which take 14 cities of China's provincial capital cities and selected cities with independent planning as the decision-making units, using the data of the year 2006. And at the second step use the Tobit method to study the impact of environmental variables on the performance of RCS. The results show that in all 14 cities, Beijing has the worst performance of RCS, its pure technical efficiency score is only 0.510, in order to achieve a pure technical efficient level, we first need to improve their amount of garbage fees.(3) After cluster analysis normalizing output indicators into a single one, stochastic frontier analysis was used to evaluation the specific cities'charging efficiency and the impact of environmental variables on the un-efficiency of RCS, these will be compare with the DEA results in order to confirm the conclusions'scientificity and explore the remaining problems.(4) Through heteroscedasticity, non-monotonic stochastic frontier model, we find that the optimal performance of environment variable on the Refuse Charge System's efficiency are as follows: the population density of 1022 persons per square kilometer, the proportion of the urban population reached 46.69 percent, the per capita disposable income of 19,978 yuan per person, the regional per capita GDP of 38,578 yuan per person, the garbage fees will increase the performance of the most significant.This study not only able to estimate the best input level under an efficient RCS, but also can find the optimal level of environment variables. However, if future studies can consider the impact of resource indicators, some more comprehensive and valuable analysis results will be achieved.