Previous studies have evaluated the investment efficiency of the government from a macro perspective, but few studies focus on specific projects with government investment. Therefore, this paper presents a method that combines data envelopment analysis and Tobit regression, which highlights the sources of funds, social benefits and influencing factors. It concludes that the overall efficiency of government investment projects (GIPs) is very high, but the excessive input and insufficient output are widespread and big improvement spaces exist; the public requirements rank first of all the influencing factors. This paper can provide references to guide the GIPs to gradually obtain better investment efficiencies.
Recently, synergistic monitoring of air pollution prevention and control in Jing-Jin-Ji area is coming up to an important issue in environment protection field under the circumstances of cooperation between Beijing, Tianjin and Hebei region. It is of great concern for government to maintain the effectiveness of monitoring effect so that the prevention and control of air pollution is guaranteed, further the air condition of Jing-Jin-Ji area would be improved. For the purpose of evaluating the synergistic monitoring effectiveness, a evaluation index system for air pollution prevention and control in Jing-Jin-Ji area should be established so as to conduct the evaluation process in a scientific and rational way. By analyzing the general principles of setting up an index system, we summarize six principles for the establishment which includes comprehensiveness, purpose, simplicity, independence, hierarchy and feasibility. On the basis of the principles mentioned above, we further break the evaluation problem into 4 targets and 23 indexes so that the index system is established. Through the index system we proposed, government and enterprises can effectively evaluate the synergistic monitoring effect of air pollution prevention and control in Jing-Jin-Ji area so that scholars and supervisors are capable to further study relative problems.
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