企业效率表现和中国环境政策-以造纸企业为例

Understanding relationship between environmental protection and economic development is crucial to form practical environmental policy. At micro level, implementation of environmental regulations often causes production mills adjustment of technology which might leads to change of productive efficiency and cost, which, in turn, determine effort level of mills and even local government in pollution control. Using a stochastic frontier production model and a set of survey data on 126 paper mills from six provinces of China, we measure the technical efficiency changes and analyze the determinants of efficiency. in particular, we examine impact of environmental policy on paper mills' efficiency, using an indicator of environmental policy-the levy ratio of COD. We also estimate a simultaneous-equation model in which the levy rate and emission are jointly determined. The results indicate that there have been efficiency improvements during 1999-2003, when enforcement of environmental regulations have been tightened. The impacts, nevertheless, are different for different types of mills. We also find the levy ratio, which is influenced by both the local social and economic conditions and the characters of paper mills, such as scale, has strong impact on the abatement of the pollutant-COD. Additionally, paper mills' technical efficiency has positive effect on the reduction of the emission intensity of the pollutant-COD. These results lead a set of implications pertinent to policy improvement.

黄骅坳陷大港探区油气资源潜力与资源结构预测

Facing the problems that Dagang region of Huanghua Depression has high exploration degree and its remaining resource potential and structure are not clear, the theory of Petroleum Accumulation System (PAS) is applied to divide and evaluate the oil/gas systems quantitatively. Then, the petroleum accumulation systems are taken as units to forecast and analyse the oil/gas resources and their structure using statistical methods of sampling analysis of discovery process model and generalized pareto distribution model. The exploration benefit of the unit is estimated using exploration simulation methods. On the basis of the above study, the resource potential of Huanghua Depression is discussed.Huanghua Depression can be diveded into four petroleum accumulation systems, i.e. North PAS5 Middle Qibei PAS, Middle Qinan PAS and South PAS. Each PAS can be diveded futher into several sub- PASs. Using the basic princple of Analytical Hierarchy Process, the method of quantitative evaluation of PAS is established. Then the elements and maturity of PAS are evaluated quantitatively.Taking migration and accumulation units and sub-PASs as prediction units, sampling analysis of discovery process model and generalized pareto distribution model are applied comparatively to forecast the resource structure of eight migration and accumulation units in six PASs of medium-high exploration degree. The results of these two methods are contrasted and analyzed. An examination of X2 data of these two models from exploration samples shows that generalized pareto distribution model is more effective than sampling analysis of discovery process model in Huanghua Depression. It is concluded that minimum and maximum size of reservoir and discovery sequence of reservoirs are the sensitive parameters of these two methods.Aiming at the difficult problem of forecast in low exploration degree, by analysis of relativity between resource parameters and their possible influential geological factors, forecast models for resource parameters were established by liner regressing. Then the resource structure is forecasted in PASs of low exploration degree.Based on the forecast results, beginning with the analysis of exploration history and benefit variation, the exploration benefit variation of the above PASs is fitted effectively using exploration simulation method. The single well exploration benefit of remaining oil resource is also forecasted reasonably.The results of resource forecast show that the total oil resources ofHuanghua Depression amount to 2.28 b illion ton. By the end o f 2 003, the accumulative total proved oil reserve is 0.90 billion ton and the remaining oil resources is 1.38 billion ton. The remaining oil resource is concentrated in Kongdian-Dengmingshi, Banqiao-Beidagang, Qidong-Yangerzhuang and Baidong-Qizhong sub-PASs.