中国高技术产业自主创新效率评价——基于DEA的Malmquist指数方法

本文利用DEA的Malmquist指数方法中技术进步反映原始创新效率,利用DEA的Malmquist指数方法中技术效率进步反映二次创新效率．实证分析结果表明：我国高技术产业自主创新效率水平已经得到较大提高,但这种提高主要受益于二次创新效率的提高,高技术产业原始创新效率水平却是在下降的,这在一定程度上抵消了高技术产业自主创新效率的提高,原始创新与二次创新能力没有同步提高．     

Total-factor energy productivity growth of regions in Japan

This article computes the energy productivity changes of regions in Japan using total-factor frameworks based on data envelopment analysis (DEA). Since the traditional DEA-Malmquist index cannot analyze changes in single-factor productivity changes under the total-factor framework, we apply a new index proposed by Hu and Chang [2009. Total-factor energy productivity growth of regions in China. Energy Policy, submitted for publication]: a total-factor energy productivity change index (TFEPI) that integrates the concept of the total-factor energy efficiency index into the Malmquist productivity index (MPI). Moreover, we separate TFEPI into change in relative energy efficiency, or the ‘catching up effect,’ and shift in the technology of energy use, or the ‘innovation effect.’ The data from 47 prefectures during the period of 1993–2003 are used to compute the TFEPI and its components for 4 kinds of energy. The TFEPI of electric power for commercial and industrial use changes −0.6% annually, which can be separated into a total-factor energy efficiency change of 0.2% and a technical change of −0.8%. The TFEPI for coal deteriorates by 1.0%/year, which is mostly caused by a decrease in relative energy efficiency change. We define and identify ‘innovators’ who cause the frontier to shift. Most regions identified as frontier shifters are located outside of Japan's four major industrial areas.     

基于生态福利绩效的湖南省矿业城市绿色发展研究

实现矿业城市的绿色发展是解决矿产资源短缺与环境污染问题的重要途径,因此有必要对其绿色发展水平进行测算和评价。本文以湖南省矿业城市为研究对象,利用非径向SBM模型与DEAMalmquist模型分析了其动态与静态的生态福利绩效,再运用Tobit回归模型进一步探索了影响矿业城市动态生态福利绩效的因素。研究结果表明:技术进步和固定资产投入能提高矿业城市动态的生态福利水平,而企业排污治理行动却导致工业产值增速放缓;生产要素的投入和使用效率能提升矿业城市静态的生态福利绩效,而经济发展水平则与其无直接关联;经济发展水平和科技创新是导致矿业城市动态生态福利绩效增长的主要驱动因素,而现有的工业产业结构和环境规制则是其抑制因素。本文研究结论可以为湖南省及其他地区的矿业城市实现矿物资源高效、绿色利用提供理论依据和实践启示。     

Benchmarking road safety of U.S. states: A DEA-based Malmquist productivity index approach

In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of U.S. states in decreasing the number of road fatalities. Even though the national trend in fatal crashes has reached to the lowest level since 1949 (Traffic Safety Annual Assessment Highlights, 2010), a state-by-state analysis and comparison has not been studied considering other characteristics of the holistic national road safety assessment problem in any work in the literature or organizational reports. In this study, a DEA based Malmquist index model was developed to assess the relative efficiency and productivity of 50 U.S. states in reducing the number of fatal crashes. The single output, fatal crashes, and five inputs were aggregated into single road safety score and utilized in the DEA-based Malmquist index mathematical model. The period of 2002–2008 was considered due to data availability for the inputs and the output considered. According to the results, there is a slight negative productivity (an average of −0.2 percent productivity) observed in the U.S. on minimizing the number of fatal crashes along with an average of 2.1 percent efficiency decline and 1.8 percent technological improvement. The productivity in reducing the fatal crashes can only be attributed to the technological growth since there is a negative efficiency growth is occurred. It can be concluded that even though there is a declining trend observed in the fatality rates, the efficiency of states in utilizing societal and economical resources towards the goal of zero fatality is not still efficient. More effective policy making towards increasing safety belt usage and better utilization of safety expenditures to improve road condition are derived as the key areas to focus on for state highway safety agencies from the scope of current research.     

Improving the discrimination of data envelopment analysis models in multiple time periods

The trade‐offs approach is an advanced tool for the improvement of the discrimination of data envelopment analysis (DEA) models; this can improve the traditional meaning of efficiency as a radial improvement factor for inputs or outputs. Therefore, the Malmquist index – the prominent index for measuring the productivity change of decision making units (DMUs) in multiple time periods that use DEA models with variable returns to scale and constant returns to scale technologies – can be improved by using the trade‐offs technology. Hence, an expanded Malmquist index can be defined as an improved method of a traditional Malmquist index that uses the production possibility set, which could present more discrimination of DMUs, in the presence of the trade‐offs technology. In addition, similar to a traditional Malmquist index, it breaks down into different components. An illustrative example is presented to show the ability of the suggested method of presenting the Malmquist index from a computational point of view.     

Road safety development in Europe: A decade of changes (2001–2010)

To evaluate the road safety development of a country over time, the percentage change in the number of road fatalities is traditionally the main indicator. However, simply considering the reduction in the road fatalities may not correctly reflect the real improvement in road safety because the transport circumstances of a country underlying the road fatalities also change every year. In this study, we present a new way for measuring the road safety performance change over time, which is to use the technique of data envelopment analysis (DEA) and the Malmquist productivity index. In doing so, we can not only focus on the evolution of road safety final outcomes within a given period, but also take the changes of different measures of exposure in the same period into account. In the application, the DEA-based Malmquist productivity index (DEA-MI) is used to measure the extent to which the EU countries have improved their road safety performance over the period 2001–2010. More objective and insightful results are obtained compared to the ones based on the traditional indicator. The results show considerable road safety progress in most of the Member States during these ten years, and the fatality risk rather than the fatality number on Europe's roads has actually been reduced by approximately half. However, the situation differed considerably from country to country. The decomposition of the DEA-MI into ‘efficiency change’ and ‘technical change’ further reveals that the bulk of the improvement during the last decade was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector in Europe, rather than through the relatively underperforming countries catching up with those best-performing ones.     

Growth and renewable energy in Europe: Benchmarking with data envelopment analysis

This paper conducts data envelopment analysis (DEA) for the purpose of calculating inefficiencies in the European countries' growth using as main inputs the variables typically used in the growth-energy literature nexus such as energy consumption, carbon emissions, employment and capital but also with a particular focus on renewable energy sources (RES) consumption. Since we have a panel data set, we also apply the Malmquist method to calculate total factor productivity and an analysis of peers. Mean overall efficiency has been calculated to be equal to 0.892, while mean pure technical efficiency is 0.569 and scale efficiency 1.798. Countries with remarkable renewable energy performance have medium to low efficiency, while renewable energy laggards are among the most technically efficient countries in Europe. Results from this paper are useful for monitoring and benchmarking purposes with respect to their 2020 renewable energy obligations stemming from 2009/28/ED Directive.     

Decomposing energy productivity change: A distance function approach

By using output distance functions, this paper decomposes energy productivity change into several components: effects of the changes in the ratios of non-energy inputs to energy, energy supply composition, and output composition; technical efficiency change; technological change. We apply this method to decompose energy productivity change in 23 OECD countries between 1980 and 1990. Results show that technological change is the most important source; increase in capital–energy ratio and the growing importance within total energy supply of electricity also contribute to it.     

An empirical analysis of energy efficiency in China''s iron and steel sector

Using Malmquist Index Decomposition, this paper investigates energy efficiency of China's iron and steel sector during the period 1994–2003. Provincial panel data is employed, allowing various energy inputs and product outputs. The energy efficiency improvement is decomposed into two components: technical change (production frontier shifting effect) and technical efficiency change (catching up effect) over time. Our empirical results indicate that the energy efficiency in China's iron and steel sector increased by 60% between 1994 and 2003, which is mainly attributable to technical progress rather than technical efficiency improvement. The energy efficiency gaps among provincial iron and steel sectors during this period have widened. However, energy efficiency of iron and steel plants owned by the state has slowly improved in some regions, such as Shanghai, Liaoning, Beijing and Hubei. Nevertheless, technical efficiency in these four regions has decreased considerably. Energy efficiency in China's two largest private-own iron and steel bases (Heibei and Jiangsu) improved significantly.     

集成电路产业生产效率及影响因素分析——基于Malmquist函数与结构方程模型

本文采用Malmquist全要素生产率指数及其关于生产效率的分解,考察了近年来我国集成电路产业(芯片设计、芯片制造、测试封装三类企业)全要素生产率及生产效率的变动趋势,分析了影响我国集成电路产业生产效率的内在与外在因素。结果表明,总体上影响集成电路产业生产效率的主要是内在因素,包括技术水平、规模效应和人员素质。据此提出了一些政策建议。