Got milk? The rapid rise of China’s dairy sector and its future prospects

This paper synthesizes recent research and new empirical findings to build a more comprehensive understanding of developments in China’s dairy sector. China’s tremendous rise in dairy demand has been driven by several mutually reinforcing factors: including rapid income growth, promotion by the government and dairy industry, changes in urban lifestyles, and the development of new, more sophisticated marketing channels. Domestic milk output has grown to satisfy rising demand largely by increasing the dairy herd. Substantial increases in productivity have been achieved through technology adoption, but there is evidence that the torrid growth has created inefficiencies because adaptations to marketing rules, infrastructure, and institutions have not kept pace with the changing environment. These results suggest there is ample room for future growth in both domestic milk production and dairy demand, but multinational firms and imported products will likely play and increasing role as China’s dairy market continues to develop.     

印度股票市场改革的经验与启示

印度股票市场改革对中国的启示主要在于,作为一个转型经济国家在发展金融市场尤其是股票市场的过程中出现某些消极问题在某种意义上是可以的,关键在于改革者要在既定的约束条件下完善相关的制度和规则,从而引导相关利益主体的行为以实现效率改进,同时在制度移植和模仿方面要注意有关的适用条件,在改革方式上宜快则快。     

西气东输工程用感应加热弯管技术条件探讨

在对国外X70管线弯管技术条件进行调查分析与研究的基础上，对其中的几个关键技术问题包括母管成分，弯管的制造工艺和技术路线，强度与韧性要求，屈强比，Cu污染问题等进行了讨论。一些观点在西气东输感应加弯管技术条件中得到应用。     

Technical analysis as the representation of typical cognitive biases

The present research provides a justification for the popularity of the technical analysis. It finds that financial analysts firmly discriminate between two types of technical signals—those based on typical cognitive biases and “empty” signals that sound like a technical analysis but are without any connotation with psychological inclinations.At the same time that they treat them differently, different analysts rate these items very similarly. These results suggest that the popularity of technical analysis is associated with its relation to the typical cognitive biases of humans.     

Information value and efficiency measurement for risk-averse firms

This paper has three goals. First, we demonstrate that standard arguments and methods from production and duality analysis can be used to provide a comprehensive and general treatment of the value of information for a risk-averse firm with expected-utility (linear-in-probabilities) preferences and a general stochastic technology. Second, we place bounds on the value of information for a risk-averse firm and relate these bounds to characteristics of the technology and the producer’s preferences. The third and final goal is to derive the implications that information differences can have for measured efficiency differences and to relate the bounds on the value of information to those measured differences.      

Performance Measurement in Government Service Provision: The Case of Police Services in New South Wales

The NSW Government is implementing a financial framework which is designed to encourage government service providers to become more efficient and effective. NSW Treasury is using Data Envelopment Analysis (DEA) to measure the efficiency of major government service providers, such as police, courts and hospitals. This paper outlines the progress in implementing the new financial framework and illustrates the way NSW Treasury will use DEA to help improve the efficiency of government service providers by describing an analysis of the NSW Police Service. The results suggest that NSW police patrols (local police districts) could, on average, reduce input usage by 13.5 percent through better management, and by 6 percent if the patrols could be restructured to achieve the optimal scale. Results also indicate that differences in operating environments, such as location and socioeconomic factors, do not have a significant influence upon the efficiency of police patrols.     

Applying efficiency measurement techniques to the measurement of productivity change

Deterministic frontier analysis (DFA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA) are alternative analytical techniques designed to measure the efficiency of producers. All three techniques were originally developed within a cross-sectional context, in which the objective is to compare the efficiencies of producers. More recently all three techniques have been extended for use in a panel data context. In the latter context it is possible to measure productivity change, and to decompose measured productivity change into its sources, one of which is efficiency change. However when efficiency measurement techniques, particularly SFA, have been applied to panel data, it has infrequently been made clear what the objective of the analysis is: the measurement of efficiency, which may vary through time as well as across producers, or the measurement and decomposition of productivity change. In this paper I explore the use of each technique in a panel data context. I find DFA and DEA to have achieved a more satisfactory reorientation toward productivity measurement than SFA has.     

A monetary business cycle model with unemployment

To reproduce key features of the post-war U.S. data, most monetary business cycle models must assume there are high price markups and that agents have high labour supply elasticities despite the existence of contradictory microeconomic evidence. This paper eliminates the need for these assumptions by introducing imperfectly observed effort into a limited participation model. The estimated model is better able to capture the sluggish price response to a monetary policy shock than the standard model, and is consistent with evidence regarding the qualitative responses of the U.S. economy to technology shocks, fiscal policy shocks and monetary policy shocks.     

Nonparametric efficiency analysis: A multivariate conditional quantile approach

This paper focuses on nonparametric efficiency analysis based on robust estimation of partial frontiers in a complete multivariate setup (multiple inputs and multiple outputs). It introduces α-quantile efficiency scores. A nonparametric estimator is proposed achieving strong consistency and asymptotic normality. Then if α increases to one as a function of the sample size we recover the properties of the FDH estimator. But our estimator is more robust to the perturbations in data, since it attains a finite gross-error sensitivity. Environmental variables can be introduced to evaluate efficiencies and a consistent estimator is proposed. Numerical examples illustrate the usefulness of the approach.     

Implications of variant efficiency measures for policy evaluations in UK higher education

Policy goals in UK higher education encourage the publicly funded universities to become more-specialised and larger in size without compromising output quality. Efficiency gains are expected to flow from this increased specialisation in accordance with universities’ comparative research and teaching strengths. Mergers to reap further gains from economies of scale are also being actively encouraged. Given this scenario, the paper investigates whether best-practice efficiency measurement based on data envelopment analysis (DEA) provides empirical support for the current policy goals. It also assesses whether such support is dependent on the specific type of efficiency measure used in the DEA modelling. This assessment finds that a selection of (nine) commonly used, variant efficiency measures generally support the current policy goals. The paper also uses the principal-agent framework to explore the issues involved in using computed DEA-based efficiency scores for policy evaluations and possible funding guidance in UK higher education. This highlights empirically how policy-makers and universities can have very different preferences about which efficiency measure is to be used for policy evaluations and possible funding guidance.