How Fast Do Banks Adjust? A Dynamic Model of Labor-Use with an Application to Swedish Banks

This paper deals with a dynamic adjustment process in which adjustment of a key variable input (labor) towards its desired level is modeled in a panel data context. The partial adjustment type model is extended to make the adjustment parameter both firm- and time-specific by specifying it as a function of firm- and time-specific variables. Desired level of labor use is represented by a labor requirement function, which is a function of outputs and other firm-specific variables. The catch-up factor is defined as the ratio of actual to desired level of employment. Productivity growth is then defined in terms of a shift in the desired level of labor use and the change in the catch-up factor. Swedish banking data is used as an application of the above model.     

On the Use of Value Efficiency Analysis and Some Further Developments

The purpose of this paper is to discuss the use of Value Efficiency Analysis (VEA) in efficiency evaluation when preference information is taken into account. Value efficiency analysis is an approach, which applies the ideas developed for Multiple Objective Linear Programming (MOLP) to Data Envelopment Analysis (DEA). Preference information is given through the desirable structure of input- and output-values. The same values can be used for all units under evaluation or the values can be specific for each unit. A decision-maker can specify the input- and output-values subjectively without any support or (s)he can use a multiple criteria support system to assist him/her to find those values on the efficient frontier. The underlying assumption is that the most preferred values maximize the decision-maker's implicitly known value function in a production possibility set or a subset. The purpose of value efficiency analysis is to estimate a need to increase outputs and/or decrease inputs for reaching the indifference contour of the value function at the optimum. In this paper, we briefly review the main ideas in value efficiency analysis and discuss practical aspects related to the use of value efficiency analysis. We also consider some extensions.     

Are generalized call-spreads efficient?

In order to explain coexistence of a deductible for low values of the loss and an upper limit for high values of the loss in insurance contracts, we consider the exchange of risk between two rank dependent expected utility maximizers. It is shown that if the insurer (insured) takes more into account the lowest outcomes – hence maximal losses – than the insured (insurer), then the optimal contract has an upper limit (includes a deductible for high values of the loss). If furthermore, the insured (insurer) neglects the highest outcomes while the insurer (insured) does not, the optimal contract includes a deductible (full insurance) for low values of the loss.     

DEA evaluations of long- and short-run efficiencies of digital vs. physical product “dot com” companies

This paper applies Data Envelopment Analysis to determine relative efficiencies between internet dot com companies that produce only physical products and those that produce only digital products. To allow for the fact that the latter are relatively inexperienced, a distinction is made between long- and short-run efficiencies and inefficiencies, with a finding of no statistically significant difference in the short run but digital product companies are significantly more efficient in the long run. A new way of distinguishing between long- and short-run performances is utilized that avoids the need for identifying the time periods associated with long-run vs. short-run efficiencies and inefficiencies. In place of “time,” this paper utilizes differences in the “properties” that economic theory associates with long- and short-run performances.     

The productivity of private and social farms: Multilateral Malmquist indices for Slovene dairying enterprises

Applying programming techniques to farm-level panel data for four cooperative and 12 private dairy farms in the Yugoslav Republic of Slovenia gives estimates of technical efficiency, scale efficiency, and technical progress. These are used to construct multilateral Malmquist indices of total factor productivity (TFP). For the cooperatives, TFP growth has been slow and is attributable to technical progress. For the private farms, technical progress was also slow, but TFP growth was faster due to improved efficiency. Scale inefficiency explains the poorer absolute performance of the private farms, indicating the need for land reform as well as technological change.     

Input- and Output-Oriented Technical Efficiency of Ukrainian Collective Farms, 1989–1992: Bayesian Analysis of a Stochastic Production Frontier Model

We propose estimation of a stochastic production frontier model within a Bayesian framework to obtain the posterior distribution of single-input-oriented technical efficiency at the firm level. All computations are carried out using Markov chain Monte Carlo methods. The approach is illustrated by applying it to production data obtained from a survey of Ukrainian collective farms. We show that looking at the changes in single-input-oriented technical efficiency in addition to the changes in output-oriented technical efficiency improves the understanding of the dynamics of technical efficiency over the first years of transition in the former Soviet Union.     

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.     

基于DEA的经济新区投资绩效评价——以天津滨海新区为例

本文利用数据包络分析(DEA)方法,对经济新区投资绩效进行了综合分析,指出各个非DEA有效决策单元中存在的投入冗余与产出不足并提出了相关结论与建议。     

基于相对竞争力比较的零售企业竞争力评价分析

通过对企业竞争力涵义的分析,构建了零售企业竞争力综合评价指标体系;利用功效系数法和综合评价的方法,通过与同行业其它零售企业竞争力比较和零售企业对自身竞争力评判的方式,建立零售企业的竞争力综合评价模型;使企业能够客观、正确地认识和评价企业自身竞争力,为其进一步提高自己市场竞争力提供科学有效的理论依据。     

Understanding resource deployment efficiency for ESG and financial performance: A DEA approach

COVID-19 has stimulated additional research interest on economic sustainability and ESG in both academia and industry. This study adopts a DEA approach to examine the efficiency of achieving ESG targets and their relationships with financial performance. Using MSCI ESG data from 2015 to 2019 on 1108 Chinese firms, we examine the ESG proportional and pillar mix efficiencies. The dominant strategies for our sampled firms are to improve overall ESG performance by enhancing the E and S pillars through sacrificing G’s performance. The second result shows a positive relationship between proportional efficiency and financial performance while a mixed relationship between pillar mix efficiency and financial performance. However, for the technology sector, there exists some trade-offs between ESG performance and financial performance. Specifically, relative to non-technology firms, improving proportional and pillar mix efficiencies for technology firms could result in some sacrifice in stock valuation.