计量经济分析 = Econometric analysis

http://d1c25a6gwz7q5e.cloudfront.net/papers/67.pdf

Efficiency of financial institutions: International survey and directions for future research

Measuring cost efficiency in banking: Econometric and linear programming evidence

Utilizing recent developments in data envelopment analysis (DEA), this paper examines the performance of the top 55 U.S. commercial banks via a two-stage production process that separates profitability and marketability. Substantial performance inefficiency is uncovered in both dimensions. Relatively large banks exhibit better performance on profitability, whereas smaller banks tend to perform better with respect to marketability. New contextdependent performance measures are defined for profitability and marketability which employ a DEA stratification model and a DEA attractiveness measure. When combined with the original DEA measure, the context-dependent performance measure better characterizes the profitability and marketability of 55 U.S. commercial banks. The new approach identifies areas for improved bank performance over the two-stage production process. The effect of acquisition on efficiency and attractiveness is also examined.

Profitability and Marketability of the Top 55 U.S. Commercial Banks

The purpose of this paper is to briefly trace the evolution of DEA from the initial publication by Charnes et al. (1978b) to the current state of the art (SOA). The state of development of DEA is characterized at four points in time to provide a perspective in both directions—past and future. An evolution map is provided which illustrates DEA growth during the 17-year period, the timing of the major events, and the interconnections and influences between topics. An extensive DEA bibliography is provided.

Data envelopment analysis: The evolution of the state of the art (1978–1995)

Measuring and evaluating the operating efficiency of bank branches requires analytic techniques that provide insights beyond those available from accounting ratio analysis. Data Envelopment Analysis (DEA), a mathematical programming technique, provides useful insights in locating inefficient branches by explicitly considering the mix of services provided and the resources used to provide these bank services. Bank management finds the DEA results provide meaningful insights not available from other techniques that focus on ways to improve productivity. The results suggests that DEA is a beneficial complement to other techniques for improving bank branch efficiency.

Bank branch operating efficiency: Evaluation with Data Envelopment Analysis

One bank used data envelopment analysis DEA to substantially improve its branch productivity and profits while maintaining service quality. It identified over $6 million of annual expense savings not identifiable with traditional financial and operating ratio analysis in its 33-branch system. A fairly new linear-programming-based benchmarking technique, DEA explicitly considers all the resources each branch uses and the services it provides. It compares branches objectively to identify the best-practice branches, the less productive branches, and the changes the less productive branches need to make to reach the best-practice level and to improve their profitability.

Managing Bank Productivity Using Data Envelopment Analysis DEA

This book guides managers and other readers in the use of DBA as a benchmarking technique to 1) identify high cost service units, 2) identify specific changes to each service unit to elevate their performance to the best practice services level providing high quality service at low cost, and 3) guide the improvement process. Bvery 
XX Preface 
assertion and method described herein is supported by an application to an organization that sought to improve performance. Areas where DBA is beneficial and where it can provide only limited benefits are discussed in the context of results and managements' reaction to the DEA findings.

Service Productivity Management : Improving Service Performance using Data Envelopment Analysis (DEA)

http://www.deafrontier.net/papers/EJOR_Shared.pdf

DEA model with shared resources and efficiency decomposition

This chapter focuses on health-care applications of DEA. The paper begins with a brief history of health applications and discusses some of the models and the motivation behind the applications. Using DEA to develop quality frontiers in health services is offered as a new and promising direction. The paper concludes with an eight-step application procedure and list of do’s and don’ts when applying DEA to health services.

H. David Sherman

Papers

Bank branch operating efficiency: Evaluation with Data Envelopment Analysis

Managing Bank Productivity Using Data Envelopment Analysis DEA

Service Productivity Management : Improving Service Performance using Data Envelopment Analysis (DEA)

DEA model with shared resources and efficiency decomposition

Health-Care Applications: From Hospitals to Physicians, from Productive Efficiency to Quality Frontiers