Health Insurance Reform and Efficiency of Township Hospitals in Rural China: An Analysis from Survey Data

In the rural health-care organization of China, township hospitals ensure the delivery of basic medical services. Particularly damaged by the economic reforms implemented from 1975 to the end of the 1990s, township hospitals efficiency is questioned, mainly with the implementation since 2003 of the reform of health insurance in rural areas. From a database of 24 randomly selected township hospitals observed over the period 2000-2008 in Weifang prefecture (Shandong), the study examines the efficiency of township hospitals through a two-stage approach. As curative and preventive medical services delivered at township hospital level use different production processes, two data envelopment analysis models are estimated with different orientation chosen to compute scores. Results show that technical efficiency declines over time. Factors explaining the technical efficiency are mainly environmental characteristics rather than internal factors, but our results suggest also that in the context of China, the efficiency of township hospitals is influenced by unobservable factors.China, New Rural Cooperative Medical Scheme, Technical efficiency, data envelopment analysis, Township Hospitals.

Sensitivity analysis of network DEA illustrated in branch banking

Users of data envelopment analysis (DEA) often presume efficiency estimates to be robust. While traditional DEA has been exposed to various sensitivity studies, network DEA (NDEA) has so far escaped similar scrutiny. Thus, there is a need to investigate the sensitivity of NDEA, further compounded by the recent attention it has been receiving in literature. NDEA captures the underlying performance information found in a firm?s interacting divisions or sub-processes that would otherwise remain unknown. Furthermore, network efficiency estimates that account for divisional interactions are more representative of a dynamic business. Following various data perturbations overall findings indicate positive and significant rank correlations when new results are compared against baseline results - suggesting resilience. Key findings show that, (a) as in traditional DEA, greater sample size brings greater discrimination, (b) removing a relevant input improves discrimination, (c) introducing an extraneous input leads to a moderate loss of discrimination, (d) simultaneously adjusting data in opposite directions for inefficient versus efficient branches shows a mostly stable NDEA, (e) swapping divisional weights produces a substantial drop in discrimination, (f) stacking perturbations has the greatest impact on efficiency estimates with substantial loss of discrimination, and (g) layering suggests that the core inefficient cohort is resilient against omission of benchmark branches. Various managerial implications that follow from empirical findings are discussed in conclusions.

A Benchmarking Analysis of Electricity Distribution Utilities in Switzerland

This paper studies the sensitivity problems of the benchmarking methods used in the regulation practice. Three commonly used methods have been applied to a sample of 52 electricity distribution utilities to estimate their cost efficiency. These methods include stochastic frontier, corrected ordinary least squares and data envelopment analysis. The results indicate that both efficiency scores and ranks are significantly different across various models. Especially considerable differences exist between parametric and non-parametric methods.

The technical efficiency of Public Libraries in the Czech Republic

The purpose of this article is to define and evaluate the development of the aggregated technical efficiency of public libraries in the Czech Republic from 1993 to 2014. To simulate technical efficiency, the Data Envelopment Analysis Model (The BCC model) was chosen. To evaluate the production units (the unit of the Czech Republic from 1993 to 2014 and its production is given by the sum of real homogenous units, i.e. the public libraries operating in a given area and in a given time), two input variables (the recalculated number of employees and the library collection) and two output variables (the number of registered readers and the number of loans) were analysed. Two basic models were simulated – the M1 model oriented to inputs and the M2 model oriented to outputs. Correlation between the input and output variables was researched using Pearson’s coefficient. Within the range of the M1 and M2 basic models, partial models were simulated. All of the basic and partial models identically showed eight efficient periods of public libraries in the Czech Republic (1995, 1997, 1999–2000, 2002–2005). Public libraries were, according to the chosen variables, inefficient in the remaining 16 observed years

CAN FISCAL POLICY EXPLAIN TECHNICAL INEFFICIENCY OF PRIVATISED FIRMS? A PARAMETRIC AND NONPARAMETRIC APPROACH

The massive interests of economic literature about the privatisation gave a notable impulse to the discussion about this theme in the pre and post privatisation firms performance. Basically in every case after privatisation the level of profit increases. Does this mean that privatisation is certainly able to increase efficiency? In this field a large part of the literature leave out the complex problem that public firms usually are subject to objectives and constraints that differently from private firms can affect the overall economic efficiency. Unfortunately many authors ignore the effects of taxation during the process of privatisation, but in real term there are significant tax issues that must be considered by public and private decision maker. In this paper we concentrate the attention on the efficiency measures with the purpose to identify and measure sources of successful performance that can be used in policy planning and allocation of resources. Several techniques to calculate these frontier functions have been used, some of them parametric, others non-parametric to empirically investigate the relationship between taxation on firm’s income and efficiency in the period pre and post-privatisation. In this work we use both econometric and mathematical programming approaches for measuring efficiency. The econometric tool provide maximum likelihood estimates of a stochastic production and cost functions to distinguish noise from inefficiency. Instead, the mathematical programming approaches are nonstochastic and they do not make strict assumptions on the functional form of production and the statistical properties of the data. The general results obtained from the 3 different tools (Stochastic Frontier, Data Envelopment Analysis and Neural Network) are consistent. In fact, we see that privatization enhanced efficiency in three out of four sample firms.Privatization, Fiscal policy, Data Envelopment Analysis, Stochastic Frontier, Neural Network

Efficiency Analysis of German Electricity Distribution Utilities : Non-Parametric and Parametric Tests

This paper applies parametric and non-parametric and parametric tests to assess the efficiency of electricity distribution companies in Germany. We address traditional issues in electricity sector benchmarking, such as the role of scale effects and optimal utility size, as well as new evidence specific to the situation in Germany This paper applies parametric and non-parametric and parametric tests to asses the efficiency of electricity distribution companies in Germany. We use labor, capital, and peak load capacity as inputs, and units sold and the number of customers as output. The data covers 307 (out of 553) German electricity distribution utilities. We apply a data envelopment analysis (DEA) with constant returns to scale (CRS) as the main productivity analysis technique, whereas stochastic frontier analysis (SFA) with distance function is our verification method. The results suggest that returns to scale play a minor role; only very small utilities have a significant cost advantage. Low customer density is found to affect the efficiency score significantly in the lower third of all observations. Surprisingly, East German utilities feature a higher average efficiency than their West German counterparts. The correlation tests imply a high coherence of the results. --Efficiency analysis,econometric methods,electricity distribution,benchmarking,Germany

Determinants of Cost Inefficiency of Critical Access Hospitals: A Two-stage, Semi-parametric Approach

This study examines, post-conversion, cost inefficiency of Critical Access Hospitals (CAH) using a two-stage approach. While the results suggest that Medicare cost-based reimbursement and longer participation in the CAH program may increase the cost inefficiency of CAHs, the extent of this inefficiency increase is lower than what previous literature showed.Critical Access Hospitals, cost inefficiency, two-stage approach, bootstrap, Community/Rural/Urban Development, Health Economics and Policy, Production Economics, I18,

Identification of Segments of French Urban Public Transport with a Latent Class Frontier Model

This paper analyses technical efficiency of French urban public transport from 1995 to 2002 with unbalanced panel data. The latent class frontier model is used allowing the identification of different segments in the production frontier. We find that there are three statistically significant segments in the sample. Therefore, we conclude that no common transport policy can reach all of the transportation companies analysed, thereby requiring transport policies by segments.Urban public transport, stochastic production frontier, latent class model, technical efficiency, panel data.

Valuing Environmental Factors in Cost-Benefit Analysis Using Data Envelopment Analysis

Environmental cost-benefit analysis (ECBA) refers to social evaluation of investment projects and policies that involve significant environmental impacts. Valuation of the environmental impacts in monetary terms forms one of the critical steps in ECBA. We propose a new approach for environmental valuation within ECBA framework that is based on data envelopment analysis (DEA) and does not demand any price estimation for environmental impacts using traditional revealed or stated preference methods. We show that DEA can be modified to the context of CBA by using absolute shadow prices instead of traditionally used relative prices. We also discuss how the approach can be used for sensitive analysis which is an important part of ECBA. We illustrate the application of the DEA approach to ECBA by means of a hypothetical numerical example where a household considers investment to a new sport utility vehicle.Cost-Benefit Analysis, Data Envelopment Analysis, Eco-Efficiency, Environmental Valuation, Environmental Performance, Performance Measurement