Frontier Analysis Model Research Articles

Stochastic cost frontier analysis – a sensitivity analysis on cost measures

Purpose This paper aims to examine alternative methods for recording and treating costs in studies of bank efficiency. Design/methodology/approach This study used stochastic frontier analysis (SFA) models with core costs and total costs to estimate the cost efficiency of banks in two different economies, Vietnam where the banking system is under-developed (and thus is dominated by traditional banking activities) and New Zealand where the banking system is well-developed (and thus non-traditional banking activities play an important role). Findings The authors found that models using total cost tend to underestimate the banks’ cost efficiency. This underestimation relates to the extent of modern activities in a banking system: it is larger in an advanced banking system (i.e. New Zealand) and smaller in a less-developed banking system (i.e. Vietnam). Research limitations/implications Research is limited to two countries, and it would be useful to apply the same technique to other data sets. Practical implications The paper suggests a new approach to cost SFA studies in banking. Originality/value The paper provides a much more searching analysis of costs in banking than has generally been seen in previous research.

Study on the Efficiency of Medical Scientific Research Based on the Stochastic Frontier Analysis Model

The article used Stochastic Frontier Analysis (SFA) model to evaluate scientific research efficiency of the medical research institutions. Firstly, the evaluation system on the two dimensions of the inputs and outputs was established based on analyzing the influencing factors of efficiency of medical scientific research process; then PCA was used to reduce the dimension of the output index system, and the SFA model was used to evaluate the efficiency; Finally, the accuracy of the model of medical scientific research efficiency was verified through actual cases. Key words: Efficiency of scientific research; Medical research; Stochastic frontier analysis

The Virtuous Circles of Clinical Information Systems: a Modern Utopia.

Clinical information systems (CIS) are developed with the aim of improving both the efficiency and the quality of care. This position paper is based on the hypothesis that such vision is partly a utopian view of the emerging eSociety. Examples are drawn from 15 years of experience with the fully integrated Georges Pompidou University Hospital (HEGP) CIS and temporal data series extracted from the data warehouses of Assistance Publique - Hôpitaux de Paris (AP-HP) acute care hospitals which share the same administrative organization as HEGP. Three main virtuous circles are considered: user satisfaction vs. system use, system use vs. cost efficiency, and system use vs quality of care. In structural equation models (SEM), the positive bidirectional relationship between user satisfaction and use was only observed in the early HEGP CIS deployment phase (first four years) but disappeared in late post-adoption (≥8 years). From 2009 to 2013, financial efficiency of 20 AP-HP hospitals evaluated with stochastic frontier analysis (SFA) models diminished by 0.5% per year. The lower decrease of efficiency observed between the three hospitals equipped with a more mature CIS and the 17 other hospitals was of the same order of magnitude than the difference observed between pediatric and non-pediatric hospitals. Outcome quality benefits that would bring evidence to the system use vs. quality loop are unlikely to be obtained in a near future since they require integration with population-based outcome measures including mortality, morbidity, and quality of life that may not be easily available. Barriers to making the transformation of the utopian part of the CIS virtuous circles happen should be overcome to actually benefit the emerging eSociety.

Disentangling the efficiency drivers in country-level global health programs: An empirical study

Motivated by the cost reductions and outcome improvements generated by benchmarking in many industries, we focus on in-country global health programs to identify and quantify opportunities for process improvement. We empirically study the major efficiency drivers of reproductive health (RH) country programs in Sub-Saharan Africa sponsored by international funding organizations. To ensure a level playing field for comparison across countries, we quantify the impact of cross-country heterogeneity and random shocks on the efficiency of RH programs. To analyze these relationships and isolate the effects attributable to managerial inefficiency, we use a three-stage Data Envelopment Analysis (DEA)/Stochastic Frontier Analysis (SFA) model. We show the impact of environmental factors on program efficiency, linking policy making decisions with operational and health outcome performance. We also show that donor fragmentation negatively impacts managerial efficiency, and we suggest actions to mitigate this effect. We then provide a way to improve performance through benchmarking efforts within groups of countries and present an initial prototype of such efforts.

Technical Efficiency in Turkish Electricity Distribution Market: An Application of Stochastic Frontier Analysis (SFA)

This study analyzes the technical efficiencies of Turkish electricity distribution companies (21 in total) throughout 2002 and 2009. For this aim, we used three different model specifications, all of which are generated from a Stochastic Frontier Analysis (SFA) model. It has been shown that the signs and significance levels of the coefficient estimations are very consistent and satisfactory in all models. For example, all model specifications confirm the presence of increasing returns to scale and of a mild technological progress over time in the market. In addition, among the inputs, all inputs except the quality of the electricity delivered are important in enhancing technical efficiency of the electricity distribution companies, according to the alternative specifications.

State Fiscal Capacity and Tax Effort: Evidence for Indian States

This study analyzes the tax effort of 17 Indian states as a means of creating fiscal space. Four individual state-level taxes—stamp duty and registration fees, state sales tax, state excise duty and motor vehicles tax—are studied as well as the total own-tax revenue of states. Stochastic frontier analysis (SFA) models have been estimated for each of the taxes and for own-tax revenue in order to obtain a measure of inefficiency in tax collection. The data used for the SFA models span the time period 2000–2001 to 2010–2011. The results of the estimation exercises point to technical inefficiency as being the primary reason for states being unable to achieve their potential for revenue collection. Possible reasons for this inefficiency are examined. The estimated tax effort points to large budgetary room that states potentially enjoy for the purpose of raising revenues from existing taxes. Rather disconcertingly, the article notes that the average tax effort seems to be declining over time. JEL Classification: H21, H71

Portfolio efficiency analysis with SFA: the case of PSI-20 companies

ABSTRACTThis study aimed to assess the technical efficiency (TE) of individual companies and their respective sectors that are traded on the Portuguese stock market. We accomplished this by combining the internal input variables (e.g., ‘market value and return’) with exogenous variables (e.g., ‘interest income’, ‘depreciation’, ‘cost of goods’, ‘employees’ and ‘net sales’) into a Stochastic Frontier Analysis (SFA) model. The TE of the PSI-20 (Portuguese Stock Index) was estimated using factors that affect efficiency variability. The main advantage of using the SFA approach is its potential to discriminate between measurement error and systematic inefficiencies in the estimation process. The results demonstrated that TE is higher for enterprises in the industrial, construction and distribution sectors, whereas the commercial banking sector has the lowest TE scores. The ‘employees’ and ‘depreciation’ are the variables which most contribute to stock market inefficiency.

Government grants, private R&D funding and innovation efficiency in transition economy

Although the development of the high-tech industry is part of the national agenda of many countries, particularly transition economies, few studies have analysed innovation efficiency in countries with environments unfavourable to high-tech industry development. This study explores the relationships of government grants, private R&D funding and innovation efficiencies of the high-tech industry in China. We use a stochastic frontier analysis model to study the roles of government and market mechanisms in high-tech industry innovation from 1995 to 2008. Findings show that government grants do not crowd out private funding, but stimulate private R&D expenditure. Private R&D funding has positively influenced innovation in the Chinese high-tech industry, and efficiency potentials are widely under-exploited. Additionally, government grants are observed to negatively impact innovation by large firms in the Chinese high-tech industry. Furthermore, we reveal that human capital can promote the innovation performance of high-tech firms, excepting those of medium scale. The findings provide insightful perspectives on China's high-tech industry.

PSI-20 portfolio efficiency analysis with SFA

The determination of the study was to assessthe technical efficiency of the individual companies andtheir respective groups of the Portuguese stock market.In order to achieve that were combined the inputvariables “market value and return” with exogenousvariables such as “interest income, “depreciation,“cost of goods, “employees” and “net sales” in aStochastic Frontier Analysis model. The technicalefficiency of the PSI-20 enterprises index was estimateddiscovering the factors which assurance to efficiencyvariability, applying the SFA approach mainimprovement which lies in its potential to categorizebetween measurement error and systematicinefficiencies in the estimation process. The resultsrevealed that the technical efficiency is higher for theenterprises in industry, construction and distributioneconomic sectors whereas the commercial bankingsector has the lowest technical efficiency scores. The“employees” and “depreciation” variables are theelements that most enhance to the stock marketinefficiency.

Relationship between recycling rate and air pollution: Waste management in the state of Massachusetts

This study examines the relationship between recycling rate of solid waste and air pollution using data from a waste municipality survey in the state of Massachusetts during the period 2009–2012. Two econometric approaches are applied. The first approach is a fixed effects model, while the second is a Stochastic Frontier Analysis (SFA) with fixed effects model. The advantage of the first approach is the ability of controlling for stable time invariant characteristics of the municipalities, thereby eliminating potentially large sources of bias. The second approach is applied in order to estimate the technical efficiency and rank of each municipality accordingly. The regressions control for various demographic, economic and recycling services, such as income per capita, population density, unemployment, trash services, Pay-as-you-throw (PAYT) program and meteorological data. The findings support that a negative relationship between particulate particles in the air 2.5μm or less in size (PM2.5) and recycling rate is presented. In addition, the pollution is increased with increases on income per capita up to $23,000–$26,000, while after this point income contributes positively on air quality. Finally, based on the efficiency derived by the Stochastic Frontier Analysis (SFA) model, the municipalities which provide both drop off and curbside services for trash, food and yard waste and the PAYT program present better performance regarding the air quality.

A panel data parametric frontier technique for measuring total-factor energy efficiency: An application to Japanese regions

Using the stochastic frontier analysis model, we estimate TFEE (total-factor energy efficiency) scores for 47 regions across Japan during the years 1996–2008. We extend the cross-sectional stochastic frontier model proposed by Zhou et al. (2012) to panel data models and add environmental variables. The results provide not only the TFEE scores, in which statistical noise is taken into account, but also the determinants of inefficiency. The three stochastic TFEE scores are compared with a TFEE score derived using data envelopment analysis. The four TFEE scores are highly correlated with one another. For the inefficiency estimates, higher manufacturing industry shares and wholesale and retail trade shares correspond to lower TFEE scores.

The phycotoxins׳ impact on the revenue of the Portuguese artisanal dredge fleet

The bivalve dredge fleet, considered as one of the most important artisanal fleets due to the high value of the catches, is by far the most extensively studied among the Portuguese artisanal segment. Acknowledging the growing presence of marine phycotoxins in the waters, the present study explores their impact on the revenue of the fleet that operates along the coast of mainland Portugal. The results obtained using stochastic frontier analysis models enlighten the harmful impact of algae blooms on the activity of the artisanal dredge fleets. In particular, it was observed that in the Algarve region, where the frequency and the intensity of these episodes is higher, the sustainability of the dredge fishing activity is seriously compromised by the phycotoxins.

The influence of the market power of Chinese commercial banks on efficiency and stability

Purpose – The purpose of this paper is to estimate the cost and profit efficiency (PE) of Chinese commercial banks in the last ten years and investigate how market power affects bank efficiency and stability. Design/methodology/approach – The paper builds a stochastic frontier analysis model to evaluate the cost and PE of commercial banks. The paper then uses a Lerner index and Z-index to represent market power and stability, respectively. In addition, the paper empirically analyzes the relationship between market power and bank efficiency, stability in the last ten years. Findings – The results show that the efficiency of banks on the Chinese mainland increased during the study period, but is still lower than that of banks in Hong Kong; moreover, the efficiency of four state-owned commercial banks is lower than that of medium and small banks. Market power has a negative relationship with efficiency while its relationship with stability varies among Chinese banks. Research limitations/implications – The results imply that the promotion of financial liberalization and banking reform to introduce an appropriate competition mechanism has had a positive effect on the efficiency and stability of Chinese commercial banks. Practical implications – Thus, the paper will contribute to deepen reform and opening up the banking sector in China. Social implications – The healthy development of banking can enhance the ability of banks to withstand financial risks, to promote the harmonious development of society. Originality/value – The paper estimates the cost and PE of Chinese commercial banks using SFA model and investigates how market power affects bank efficiency and stability. The study design has a certain novelty, where Lerner index and Z index are used, respectively, to measure market power and stability and management efficiency of commercial banks is investigated from two aspects – PE and cost efficiency – by the translog cost function, instead of Douglas production function. In addition, the paper tries to put some of Hong Kong banks included in the study sample, and has a certain reference value.

Estimating the Technical Improvement of Energy Efficiency in the Automotive Industry—Stochastic and Deterministic Frontier Benchmarking Approaches

The car manufacturing industry, one of the largest energy consuming industries, has been making a considerable effort to improve its energy intensity by implementing energy efficiency programs, in many cases supported by government research or financial programs. While many car manufacturers claim that they have made substantial progress in energy efficiency improvement over the past years through their energy efficiency programs, the objective measurement of energy efficiency improvement has not been studied due to the lack of suitable quantitative methods. This paper proposes stochastic and deterministic frontier benchmarking models such as the stochastic frontier analysis (SFA) model and the data envelopment analysis (DEA) model to measure the effectiveness of energy saving initiatives in terms of the technical improvement of energy efficiency for the automotive industry, particularly vehicle assembly plants. Illustrative examples of the application of the proposed models are presented and demonstrate the overall benchmarking process to determine best practice frontier lines and to measure technical improvement based on the magnitude of frontier line shifts over time. Log likelihood ratio and Spearman rank-order correlation coefficient tests are conducted to determine the significance of the SFA model and its consistency with the DEA model. ENERGY STAR® EPI (Energy Performance Index) are also calculated.

A new approach to estimating the metafrontier production function based on a stochastic frontier framework

This paper proposes a new two-step stochastic frontier approach to estimate technical efficiency (TE) scores for firms in different groups adopting distinct technologies. Analogous to Battese et al. (J Prod Anal 21:91–103, 2004), the metafrontier production function allows for calculating comparable TE measures, which can be decomposed into group specific TE measures and technology gap ratios. The proposed approach differs from Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) mainly in the second step, where a stochastic frontier analysis model is formulated and applied to obtain the estimates of the metafrontier, instead of relying on programming techniques. The so-derived estimators have the desirable statistical properties and enable the statistical inferences to be drawn. While the within-group variation in firms’ technical efficiencies is frequently assumed to be associated with firm-specific exogenous variables, the between-group variation in technology gaps can be specified as a function of some exogenous variables to take account of group-specific environmental differences. Two empirical applications are illustrated and the results appear to support the use of our model.

Rights, Water Use and Technical Efficiency in U.S. Agricultural Production

Use of water in agriculture has a major driving force behind general water use patterns in the United States. To assess water's usage and value to agricultural production, this paper adopts the two error stochastic frontier analysis model of Battese and Coelli (1995) to estimate a translog production frontier for agriculture at the county level with four inputs: capital; labor; intermediate inputs; and water withdrawals. We include environmental variables to account for climate effects and pay particular attention to pair-wise differences between the riparian and modified riparian, and the prior appropriation and hybrid water regimes, to place an aggregate value on additional restrictions on water use.All of the primary input coefficients are significant, except for the cross-effect between intermediates and water, with intermediates and cropland having similar marginal products across all regions. The two riparian-based regimes have comparable marginal products of water, while the hybrid average is larger than the prior appropriation value by a factor of ten. Similar patterns appear when looking at measures of efficiency, with riparian and modified riparian regimes having nearly equal efficiency and climate losses when taken in dollar terms, while prior appropriation counties display the largest efficiency losses for each measure.We combine the marginal product and the marginal effect of water-based variables on efficiency to construct a more accurate shadow price of water. The efficiency component displays a consistent premium to regulation, with an average value of $0.71 per acre-foot and a maximum of $1.47, but this does not carry through to the shadow prices. Prior appropriation rights counties have the lowest average shadow price of $15.66 and hybrid rights counties the highest at $162.26, compared to the overall average of $51.79. These differences do seem to be primarily due to the efficiency of water use in production and not due to crop choices.

Efficiency in Brazil's water and sanitation sector and its relationship with regional provision, property and the independence of operators

The purpose of this paper is to assess the comparative efficiency of Brazil's water and sanitation sector. We run a Stochastic Frontier Analysis (SFA) model for a panel of 127 providers covering more than 70 percent of the country's urban population in the period 2003–2010. We use a database built on the National System of Sanitation Statistics (SNIS). The model is fitting and shows a modest efficiency average. The study has policy implications in the discussion of state-level run v. municipal-level run, government-owned v. private-provision, and corporatized providers v. dependent ones. The optimal industrial organization of the sector is discussed from the efficiency perspective. We find that regional and micro-regional firms' have lower costs than municipal providers. Administrative independence seems not relevant when explaining the cost structure, but ownership is. The joint provision of water and sanitation results in higher fixed costs compared to water-only operators. We find that there are not regional differences in cost structures. However, there are slight variations in the efficiency levels and in their dispersion in each region. Finally, inefficiency decreased at a rate of 4.9 percent per year during the time frame under study.

Structural and behavioral robustness in applied best-practice regulation

Benchmarking methods, primarily non-parametric techniques such as Data Envelopment Analysis, have become well-established and informative tools for economic regulation, in particular in energy infrastructure regulation. The axiomatic features of the non-parametric methods correspond closely to the procedural and economic criteria for good practice network regulation. However, critique has been voiced against the robustness of best-practice regulation in presence of uncertainty regarding model specification, data definition and collection. Incorrect data may result from structural sources, such as heterogeneous technologies; deterministic approaches applied to stochastic data generation processes or poorly defined scope of activity. Specifically within regulation, reporting may also be biased through individual gaming or collusive behavior, including the intentional provision of absurd data in order to stall or perturb regulatory process (here called maverick reporting). We review three families of outlier detection methods in terms of their function and application using a data set from Swedish electricity distribution, illustrating the different types of outliers, contrasting with the actual analysis ex post. This paper investigates the foundation of the critique both conceptually and by describing the actual state-of-the-art used in energy network regulation using frontier analysis models in Sweden (2000–2003) and in Germany (2007-). Finally, the paper concludes on the role of outlier detection as a mean to implement regulation with higher robustness.

The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals

The importance of a scientific journal is usually established by considering the number of citations received by the papers that the journal publishes. In this way, the number of citations received by a scientific journal can be considered as a measure of the total production of the journal. In this paper, in order to obtain measures of the efficiency in the production process, the approach provided by stochastic frontier analysis (SFA) is considered, and econometric models are proposed. These models estimate a frontier production, which is the maximum achievable number of citations to the journal based on its resources. The efficiency can then be measured by considering the difference between the actual production and the estimated frontier. This approach is applied to the measurement of the productive efficiency of the journals of the JCR social sciences edition database, which belong simultaneously to the areas of “economics” and “social sciences, mathematical methods”.

Thai manufacturing small and medium sized enterprise technical efficiency: Evidence from firm-level industrial census data

Thai manufacturing small and medium sized enterprises (SMEs) face intense competition in domestic and foreign markets. Given their importance to the economic development of the country it is important to have a clear understanding of their readiness to face the rigors of international competition, including the barriers and specific problems that they face. This study uses a stochastic frontier analysis (SFA) and technical inefficiency effects model to analyze the technical efficiency of Thai manufacturing SMEs and key factors impacting upon it. Analysis of cross-sectional data from a 2007 census of Thai manufacturing SMEs indicates that their weighted average technical efficiency is approximately 50 percent, signifying a high level of technical inefficiency which is reducing potential output. The inefficiency effects model reveals that firm size, firm age, skilled labor, ownership characteristics and location are firm-specific factors that significantly affect the technical inefficiency of production. Key measures to improve the technical efficiency of Thai manufacturing SMEs are an adequate supply of inputs, access to credit facilities, extensive infrastructural development and training programs for employees.