Technical Efficiency and Its Determinants in China's Grain Production

Using survey data from China, frontier production functions are estimated individually for crops of rice, wheat and corn. Technical efficiencies and their determinants are analyzed. The results suggest that one cannot be optimistic about the future of China's grain sector as the scope for output growth through input injection and efficiency gain is found to be quite limited.     

Reverse efficiency measures for environmental assessment in data envelopment analysis

Environmental issues are becoming more and more important in our everyday life. Data Envelopment Analysis (DEA) is a tool developed for measuring relative operational efficiency. DEA can also be employed to estimate environmental efficiency where undesirable outputs like greenhouse gases exist. The classical DEA method identifies best practices among a given empirical data set. In many situations, however, it is advantageous to determine the worst practices and perform efficiency evaluation by comparing DMUs with the full-inefficient frontier. This strategy requires that the conventional production possibility set is defined from a reverse perspective. In this paper, presence of both desirable and undesirable outputs is assumed and a methodological framework for performing an unbiased efficiency analysis is proposed. The reverse production possibility set is defined and new models are presented regarding the full-inefficient frontier. The operational, environmental and overall reverse efficiencies are studied. The important notion of weak disposability is discussed and the effects of this assumption on the proposed models are investigated. The capability of the proposed method is examined using data from a real-world application about paper production.     

Estimation of a non-neutral stochastic frontier production function

This article proposed a hybrid of a stochastic frontier regression. The proposed model and estimation differ from the conventional model of Aigner, Lovell, and Schmidt. The model combines a stochastic frontier regression and a truncated regression to estimate the production frontier with non-neutral shifting of the average production function. The truncated regression identifies the sources of efficiency. The article presents empirical evidence of non-neutral effects of the firm's characteristics—the age of the firms, the export ratio, and the R&D expenditure—on the frontier production function and production efficiency in the Taiwan's electronics industry.We would like to express appreciation to George E. Battese, the associate editor, and anonymous referees for various comments and suggestions. The research was partially supported by the University Research Council of Vanderbilt University, and the Sun Yat-Sen Institute for Social Sciences and Philosophy of Academia Sinica, Taiwan. Residual errors are ours alone.     

Fuzzy Pair-wise Dominance and Implications for Technical Efficiency Performance Assessment

Classically, the concept of efficiency measurement is based on the definition of a frontier that envelops the observed production plans. The efficiency score itself is based on the distance of an observed production plan from this frontier. The frontier along with the required technological assumptions (such as convexity) needed for its definition may be replaced with the concept of pair-wise dominance. This concept leads to a classification scheme for all production plans instead of a ranking based on efficiency scores. Also, the traditional assumption of deterministic or crisp production plans may be substituted with the weaker assumption of fuzzy production plans as proposed by fuzzy set theory. This paper merges these two concepts and defines a new classification scheme based on fuzzy dominance.     

The measurement of productive efficiency: A robust minimax approach

Some applied aspects of robustness are formulated and empirically tested so as to generalize the Farrell efficiency measure for the frontier production function. A minimax method is used to develop a Chebyshev efficiency measure along with a stochastic production frontier. The relative insensitivity of such a measure in respect of sample size variations and outliers are illustrated by an empirical application to educational production functions.     

基于DEA的北京市高技术产业R＆D效率比较分析

本文运用DEA模型全面测算了北京市高技术产业1996—2010年间R＆D的生产前沿面效率、综合技术效率、纯技术效率以及规模效率,对规模收益变化和投入产出的冗余与不足进行了具体分析,并针对北京市政府如何提高高技术产业的R＆D效率提出了建议。     

Production frontier estimation to measure efficiency: A critical evaluation in light of data envelopment analysis

The ranking and measurement of efficiency of decision-making units by two methods—data envelopment analysis and frontier production function—may not always lead to identical results. In this framework we attempt here a critical evaluation of the frontier production function theory in terms of theoretical and empirical implications. It is shown that under certain conditions the two approaches to effciency measurement may lead to identical results.     

A Stochastic Frontier Production Function with Flexible Risk Properties

This paper considers a stochastic frontier production function which has additive, heteroscedastic error structure. The model allows for negative or positive marginal production risks of inputs, as originally proposed by Just and Pope (1978). The technical efficiencies of individual firms in the sample are a function of the levels of the input variables in the stochastic frontier, in addition to the technical inefficiency effects. These are two features of the model which are not exhibited by the commonly used stochastic frontiers with multiplicative error structures.An empirical application is presented using cross-sectional data on Ethiopian peasant farmers. The null hypothesis of no technical inefficiencies of production among these farmers is accepted. Further, the flexible risk models do not fit the data on peasant farmers as well as the traditional stochastic frontier model with multiplicative error structure.     

Measuring mortgage credit availability: A frontier estimation approach

We construct a new measure of mortgage credit availability using a technique developed for production frontier estimation. The resulting “loan frontier” describes the maximum amount obtainable by a borrower of given characteristics. We estimate this frontier using mortgage originations data from 2001 to 2014. We find a substantial expansion of mortgage credit for all borrowers during the housing boom, not only for low‐score or low‐income borrowers. The subsequent contraction in credit was most pronounced for low‐score borrowers. Using variation in the frontier across metropolitan areas over time, we show that borrowing constraints played an important role in the recent housing cycle.     

Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis

Improving productive efficiency is an increasingly important determinant of the future of the swine industry in Hawaii. This paper examines the productive efficiency of a sample of swine producers in Hawaii by estimating a stochastic frontier production function and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models. The technical efficiency estimates obtained from the two frontier techniques are compared. The scale properties are also examined under the two approaches. The industry's potential for increasing production through improved efficiency is also discussed.     

On measures of technical inefficiency and production uncertainty in stochastic frontier production model with correlated error components

Analysis of the behavior of technical inefficiency with respect to parameters and variables of a stochastic frontier model is a neglected area of research in frontier literature. An attempt in this direction, however, has recently been made. It has been shown that in a “standard” stochastic frontier model that both the firm level technical inefficiency and the production uncertainty are monotonically decreasing with observational error. In this paper we show, considering a stochastic frontier model whose error components are jointly distributed as truncated bivariate normal, that this property holds if and only if the distribution of observational error is negatively skewed. We also derive a necessary and sufficient condition under which both firm level technical inefficiency and production uncertainty are monotonically increasing with noise-inefficiency correlation. We next propose a new measure of the industry level production uncertainty and establish the necessary and sufficient condition for firm level technical inefficiency and production uncertainty to be monotonically increasing with industry level production uncertainty. We also study the limiting probabilistic behavior of these conditions under different parametric configuration of our model. Finally we carry out Monte Carlo simulations to study the sample behavior of the population monotonic property of the firm level technical inefficiency and production uncertainty in our model.

Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers

Earlier papers by Aiger, Lovell and Schmidt and by Meeusen and van den Broeck have considered stochastic frontier production functions. this paper extends that work by considering the duality between stochastic frontier production and cost funstions, under the assumtions of exact cost minimization (tecchnical inefficiency only) and of inexact cost minimization (technical and allocative inefficiency). We show how to measure both types of inefficiency, and the associated cost of inefficiency. The techniques are illustrated using data on steam-electric generating plants.     

Technical efficiency during economic reform in Nicaragua: evidence from farm household survey data

This paper employs a translog stochastic frontier model to examine technical efficiency of maize and bean farmers in two selected regions of Nicaragua using farm-level survey data for the 1994–1995 crop year. The average technical efficiency levels are 69.8 and 74.2% for maize and beans, respectively. The results from the maize and beans translog frontier functions show that farmers’ human capital represented by the level of schooling, access to formal credit and farming experience represented by age contribute positively to production efficiency, while farmers’ participation in non-farm employment tends to reduce production efficiency.     

An assessment of Portuguese banks’ efficiency and productivity towards euro area participation

This paper analyses the production technology of Portuguese banks during the 1992–2006 period through the estimation of a translog cost frontier. This period is of major interest because it covers Portugal’s euro area accession and its impact on the banking system. Hence, critical factors impacting the banking system are identified against the background of increasing financial integration prior to the financial crisis that started in 2007 and later translated into strains in some European sovereign debt markets. Banks are modelled as firms which produce loans and other earning assets, choosing the cost minimizing combination of labour, capital and interest bearing debt, subject to holding a predetermined level of equity. According to the results of this study, technological progress has shifted the cost frontier downwards throughout the period under consideration, whereas the distance at which banks have operated from the frontier seems to have remained constant. Further, increases in production under scale economies have also contributed to the recorded increase in productivity.     

Are all Scales Optimal in DEA? Theory and Empirical Evidence

Policy recommendations concerning optimal scale of production units may have serious implications for the restructuring of a sector. The piecewise linear frontier production function framework (DEA) is becoming the most popular one for assessing not only technical efficiency of operations, but also for scale efficiency and calculation of optimal scale sizes. The main purpose of the present study is to investigate if neoclassical production theory gives any guidance as to the nature of scale properties in the DEA model, and empirically explore such properties. Theoretical results indicate that the DEA model may have more irregular properties than usually assumed in neoclassical production theory, concerning shape of optimal scale curves and the M-locus. The empirical results indicate that optimal scale may be found over almost the entire size variations in outputs and inputs, thus making policy recommendations about efficient scale difficult. It seems necessary to establish the nature of optimal scale before any practical conclusions can be drawn. Proposals for indexes characterizing the nature of optimal scale are provided.     

Robustness and inference in nonparametric partial frontier modeling

A major aim in recent nonparametric frontier modeling is to estimate a partial frontier well inside the sample of production units but near the optimal boundary. Two concepts of partial boundaries of the production set have been proposed: an expected maximum output frontier of order m=1,2,… and a conditional quantile-type frontier of order α∈]0,1]. In this paper, we answer the important question of how the two families are linked. For each m, we specify the order α for which both partial production frontiers can be compared. We show that even one perturbation in data is sufficient for breakdown of the nonparametric order-m frontiers, whereas the global robustness of the order-α frontiers attains a higher breakdown value. Nevertheless, once the α frontiers break down, they become less resistant to outliers than the order-m frontiers. Moreover, the m frontiers have the advantage to be statistically more efficient. Based on these findings, we suggest a methodology for identifying outlying data points. We establish some asymptotic results, contributing to important gaps in the literature. The theoretical findings are illustrated via simulations and real data.     

An examination of the cost efficiency of banks in Taiwan and China using the metafrontier cost function

Using the stochastic metafrontier framework of Battese et al. (J Prod Anal 21:91–103, 2004), this study proposes to compare and measure the cost efficiency and cost frontier gap between the banking industry in Taiwan and China. It further identifies environmental variables that determine bank’s cost frontier gap between two countries. Data on 69 sample banks for years 2005–2009 are used in the empirical analysis and inference. The empirical results show that Taiwanese banks have in general the superior cost frontier of production, but inferior cost efficiency of operation than Chinese banks. Private banks in Taiwan have the best cost frontier, whereas foreign banks in China are most cost efficient among all banks in Taiwan and China. The empirical results also reveal that the majority of Taiwanese banks are undersized and that most banks in China are oversized. Finally, the regression results show that the financial market structure, institutional environment, and political development are significant determinants of the cost gap between the cost frontiers of banks in Taiwan and China. Therefore, programs related to changes directed toward a better bank production environment can be initiated to improve the cost technologies of banks in both Taiwan and China.     

A general framework for frontier estimation with panel data

The main objective of the paper is to present a general framework for estimating production frontier models with panel data. A sample of firms i = 1, ..., N is observed on several time periods t = 1, ... T. In this framework, nonparametric stochastic models for the frontier will be analyzed. The usual parametric formulations of the literature are viewed as particular cases and the convergence of the obtained estimators in this general framework are investigated. Special attention is devoted to the role of N and of T on the speeds of convergence of the obtained estimators. First, a very general model is investigated. In this model almost no restriction is imposed on the structure of the model or of the inefficiencies. This model is estimable from a nonparametric point of view but needs large values of T and of N to obtain reliable estimates of the individual production functions and estimates of the frontier function. Then more specific nonparametric firm effect models are presented. In these cases, only NT must be large to estimate the common production function; but again both large N and T are needed for estimating individual efficiencies and for estimating the frontier. The methods are illustrated through a numerical example with real data.     

A Production Model With Firm-Specific Temporal Variation in Technical Inefficiency: With Application to Spanish Dairy Farms

This paper introduces a stochastic frontier production model which accommodates firm-specific temporal variation in technical inefficiency. Unlike Cornwell, Schmidt and Sickles (1990), technical inefficiency is not modeled through the intercept of the production frontier, but through an error component model. The proposed model is a generalization of the Battese and Coelli (1992) model, which imposed a common temporal pattern upon all firms. In our application involving Spanish dairy farms, we find that the new model is preferred to the Battese and Coelli (1992) model on the basis of the likelihood ratio test. Results provide a new source of information on the different patterns of technical inefficiency change among the 82 farms in the sample.     

A Recursive Thick Frontier Approach to Estimating Production Efficiency*

We introduce a new panel data estimation technique for production and cost functions, the recursive thick frontier approach (RTFA). RTFA has two advantages over existing econometric frontier methods. First, technical inefficiency is allowed to be dependent on the explanatory variables of the frontier model. Secondly, RTFA does not hinge on distributional assumptions on the inefficiency component of the error term. We show by means of simulation experiments that RTFA outperforms the popular stochastic frontier approach and the ‘within’ ordinary least squares estimator for realistic parameterizations of a productivity model. Although RTFAs formal statistical properties are unknown, we argue, based on these simulation experiments, that RTFA is a useful complement to existing methods.