A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms

This article investigates farm-level efficiency of U.S. dairy farmers by estimating their technical and allocative efficiency. Technical inefficiency is assumed to be composed of a deterministic component that is a function of some farm-specific characteristics and a random component. By doing this we extend the stochastic frontier methodology in which determinants of technicial inefficiency are explicitly introduced in the model. Given the inputs, variations in efficiency of farms are then explained by both deterministic and random components of technical inefficiency. The empirical results indicate that (a) levels of education of the farmer are important factors determining technical inefficiency and (b) large farms are more efficient (technically) than small and medium-sized farms. Both technical and allocative inefficiency are found to decrease with increase in the level of education of the farmer.     

基于随机前沿分析的中国玉米生产技术效率研究

利用1995～2008年中国15个主要玉米产区的投入与产出面板数据建立了随机前沿生产函数模型,对中国玉米生产的技术效率进行了测算,全国玉米生产平均技术效率为0.824。在此基础上,进一步分析了技术效率的时间差异、地区差异及收敛性,发现玉米生产技术效率时间、地区差异明显,但从全国来看,各产区之间的玉米生产技术效率的差距正在逐步缩小,具有趋同趋势。提高玉米生产技术效率,需要在以下几个方面做出改进：加强对灾害的预防和监测工作,并有科学计划地兴修农田水利设施;加大种子用量,提高机械化水平,进行科学管理;加强玉米生产技术的研发和创新等。     

Measuring and Decomposing Productivity Change

Measuring productivity change with Malmquist indices has become common practice, because they are easily computed using nonparametric programming techniques and can be readily decomposed into technical and efficiency change. However, this approach is nonstochastic and requires a constant returns to scale assumption to construct the reference technology. We propose estimating productivity change using a stochastic input distance frontier, imposing no restrictions on returns to scale. We derive the analogous decomposition of productivity change and develop a generalized method of moments strategy in which outputs or inputs may be endogenous. We compare two methods in an application to electric utilities.     

企业技术效率的影响分析

 本文以上海市166家大中型企业五年的面板数据为研究对象,设定两种不同的生产函数和两种误差分布,利用随机前沿方法分别进行了技术效率的估计。我们发现不同测算方法的结果差异不大,且对企业的评价具有一致性。结果表明上海市工业企业的技术效率整体水平不高。通过研究影响企业技术效率的外生性因素,发现企业的所有制结构、规模、R&D经费支出与R&D人员投入、资本密集程度和企业的垄断程度等因素都对上海市工业企业的技术效率水平具有显著影响。基于研究结果,我们给出了提高企业技术效率的一些建议。     

退耕还林背景下农业生产技术效率研究——基于陕西省志丹县退耕农户的随机前沿分析

采用超越对数生产函数形式的随机前沿模型,以陕西省志丹县退耕农户的微观面板数据作为实证,对影响退耕农户农业生产技术效率的外生性因素进行了系统分析,得出结论:退耕农户整体农业生产技术效率水平偏低,可通过增加播种面积和农药化肥投入来提升农业生产效率水平;对影响农户农业生产技术效率的微观因素进行测算,可以发现,户主受教育年限、耕地细碎化、人均收入水平和农业收入占家庭总收入比重会给农业生产技术效率带来明显的正效应;农户干部身份、外出务工、贷款行为和人均耕地面积则会在不同程度上恶化农业生产效率水平.在此基础上,提出政策建议以期提高退耕农户的农业生产技术效率水平.     

The “wrong skewness” problem in stochastic frontier models: A new approach

Stochastic frontier models are widely used to measure, e.g., technical efficiencies of firms. The classical stochastic frontier model often suffers from the empirical artefact that the residuals of the production function may have a positive skewness, whereas a negative one is expected under the model, which leads to estimated full efficiencies of all firms. We propose a new approach to the problem by generalizing the distribution used for the inefficiency variable. This generalized stochastic frontier model allows the sample data to have the wrong skewness while estimating well-defined and nondegenerate efficiency measures. We discuss the statistical properties of the model, and we discuss a test for the symmetry of the error term (no inefficiency). We provide a simulation study to show that our model delivers estimators of efficiency with smaller bias than those of the classical model even if the population skewness has the correct sign. Finally, we apply the model to data of the U.S. textile industry for 1958–2005 and show that for a number of years our model suggests technical efficiencies well below the frontier while the classical one estimates no inefficiency in those years.     

Energy performance evaluation of OECD countries using Bayesian stochastic frontier analysis and Bayesian network classifiers

More recently a large amount of interest has been devoted to the use of Bayesian methods for deriving parameter estimates of the stochastic frontier analysis. Bayesian stochastic frontier analysis (BSFA) seems to be a useful method to assess the efficiency in energy sector. However, BSFA results do not expose the multiple relationships between input and output variables and energy efficiency. This study proposes a framework to make inferences about BSFA efficiencies, recognizing the underlying relationships between variables and efficiency, using Bayesian network (BN) approach. BN classifiers are proposed as a method to analyze the results obtained from BSFA.     

Frontier estimation using kernel smoothing estimators with data transformation

In economics, a production frontier function is a graph that shows the maximum output of production units such as firms, industries, or economies, as a function of their inputs. Practically, estimating production frontiers often requires imposition of constraints such as monotonicity or monotone concavity. However, few constrained estimators of production frontier have been proposed in the literature. They are based on simple envelopment techniques which often suffer from lack of precision and smoothness. Motivated by this observation, we propose a smooth constrained nonparametric frontier estimator respecting constraints by considering kernel smoothing estimators from a transformed data. It is particularly appealing to practitioners who would like to use smooth estimates that, in addition, satisfy theoretical axioms of production. The utility of this method is illustrated through application to one real dataset and simulation evidences are also presented to show its superiority over the most known methods.     

欠发达地区技术效率变迁机制研究——以贵州为例证

建立柯布—道格拉斯随机前沿生产函数估算贵州三次产业的技术效率,研究发现:贵州三次产业技术效率变化呈现出边际递减现象.第三产业最具技术效率,但是下降速度也最快;第二产业下降速度较快;第一产业最慢.在将地方政府行为和产权结构纳入技术效率回归模型进行估计后发现:欠发达地区技术效率的提升不仅需要政府加大教育和科技投入,而且需要有效地抑制官员腐败;欠发达地区国有企业对技术效率提升具有正面影响,外资企业的正面影响超过国有企业.     

Stochastic metafrontiers

ABSTRACT

We consider the case of production units arranged into a number of groups. All units within a group choose output–input combinations from the same production possibilities set that is represented by a stochastic frontier model. The metafrontier is the envelope of the group-specific frontiers. We are interested in the metafrontier distance, which is the amount by which the group-specific frontier lies below the metafrontier.

Previous work has measured the metafrontier distance using the deterministic portion of the frontier. In a stochastic frontier model, this is not appropriate. We show how to evaluate the metafrontier distance, and we demonstrate the empirical relevance of this issue.     

Stochastic Production Frontier and Technical Inefficiency: A Sensitivity Analysis

The present paper focuses attention on the sensitivity of technical inefficiency to most commonly used one-sided distributions of the inefficiency error term, namely the truncated normal, the half-normal, and the exponential distributions. A generalized version of the half-normal, which does not embody the zero-mean restriction, is also explored. For each distribution, the likelihood function and the counterpart of the estimator of technical efficiency are explicitly stated (Jondrow, J., Lovell, C. A. K., Materov, I. S., Schmidt, P. ([1982]), On estimation of technical inefficiency in the stochastic frontier production function model, J. Econometrics19:233-238). Based on our panel data set, related to Tunisian manufacturing firms over the period 1983-1993, formal tests lead to a strong rejection of the zero-mean restriction embodied in the half normal distribution. Our main conclusion is that the degree of measured inefficiency is very sensitive to the postulated assumptions about the distribution of the one-sided error term. The estimated inefficiency indices are, however, unaffected by the choice of the functional form for the production function.     

二氧化碳约束下中国主要工业省区的能源技术效率

基于方向性环境距离函数,选择中国13个主要工业省区2002--2009年数据,对C02约束下各省区在规模报酬不变（CRS）和规模报酬可变（VRS）两模型下的能源技术效率进行测算。研究发现：总体上在考虑了CO2约束后,中国主要工业省区在生产前沿上的数目增多与测算所得能源技术效率明显高于不考虑有CO2的情形;VRS下得到的能源技术效率高于CRS下的效率;在最大化减少要素投入和C02的同时,增加期望产出得到的效率值最高,而只考虑个别变量所得效率值表现出普遍的无效率性;加快经济增长方式转变,调整产业结构、能源结构和绿色能源技术开发已成为工业发展的必然选择。     

空间ZISF的估计及蒙特卡罗模拟

在随机前沿模型中引入空间效应和技术无效率项的非连续性并构建了空间零无效率随机前沿模型,使用极大似然估计和JLMS方法得出参数和技术效率的估计。蒙特卡罗模拟表明:(1)逆似然比检验能以较高的准确率识别真实模型;(2)本方法在参数估计和技术效率的估计两方面均表现较好;(3)若真实模型为空间零无效率随机前沿模型但误用了空间随机前沿模型,参数估计和技术效率的估计两方面均表现较差。空间零无效率随机前沿模型有其存在的必要性。     

Bias free measurement of technical efficiency

Technical efficiency, which is a measure of production performance of a firm, has been estimated generally using a primal production frontier. Since the estimation is carried out for a given level of inputs, the efficiency measure includes the effect of 'input-mix' or 'input-allocation' and consequently, the technical efficiency estimate is biased. The objectives of this paper are to gauge the magnitude of 'input-mix' bias in technical efficiency estimate and to suggest a method to measure technical efficiency eliminating the bias. The workability of the suggested method is demonstrated through an empirical analysis using agricultural data from India covering the period 1970-1993.     

Probabilistic frontier regression models for binary type output data

This paper proposes a probabilistic frontier regression model for binary type output data in a production process setup. We consider one of the two categories of outputs as ‘selected’ category and the reduction in probability of falling in this category is attributed to the reduction in technical efficiency (TE) of the decision-making unit. An efficiency measure is proposed to determine the deviations of individual units from the probabilistic frontier. Simulation results show that the average estimated TE component is close to its true value. An application of the proposed method to the data related to the Indian public sector banking system is provided where the output variable is the indicator of level of non-performing assets. Individual TE is obtained for each of the banks under consideration. Among the public sector banks, Andhra bank is found to be the most efficient, whereas the United Bank of India is the least.     

Efficiency Measure from Dynamic Stochastic Production Frontier: Application to Tunisian Textile, Clothing, and Leather Industries

This paper adresses the measurement of technical efficiency of textile, clothing, and leather (TCL) industries in Tunisia through a panel data estimation of a dynamic translog production frontier. It provides a perspective on productivity and efficiency that should be instructive to a developing economy which will face substantial competitive pressure along the gradual economic liberalisation process. The importance of TCL industries in Tunisian manufacturing sector is a reason for obtaining more knowledge of productivity and efficiency for this key industry. Dynamic is introduced to reflect the production consequences of the adjustment costs, which are associated with changes in factor inputs. Estimation of a dynamic error components model is considered using the system generalized method of moments (GMM) estimator suggested by Arellano and Bover (1995), Another look at the instrumental-variable estimation of error-components models, J. Econometrics68:29-51) and Blundell and Bond (Blundell, R., Bond, S. (1998a), Initial conditions and moment restrictions in dynamic panel data models. J. Econometrics87:115-143; Blundell, R., Bond, S. (1998b), GMM estimation with persistent panel data: an application to production functions, Paper presented at the Eighth International Conference on Panel Data, Goteborg University). Our study evaluates the sensitivity of the results, particularly of the efficiency measures, to different specifications. Firm-specific time-invariant technical efficiency is obtained using the Schmidt and Sickles (Schmidt, P., Sickles, R. C. (1984). Production frontiers and panel data. J. Bus. Econ. Stat.2:367-374) approach after estimating the dynamic frontier. We stress the importance of allowing for lags in adjustment of output to inputs and of controlling for time-invariant variables when estimating firm-specific efficiency. The results suggest that the system GMM estimation of the dynamic specification produces the most accurate parameter estimates and technical efficiency measure. Mean efficiency scores is of 68%. Policy implications of the results are outlined.     

Work effort,technical efficiency and productivity growth

This paper develops a model to examine labor-use efficiency associated with the effieciency wage theory and technical effieciency associated with the frontier production model. The generalixed modelcombines these two approaches and derives measures of technical and labor-use efficiency as well as their effects on productivity growth. It also seperates technical inefficiency from industry heterogenity. the model is applied to estimate loss of output due to technical and labor-use inefficiency for 18 two-digit U.S manufacturing industries using time series and cross-sectional data.     

Work effort, technical efficiency and productivity growth

This paper develops a model to examine labor-use efficiency associated with the effieciency wage theory and technical effieciency associated with the frontier production model. The generalixed modelcombines these two approaches and derives measures of technical and labor-use efficiency as well as their effects on productivity growth. It also seperates technical inefficiency from industry heterogenity. the model is applied to estimate loss of output due to technical and labor-use inefficiency for 18 two-digit U.S manufacturing industries using time series and cross-sectional data.     

真实固定效应空间随机前沿模型的贝叶斯估计

忽略个体效应和空间效应会严重干扰效率测算,其中忽略个体效应使得技术无效率项发生偏移,忽略空间相关性导致估计量有偏且不一致。本文基于真实固定效应随机前沿模型（引入了个体效应）,引入因变量和双边误差项的空间滞后项,构建了适用性更佳的真实固定效应空间随机前沿模型。对模型进行组内变化以消除额外参数,使用贝叶斯方法（需推导未知参数的后验分布并执行MCMC抽样）估计参数和技术效率。该方法真正克服了额外参数问题,比同类方法直观、简便。数值模拟结果表明,本文方法对参数、个体截距项及技术无效率项的估计精度均较高,且增加样本容量,估计精度变优。     

Testing the Stochastic Structure of Production: A Flexible Moment-Based Approach

Conventional production function specifications are shown to impose restrictions on the probability distribution of output that cannot be tested with the conventional models. These restrictions have important implications for firm behavior under uncertainty. A flexible representation of a firm's stochastic technology is developed based on the moments of the probability distribution of output. These moments are a unique representation of the technology and are functions of inputs. Large-sample estimators are developed for a linear moment model that is sufficiently flexible to test the restrictions implied by conventional production function specifications. The flexible moment-based approach is applied to milk production data. The first three moments of output are statistically significant functions of inputs. The cross-moment restrictions implied by conventional models are rejected.