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.     

A General Method of Deriving the Inefficiencies of Banks from a Profit Function

This article develops a new method of estimating inefficiencies in joint production and shows that unlike the approaches utilized in the previous studies of inefficiency, this method maintains a consistent relationship between the error term of a profit function and the error terms of its price derivatives. A useful by-product of the method is a proof of a Hotelling-like lemma that relates stochastic input demand and output supply functions to stochastic profit functions. While the previous studies fit a single frontier to data on all firms, this paper estimates a frontier unique to every observed firm to allow each one to have a different potential of achieving maximal levels of profit. The new method is applied in the analysis of annual data, 1984–1989, for U.S. commercial banks. Both the analytical and numerical results of the paper show that the residual that the previous studies attribute to inefficiency includes the effects of excluded variables and of inaccuracies in the specified functional forms. Once accurate estimates of these effects are subtracted from the residual, the distortions in the measured inefficiencies should be considerably reduced. Consequently, this article considers how such estimates might be obtained.     

Nonparametric least squares methods for stochastic frontier models

When analyzing productivity and efficiency of firms, stochastic frontier models are very attractive because they allow, as in typical regression models, to introduce some noise in the Data Generating Process . Most of the approaches so far have been using very restrictive fully parametric specified models, both for the frontier function and for the components of the stochastic terms. Recently, local MLE approaches were introduced to relax these parametric hypotheses. In this work we show that most of the benefits of the local MLE approach can be obtained with less assumptions and involving much easier, faster and numerically more robust computations, by using nonparametric least-squares methods. Our approach can also be viewed as a semi-parametric generalization of the so-called “modified OLS” that was introduced in the parametric setup. If the final evaluation of individual efficiencies requires, as in the local MLE approach, the local specification of the distributions of noise and inefficiencies, it is shown that a lot can be learned on the production process without such specifications. Even elasticities of the mean inefficiency can be analyzed with unspecified noise distribution and a general class of local one-parameter scale family for inefficiencies. This allows to discuss the variation in inefficiency levels with respect to explanatory variables with minimal assumptions on the Data Generating Process.     

Measuring the impact of restructuring and country-specific factors on the efficiency of post-crisis East Asian banking systems: Integrating DEA with SFA

This paper investigates the relationship between post-crisis bank restructuring, country-specific conditions and bank efficiency in Asian countries from 1997 to 2001 using an approach that integrates data envelopment analysis and stochastic frontier analysis. We focus on restructuring measures related to bank ownership. The results indicate that although domestic mergers produce more efficient banks, overall, restructuring does not lead to more efficient banking systems. Banking system inefficiencies are mostly attributed to country-specific conditions, particularly, high interest rates, concentrated markets and economic development.     

Cost efficiency and value driver analysis of insurers in an emerging economy

This study investigated cost inefficiencies and its relationship with value drivers of insurers in United Arab Emirates (UAE). The study revealed that there were 21–33% cost inefficiencies in these insurers under different model specifications of stochastic frontier and DEA; value drivers such as lower leverage risk, lower capital risk significantly improved cost efficiencies consistent with Basel II norms; ROE positively influenced cost efficiencies with further trade off between increased profit margin, decreased asset utilization and/or reduced equity multiplier by the insurer managements to achieve a target‐ROE; and the trend of cost efficiency was improving during 2000–2004. The study suggests that stock insurers could overcome their cost inefficiencies through adoption of efficient measures such as risk mapping of clients, risk prioritization besides ALM techniques. The study has direct implications for individual and institutional investors in making their portfolio investment decisions in insurance sector, policymakers, and regulators to closely monitor inefficient insurers consistent with Basel II norms. Copyright © 2008 John Wiley & Sons, Ltd.     

Inefficiency Spillovers in Five OECD Countries: An Interindustry Analysis

Empirical studies have widely demonstrated that real-world activities are rarely on their production frontier. Hence, an obvious concern arises towards the detection of inefficiencies affecting sectoral performances. The current literature and practice have widely explored the sources of inefficiency internal to decision-making units. This paper argues that a major role is played by external effects due to inefficiency spillovers propagating through interindustry transactions. In order to take this mechanism into account, the paper suggests assessing sectoral performances by a system approach that makes use of shadow prices of intermediate inputs. Our approach is able to disentangle sectoral inefficiencies into internal sectoral inefficiencies and inefficiencies imported from other sectors. The latter component is due to inefficiency spillovers that appear to be empirically relevant in all sectors of five OECD countries.     

An Integrated Assessment of Productivity and Efficiency Impacts of Information Technology Investments: Old Data,New Analysis and Evidence

We reexamine the Information Technology (IT) productivity paradox from the standpoints of theoretical basis, measurement issues and potential inefficiency in IT management. Two key objectives are: (i) to develop an integrated microeconomic framework for IT productivity and efficiency assessment using developments in production economics, and (ii) to apply the framework to a dataset used in prior research with mixed results to obtain new evidence regarding IT contribution. Using a stochastic frontier with a production economics framework involving the behavioral assumptions of profit maximization and cost minimization, we obtain a unified basis to assess both productivity and efficiency impacts of IT investments. The integrated framework is applied to a manufacturing database spanning 1978–1984. While previous productivity research with this dataset found mixed results regarding the contribution from IT capital, we show the negative marginal contribution of IT found in an important prior study is attributable primarily to the choices of the IT deflator and modeling technique. Further, by ignoring the potential inefficiency in IT investment and management, studies that have reported positive results may have significantly underestimated the true contribution of IT. This positive impact of IT is consistent across multiple model specifications, estimation techniques and capitalization methods. The stochastic production frontier analysis shows that while there were significant technical, allocative and scale inefficiencies, the inefficiencies reduced with an increase in the IT intensity. Given that the organizational units in our sample increased their IT intensity during the time period covered by the study, management was taking a step in the right direction by increasing the IT share of capital inputs. Our results add to a small body of MIS literature which reports significant positive returns from IT investments.     

Cost efficiency of insurance firms in Ghana

The huge infrastructural deficit in Africa requires the establishment of an efficient insurance industry in the pursuance of economic development. Unfortunately, global statistics reveal low patronage of insurance in developing countries, thus making its impact limited in the region. To position the industry for economic development, this study utilizes the stochastic frontier technique to undertake a thorough analysis on the cost efficiency of insurers from the perspective of developing economies using Ghana as a case study. The results on the 30 insurers studied from 2005 to 2014 indicate that insurers in Ghana operate with about 53.8% average cost inefficiency. This stands to confirm the long existed low performance perception of Ghanaians about the industry. Factors identified to explain the cost inefficiencies were firm size, market share, capitalization, reinsurance, regulation, and business type. Several policy recommendations that can help boost the cost efficiency of insurers were derived from the results.     

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.     

Stochastic frontier models with multiple time-varying individual effects

This paper proposes a flexible time-varying stochastic frontier model. Similarly to Lee and Schmidt [1993, In: Fried H, Lovell CAK, Schmidt S (eds) The measurement of productive efficiency: techniques and applications. Oxford University Press, Oxford], we assume that individual firms’ technical inefficiencies vary over time. However, the model, which we call the “multiple time-varying individual effects” model, is more general in that it allows multiple factors determining firm-specific time-varying technical inefficiencies. This allows the temporal pattern of inefficiency to vary over firms. The number of such factors can be consistently estimated. The model is applied to data on Indonesian rice farms, and the changes in the efficiency rankings of farms over time demonstrate the model’s flexibility.

Panel estimators and the identification of firm-specific efficiency levels in parametric,semiparametric and nonparametric settings

The paper analyzes a number of competing approaches to modeling efficiency in panel studies. The specifications considered include the fixed effects stochastic frontier, the random effects stochastic frontier, the Hausman–Taylor random effects stochastic frontier, and the random and fixed effects stochastic frontier with an AR(1) error. I have summarized the foundations and properties of estimators that have appeared elsewhere and have described the model assumptions under which each of the estimators have been developed. I discuss parametric and nonparametric treatments of time varying efficiency including the Battese–Coelli estimator and linear programming approaches to efficiency measurement. Monte Carlo simulation is used to compare the various estimators and to assess their relative performances under a variety of misspecified settings. A brief illustration of the estimators is conducted using U.S. banking data.     

Finite sample evidence on the performance of stochastic frontier models using panel data

Most stochastic frontier models have focused on estimating average productive efficiency across all firms. The failure to estimate firm-specific effiicency has been regarded as a major limitation of previous stochastic frontier models. In this paper, we measure firm-level efficiency using panel data, and examine its finite sample distribution over a wide range of the parameter and model space. We also investigate the performance of the stochastic frontier approach using three estimators: maximum likelihood, generalized least squares and dummy variables (or the within estimator). Our results indicate that the performance of the stochastic frontier approach is sensitive to the form of the underlying technology and its complexity. The results appear to be quite stable across estimators. The within estimatoris preferred, however, because of weak assumptions and relative computational ease.The refereeing process of this paper was handled through J. van den Broeck.     

Decomposition of technical efficiency under fixed proportion technologies: an application of data envelopment analysis

In this paper, we extend the four-component stochastic frontier model to allow for global spatial dependence via the endogenous spatial autoregressive variable. Our proposed model is more general than the model considered by (Glass et al., 2016) in the sense that we include a random effect as well as a permanent efficiency component. With the spatial autoregressive specification, our model is able to capture the asymmetric efficiency spillovers and also decompose the persistent/transient inefficiencies into direct and indirect efficiencies. Moreover, we also investigate the marginal effects of the exogenous variables on the persistent/transient efficiency. We suggest a maximum simulated likelihood method to estimate the frontier parameters of the model, and we predict the efficiencies using the simulated estimator. Monte Carlo simulations reveal that the suggested estimator performs well in finite samples. An empirical application is considered to illustrate the usefulness of our proposed model and method.

     

Consistent estimation of the fixed effects stochastic frontier model

In this paper we consider a fixed-effects stochastic frontier model. That is, we have panel data, fixed individual (firm) effects, and the usual stochastic frontier analysis (SFA) composed error.     

Estimation of the two-tiered stochastic frontier model with the scaling property

The two-tiered stochastic frontier model has enjoyed success across a range of application domains where it is believed that incomplete information on both sides of the market leads to surplus which buyers and sellers can extract. Currently, this model is hindered by the fact that estimation relies on very restrictive distributional assumptions on the behavior of incomplete information on both sides of the market. However, this reliance on specific parametric distributional assumptions can be eschewed if the scaling property is invoked. The scaling property has been well studied in the stochastic frontier literature, but as of yet, has not been used in the two-tier frontier setting.     

Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency

This paper analyzes the productivity of farms across 370 municipalities in the Center-West region of Brazil. A stochastic frontier model with a latent spatial structure is proposed to account for possible unknown geographical variation of the outputs. The paper compares versions of the model that include the latent spatial effect in the mean of output or as a variable that conditions the distribution of inefficiency, include or not observed municipal variables, and specify independent normal or conditional autoregressive priors for the spatial effects. The Bayesian paradigm is used to estimate the proposed models. As the resultant posterior distributions do not have a closed form, stochastic simulation techniques are used to obtain samples from them. Two model comparison criteria provide support for including the latent spatial effects, even after considering covariates at the municipal level. Models that ignore the latent spatial effects produce significantly different rankings of inefficiencies across agents.

Stochastic frontier models with network selectivity

Worker peer-effects and managerial selection have received limited attention in the stochastic frontier analysis literature. We develop a parametric production function model that allows for worker peer-effects in output and worker-level inefficiency that is correlated with a manager’s selection of worker teams. The model is the usual “composed error” specification of the stochastic frontier model, but we allow for managerial selectivity (endogeneity) that works through the worker-level inefficiency term. The new specification captures both worker-level inefficiency and the manager’s ability to efficiently select teams to produce output. As the correlation between the manager’s selection equation and worker inefficiency goes to zero, our parametric model reduces to the normal-exponential stochastic frontier model of Aigner et al. (1977) with peer-effects. A comprehensive application to the NBA is provided.     

Estimation and testing of stochastic frontier models using variational Bayes

We show how a wide range of stochastic frontier models can be estimated relatively easily using variational Bayes. We derive approximate posterior distributions and point estimates for parameters and inefficiency effects for (a) time invariant models with several alternative inefficiency distributions, (b) models with time varying effects, (c) models incorporating environmental effects, and (d) models with more flexible forms for the regression function and error terms. Despite the abundance of stochastic frontier models, there have been few attempts to test the various models against each other, probably due to the difficulty of performing such tests. One advantage of the variational Bayes approximation is that it facilitates the computation of marginal likelihoods that can be used to compare models. We apply this idea to test stochastic frontier models with different inefficiency distributions. Estimation and testing is illustrated using three examples.     

Economic Efficiency and Productivity Growth in the Post-Privatization Chilean Hydroelectric Industry

Chiles hydroelectric industry was privatized in 1985, but required to operate within a regulatory framework designed to achieve a competitive outcome. A centralized dispatch center was established to ensure production at minimum cost, subject to constraints on minimum release and minimum reservoir stock. A reluctance to rapidly reduce the industry work force may also have existed. We develop a constrained cost-minimization model for thermal and hydro generation to obtain the shadow price of water and to determine the qualitative effect of these constraints on allocative efficiency. Using panel data from 1986–1997, we assess the economic efficiency of the hydro industry by estimating a stochastic distance frontier and price equations from the dual cost-minimization problem. We find dramatic increases in technical change and productivity change, with positive efficiency change for all years but the last. We also observe a dramatic decline in allocative inefficiencies over our sample period. The share of hydro generation from run-of-river and thermal plants relative to reservoir plants has increased, presumably in reaction to the water release and reservoir stock constraints, reducing the relative over-utilization of capital to water from the pre-1985 regime. Further, the over-utilization of labor to capital and water has fallen over time. However, considerable allocative inefficiencies remain, consistent with our finding of industry-wide scale economies. Substantial cost savings would result if technical and allocative efficiency were eliminated.JEL Classification: L94, D24