Firm exit and technical inefficiency

The purpose of the paper is to examine formally the fundamental implication that technical inefficiency (TI) is related to firm exit. Traditional stochastic frontier models allow for the measurement of TI but do not allow for a direct effect of TI on exit. We propose a model which allows for such effects and consists of a stochastic frontier model, and an additional equation that describes the probability of exit as a function of covariates and TI. Since TI is unobserved, econometric complications arise, and obtaining consistent estimates is non-trivial due to the presence of integrals in the likelihood function. We propose and implement maximum likelihood estimation one step, employing data for 3,404 manufacturing firms in Greece. We find significant positive effects from TI on the probability of exit. We also propose and provide measures of TI that respect the fact that unobserved TI affects the probability of exit and compare them to TI measures from the traditional stochastic frontier model.

Bilateral J-curve between India and her trading partners

This paper aims to test whether a given type of process innovation, namely flexible production technologies (FPTs), contributes to increased firm efficiency. Using one-year firm data from the Portuguese manufacturing industry and applying a parametric stochastic frontier approach, individual technical efficiencies are obtained and their determinants simultaneously estimated, using a single-step procedure recently proposed by Battese and Coelli (1995 Battese, G and Coelli, T. 1995. A model for technical inefficiency effects in a stochastic frontier production function and panel data. Empirical Economics, 20: 325–32.  ). The results support the hypothesis that technological flexibility, measured through the use of FPTs, is important in explaining differences in efficiency. Furthermore, given the specifications of the stochastic frontier function, the null hypothesis that Portuguese firms are fully technically efficient is rejected.     

Differentials at firm level productive capacity realization in Bangladesh food manufacturing: an empirical analysis

This article empirically estimates the firm-specific productive capacity realization (PCR) indices using the stochastic frontier production function and analyses a number of variables explaining realization rates across firms and over time. Following Battese and Coelli (1995 Battese, GE and Coelli, TJ. 1995. A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20: 325–32. [Crossref] , [Google Scholar]) the stochastic frontier production function is used to estimate capacity output and thereby PCR. Using the Firm level panel data from Bangladesh food manufacturing, the results show that capacity realization rates widely vary across firms and over time. The average rate of realization is about 65% implying that most of the firms are producing away from their full production capacity. This article also identifies several firm-specific and policy-related variables explaining capacity realization. The results show that firm size (SZE) and outward orientation (OPN) have positive while capital intensity (CNSTY), market structure (MSTRE) and effective rate of assistance (ERA) have negative impact on realization rates. Strikingly, both policy-related variables are statistically insignificant. Sensitivity analysis using the ‘extreme bound analysis’ also confirms the fragility (insignificance) of these two variables. Excessive support to firms and piecemeal liberalization reform may be attributed to these results. Thus, further reform of the domestic and trade policies are suggested to ensure competition and competitiveness of the manufacturing sector and of the country.     

Modelling Exogenous Variables in Human Capital Formation through a Heteroscedastic Stochastic Frontier

The objective of this paper is to suggest the use of a stochastic frontier model in which the inefficiency component is heteroscedastic in the measurement of technical efficiency in Human Capital Formation in the Italian University System. The heteroscedastic frontier model enables one to consider the effect of students’ individual characteristics and the influences of the resources and organization of the specific faculty on efficiency. The suggested model is applied to the case of Florence University graduates. The results show that the model specification is strongly supported by the data. Moreover, the suggested specification explains variation in technical efficiency in terms of graduate-specific factors. The technical efficiency scores obtained are comparable across faculties.

Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers

In previous studies, measures of technical inefficiency effects derived from stochastic production frontiers have been estimated from residuals which are sensitive to specification errors. This study corrects for this inaccuracy by extending the doubly heteroscedastic stochastic cost frontier suggested by Hadri (1999) to the model for technical inefficiency effects. This model is a stochastic frontier production function for panel data as proposed by Battese and Coelli (1995). The study uses, for illustration of the techniques, data on 101 mainly cereal farms in England. We find that the correction for heteroscedasticity is supported by the data. Both point estimates and confidence intervals for technical efficiencies are provided. The confidence intervals are constructed by extending the “Battese-Coelli” method reported by Horrace and Schmidt (1996) by allowing the technical inefficiency to be time varying and the disturbance terms to be heteroscedastic. The confidence intervals reveal the precision of technical efficiency estimates and show the deficiencies of making inferences based exclusively on point estimates. First version received: March 2000/Final version received: Oct. 2001 RID="*" ID="*"  The authors are grateful to the Economic and Social Research Council for access to their Data Archive which has provided the data for this research. We are indebted to Badi Baltagi and two anonymous referees for their helpful comments and suggestions. The usual caveat applies.     

Efficiency and Equity in School Funding: A Case Study for Kansas

This study measures cost inefficiency of Kansas public school districts and applied both mathematical programming and stochastic frontier approach. The empirical study uses two-stage data envelopment analysis model and the cost inefficiency effects model proposed by Battese and Coelli (Empirical Economics 24:325–332, 1995) and applied to a panel data. The results found mean inefficiencies from these two models are very close. The results indicate that Kansas school districts, on average, exhibit cost inefficiency in their operations, however, there is a tendency for inefficiencies to decline over time. The study does not find any strong evidence for lower efficiency due to lower expenditure per-pupil. Instead, we found inconclusive evidences where lower efficiency for certain school districts could be assigned to unfavorable environmental cost conditions.

Measurement of technical and allocative efficiencies using a CES cost frontier: a benchmarking study of Japanese transmission-distribution electricity

This paper estimates the technical and allocative inefficiencies of the transmission-distribution sector of Japanese electric utilities using a panel data during the 1981–1998 period. A stochastic production frontier of the CES form is jointly estimated with input demand equations. Taking advantage of the self-duality, we retrieve the cost frontier by which the impacts of technical and allocative inefficiencies on costs and input demands are measured. The estimated elasticity of substitution is significantly different from unity in favor of the CES specification over the Cobb–Douglas. The results show that observed costs are 9 to 48% higher than the efficient level; technical inefficiency raises costs by 1 to 28%, while allocative inefficiency does so by 8 to 30%. Although their impacts on costs are similar, technical inefficiency more fluctuates so the differences in the performance of utilities are mainly due to technical inefficiency. We also find a substantial over-utilization of capital for all utilities.

Impact of the adoption of information and communication technologies on firm efficiency in the Tunisian manufacturing sector

This paper aims at measuring the impact of information and communication technology use on the efficiency of the Tunisian manufacturing sector at the firm level within a simple theoretical framework. We are using a firm-level panel data for the manufacturing sector in Tunisia to investigate whether adoption of ICT influences efficiency in factor use. The analysis is conducted through the use of a parametric method to measure technical efficiency. We estimate a stochastic production frontier and the relationship aims to explain technical efficiency differentials in a single stage as suggested by Battese and Coelli [Battesse, G.E, Coelli, T.J. (1995). A model for technical inefficiency in a stochastic frontier production function for panel data. Empirical Economics, 20, 325–332].The results have confirmed the presence of positive returns to ICT capital. We have found that the impact of ICT on efficiency is strong. Our results also suggest that it is important to carefully control for human capital related characteristics of employment when studying the effect of ICT. The evidence shows that achieving benefits from investment in ICT requires complementary investments and changes in human capital. This means that the combined use of ICT and human capital in a firm would enhance its efficiency beyond the direct effects of these factors taken alone.     

Technical efficiency analysis correcting for biases from observed and unobserved variables: an application to a natural resource management project

This article brings together the stochastic frontier framework with impact evaluation methodology to compare technical efficiency (TE) across treatment and control groups using cross-sectional data associated with the MARENA Program in Honduras. A matched group of beneficiaries and control farmers is determined using propensity score matching techniques to mitigate biases stemming from observed variables. In addition, possible self-selection arising from unobserved variables is addressed using a selectivity correction model for stochastic frontiers recently introduced by Greene (J Prod Anal 34:15?C24, 2010). The results reveal that average TE is consistently higher for beneficiary farmers than the control group while the presence of selectivity bias cannot be rejected. TE ranges from 0.67 to 0.75 for beneficiaries and from 0.40 to 0.65 for the control depending on whether biases were controlled or not. The TE gap between beneficiaries and control farmers decreases by implementing the matching technique and the sample selection framework decreases this gap even further. The analysis also suggests that beneficiaries do not only exhibit higher TE but also higher frontier output.     

Allocative and scale efficiency among maize farmers in Zambia: a zero efficiency stochastic frontier approach

The commonly used stochastic frontier model assumes that all firms are inefficient. In this specification, inefficiency is non-negative, and the probability of inefficiency being exactly zero is also zero. To the extent that efficiency varies widely across farms in under-developed economies, it is important to employ techniques that account for both inefficiency and full efficiency to ensure unbiased efficiency estimates. In this study, we employ a zero-inefficiency stochastic frontier model to examine allocative efficiency and scale economies, as well as key determinants of efficiency among Zambian maize farmers. The results show that, unlike the stochastic frontier model, the zero-inefficiency stochastic frontier model successfully allows for both fully efficient and inefficient firms to be accounted for in the estimation procedure. The estimates also reveal the presence of scale economies, with the zero-inefficiency stochastic frontier model better predicting scale efficiency compared to the stochastic frontier model. The findings also show that inefficiency is explained by the level of education, access to extension services, distance to markets and access to credit.     

Maximum entropy: a stochastic frontier approach for electricity distribution regulation

The literature on incentive-based regulation in the electricity sector indicates that the size of this sector in a country constrains the choice of frontier methods as well as the model specification itself to measure economic efficiency of regulated firms. The aim of this study is to propose a stochastic frontier approach with maximum entropy estimation, which is designed to extract information from limited and noisy data with minimal statements on the data generation process. Stochastic frontier analysis with generalized maximum entropy and data envelopment analysis—the latter one has been widely used by national regulators—are applied to a cross-section data on thirteen European electricity distribution companies. Technical efficiency scores and rankings of the distribution companies generated by both approaches are sensitive to model specification. Nevertheless, the stochastic frontier analysis with generalized maximum entropy results indicate that technical efficiency scores have similar distributional properties and these scores as well as the rankings of the companies are not very sensitive to the prior information. In general, the same electricity distribution companies are found to be in the highest and lowest efficient groups, reflecting weak sensitivity to the prior information considered in the estimation procedure.

     

Real option value and random jumps: application of a simulation model

This article studies how sensitive real option valuations are to incorrect assumptions about the stochastic process followed by the state variables. We design a valuation model which combines Monte Carlo simulation and dynamic programming and provides an appropriate framework to evaluate the effect of estimation errors on both the value of real options and their critical frontier. Although the model is flexible enough to value American-type options contingent on a wide range of stochastic processes, we focus on the analysis of the effect of stochastic jumps. We apply our model to the valuation of an investment in the car parts industry documented in previous literature. Our results clearly show that underestimating this type of jumps might lead to substantial misjudgements in a firm's decision-making processes. For instance, it may lead to profitable projects being rejected when jump diffusion is low, or negative expanded net present value projects being accepted.     

The impact of knowledge accumulation and geographical spillovers on productivity and efficiency: The case of U. S. shipbuilding during WWII

This paper examines the productivity and efficiency experience of World War II Liberty ship builders using two complementary paradigms which can be viewed as alternative specifications of the endogenous growth model introduced by Romer (1986) and the stochastic frontier production model introduced by Aigner, Lovell, and Schmidt (1977). We develop modifications in the endogenous growth model to allow for learning as well as spatial spillovers by relating productivity growth to cumulative productive experience (the ‘learning curve’) and to worker experience as it is transferred and utilized across different geographical regions. We also consider the relative impact of both proximal and distant simultaneous production on productivity growth. We then utilize a framework in which the efficiency component of productivity growth is explicitly considered using a stochastic frontier model wherein contributions to productivity growth introduced in the endogenous growth model are formally modeled as determinants of efficiency change.     

Localized innovation, localized diffusion and the environment: an analysis of reductions of CO2 emissions by passenger cars

We investigate technological change with regard to CO₂ emissions by passenger cars, using a Free Disposal Hull methodology to estimate technological frontiers. We have a sample of cars available in the UK market in the period 2000–2007. Our results show that the rates of technological change (frontier movement) and diffusion (distance to frontier at the car brand level) differ substantially between segments of the car market. We conclude that successful policies should be aimed at the diffusion of best-practice technology, and take account of the different potential for further progress between different segments of the market (e.g. diesel vs. gasoline engines and small vs. large engines).

Bubbles in Stochastic Economies: Can They Cure Overaccumulation of Capital?

It is well known that bubbles possess the potential to increase economic welfare due to a reduction of capital accumulation in deterministic overlapping generations economies that are in a dynamically inefficient state. However, actual economies are stochastic, where the concept of dynamic efficiency has turned out to be a complex issue. This paper contributes in two ways. First, the model presented in this paper establishes that dynamic inefficiency is not a necessary condition for deterministic bubbles in a stochastic economy. Second, a simulation shows that although bubbles are unable to persist in the stochastic steady state, they can still cure overaccumulation of capital for a time long enough to cover agents relevant time horizon.     

A model for technical inefficiency effects in a stochastic frontier production function for panel data

A stochastic frontier production function is defined for panel data on firms, in which the non-negative technical inefficiency effects are assumed to be a function of firm-specific variables and time. The inefficiency effects are assumed to be independently distributed as truncations of normal distributions with constant variance, but with means which are a linear function of observable variables. This panel data model is an extension of recently proposed models for inefficiency effects in stochastic frontiers for cross-sectional data. An empirical application of the model is obtained using up to ten years of data on paddy farmers from an Indian village. The null hypotheses, that the inefficiency effects are not stochastic or do not depend on the farmer-specific variables and time of observation, are rejected for these data.     

Modeling stochastic innovation races

We consider a firm moving towards a stochastic final destination to be chosen from a discrete set after a decision period. The decision period itself may be deterministic or stochastic. We assume the firm can move at variable innovation (R&D) speed associated with a monotone nondecreasing variable cost, and it can also stop and move anywhere. There is a fixed cost per time unit “carried” by the firm as well, associated with keeping at the knowledge (technology) frontier. We investigate various types of the firm's optimal trajectory in the R&D race during the decision period. The model is adapted and applied to racing behaviour in the Japanese telecommunication industry.     

Technology Adoption, Human Capital, and Growth Theory

The paper explores a model in which growth is determined by a combination of human capital and technology adoption. At the heart of the model is the notion of "contiguous knowledge"—the idea that knowledge spreads out a certain distance. Because of this property of knowledge, a country can adopt existing technology only when it is sufficiently close to the technological frontier. Unlike the neoclassical growth model, the proposed model predictions are pessimistic for countries that are far away from the frontier. The model is thus able to account both for rapid growth episodes and economic stagnation.     

A Spatial Stochastic Frontier Model with Spillovers: Evidence for Italian Regions

Efficiency measurement using stochastic frontier models is well established in applied econometrics. However, no published work seems to be available on efficiency analysis using spatial data dealing with possible spatial dependence between regions. This article considers a stochastic frontier model with decomposition of inefficiency into an idiosyncratic and a spatial, spillover component. Exact posterior distributions of parameters are derived, and computational schemes based on Gibbs sampling with data augmentation are proposed to conduct simulation‐based inference and efficiency measurement. The new method is illustrated using production data for Italian regions (1970–1993). Clearly, further theoretical and empirical research on the subject would be of great interest.     

Estimation of nonparametric inefficiency effects stochastic frontier models with an application to British manufacturing

The purpose of this paper is to propose a simple stochastic frontier model with a non-parametric specification for covariates affecting the mean of technical inefficiency. We derive a simple two-step semiparametric estimation procedure to estimate the frontier parameters as well as the mean of the technical inefficiency. The consistency of the estimator and its asymptotic normality are shown. The proposed method is illustrated using a large panel data set of British manufacturing firms.