Identifying technically efficient fishing vessels: a non‐empty,minimal subset approach

Stochastic frontier models are often employed to estimate fishing vessel technical efficiency. Under certain assumptions, these models yield efficiency measures that are means of truncated normal distributions. We argue that these measures are flawed, and use the results of Horrace ( 2005 ) to estimate efficiency for 39 vessels in the Northeast Atlantic herring fleet, based on each vessel's probability of being efficient. We develop a subset selection technique to identify groups of efficient vessels at pre‐specified probability levels. When homogeneous production is assumed, inferential inconsistencies exist between our methods and the methods of ranking the means of the technical inefficiency distributions for each vessel. When production is allowed to be heterogeneous, these inconsistencies are mitigated. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimation of stochastic frontier production functions with input-oriented technical efficiency

This paper deals with estimation of input-oriented (IO) technical inefficiency using a stochastic production frontier model. Econometrically the model is similar to a class of models that arise in specifying technical inefficiency in cost-minimizing and profit-maximizing frameworks. The standard maximum likelihood (ML) method that is used to estimate output-oriented (OO) technical efficiency cannot be applied to estimate these models. We use a simulated ML approach to estimate the IO production function and compare results from the IO and OO models, mainly to emphasize the point that estimated efficiency, returns to scale, technical change, etc., differ depending on whether one uses the model with IO or OO technical inefficiency.     

Beyond profitability: effects of acquisitions on technical efficiency in the Italian pasta industry

Unlike traditional studies on the impact of ownership changes—which use either profitability measures or stock prices—this paper investigates the impact of acquisitions on acquired firms' technical efficiency. Using a panel of Italian firms in the pasta industry for the 1981–1997 period, I estimate a stochastic production frontier with exogenous factors affecting efficiency in a translog specification with non‐neutral technical progress. The main result is that acquired firms experience, within the 6 years period following the acquisition, an increase in technical efficiency of the order of 10%. This result is statistically significant and proves to be robust with respect to the inclusion of size and calendar year effects as explanatory variables of firms' inefficiency. These findings contribute to the debate on the welfare gains of ownership changes by providing evidence that mergers and acquisitions lead to cost savings, due to the reduction of acquired firms' X‐inefficiency. Copyright © 2002 John Wiley & Sons, Ltd.     

Market Concentration and Multifaceted Productive Efficiency

Developing the analytical framework of the decision making process of a possible entrant, a reduced form system equations model is estimated in order to examine the market concentration – productive efficiency relationship in an endogeneity context. Technical and scale efficiency estimates are obtained from an inter-industry stochastic production frontier using a panel dataset regarding the seven most energy intensive manufacturing industries in Greece over the period 1980–96. Several new versions of the concentration – efficiency relationship, may be derived from the alternatives of the entrant considering the possible conduct character of incumbents’ technical efficiency and excess capacity, which is depicted on their scale efficiency, on market concentration.     

Multiple Comparisons with the Best: Bayesian Precision Measures of Efficiency Rankings

A large literature measures the allocative and technical efficiency of a set of firms using econometric techniques to estimate stochastic production frontiers or distance functions. Typically, researchers compute only the precision of individual efficiency rankings. Recently, Horrace and Schmidt (Journal of Applied Economics 15, 1–26, 2000) have applied sampling theoretic statistical techniques known as multiple comparisons with a control (MCC) and multiple comparisons with the best (MCB) to make statistical comparisons of efficiency rankings. As an alternative, this paper offers a Bayesian multiple comparison procedure that we argue is simpler to implement, gives the researcher increased flexibility over the type of comparison, and provides greater, and more intuitive, information content. For these methods and a parametric bootstrap technique, we carry out multiple comparisons of technical efficiency rankings for a set of U.S. electric generating firms, estimated using a distance function framework. We find that the Bayesian method provides substantially more precise inferences than obtained using the MCB and MCC methods.Jel Classification: C11, C32, D24.     

Influences of the Business Environment on Manufacturing Firms Technical Efficiencies: The Côte d’Ivoire Case

An unbalanced panel is used to estimate technical and managerial efficiency levels of manufacturing firms in Côte d’Ivoire. A stochastic frontier production model with non-neutral effects on technical efficiency of the business environment variables is specified. This specification allows to evaluate and to compare technical efficiencies and efficiency levels net of business environment influences. In order to determine net efficiency levels in the non-neutral case, a practical method based on the definition of an artificial environment is proposed. Results suggest that informal firms are less technically efficient than formal firms whereas their managerial performances are closed to those of formal firms.     

Mix Efficiency in a Multi-species Fishery

A feature of fisheries that distinguishes them from most other industries is the level of control imposed on the production process. Previous studies have identified inefficiency in fisheries that is directly related to the management restrictions. The development of Slack-based measure (SBM) models allows the effects of management distortions to be further investigated through consideration of input and output mix efficiency. In this paper, the mix efficiency of a fleet operating in a multispecies fishery is examined. The results indicate that inefficiencies exist in the mix of inputs, which have developed as a consequence of the management restrictions imposed.     

Technical efficiency with multi-output,heterogeneous production: a latent class,distance function model of english football

This study combines the output distance function approach with a latent class model to estimate technical efficiency in English football in the presence of productive heterogeneity within a stochastic frontier analysis framework. The distance function approach allows the researcher to estimate technical efficiency including both on-field and off-field production, which is important in the case of English football where clubs are generally thought to maximize something other than profit. On-field production is measured using total league points, and off-field production is measured using total revenue. The data set consists of 2177 club-level observations on 88 clubs that competed in the four divisions of professional football in England over the 29-season period from 1981/82 to 2009/10. The results show evidence of three separate productivity classes in English football. As might be expected, technical efficiency estimated using the latent class model is, on average, higher than technical efficiency using an alternative method which confines heterogeneity to the intercept coefficient. Specifically, average efficiency for the sample is 87.3 and 93.2% for the random-intercept model and the latent class model respectively.     

Characterizing Managerial Skill and Technical Efficiency in a Fishery

Researchers have long recognized that entrepreneurial or managerial skill is a major determinant of productivity or reason why production among firms varies. Yet, except for a few studies, differences in productivity and output levels are usually attributed to plant configuration or scale. More important, there appears to have been few attempts to relate technical efficiency to managerial skill. Utilizing a stochastic production frontier, we examine the relationship between technical efficiency and characteristics of skill such as experience and education in a fishery. Although we can not determine threshold or essential levels of experience and education, substitution possibilities are found to exist between years of experience and education levels. Additional analysis of efficiency for two captains of the same background and experience reveals that additional characteristics need to be considered in the examination of skipper skill or the good-captain hypothesis.     

Count data stochastic frontier models, with an application to the patents–R&D relationship

This article introduces a new count data stochastic frontier model that researchers can use in order to study efficiency in production when the output variable is a count (so that its conditional distribution is discrete). We discuss parametric and nonparametric estimation of the model, and a Monte Carlo study is presented in order to evaluate the merits and applicability of the new model in small samples. Finally, we use the methods discussed in this article to estimate a production function for the number of patents awarded to a firm given expenditure on R&D.     

Analyzing China's productivity growth: Evidence from manufacturing industries

This article examines the growth attributes of manufacturing industries in China for the sample period of 1999–2007. The output growth of manufacturing industries classified under four groups and four regions is decomposed into four components of input growth, scale effect, technical progress, and technical efficiency change. A stochastic frontier model is applied to the translog production function to estimate technical efficiency. Despite the conventional argument that input growth and technical progress are important factors to output growth, the empirical findings show a significant scale effect but a weak technical efficiency change. The contribution to growth from labor has been replaced by human and physical capitals. Structural transformation in the industrial sector is evident, so as regional imbalances.     

Technical efficiency measures for dairy farms using panel data: A comparison of alternative model specifications

This article examines the impact of fixed effects production functions vis-à-vis stochastic production frontiers on technical efficiency measures. An unbalanced panel consisting of 96 Vermont dairy farmers for the 1971–1984 period was used in the analysis. The models examined incorporated both time-variant and time-invariant technical efficiency. The major source of variation in efficiency levels across models stemmed from the assumption made concerning the distribution of the one-sided term in the stochastic frontiers. In general, the fixed effects technique was found superior to the stochastic production frontier methodology. Despite the fact that the results of various statistical tests revealed the superiority of some specifications over others, the overall conclusion of the study is that the efficiency analysis was fairly consistent throughout all the models considered.     

Non-parametric, unconditional quantile estimation for efficiency analysis with an application to Federal Reserve check processing operations

This paper examines the technical efficiency of US Federal Reserve check processing offices over 1980–2003. We extend results from Park et al. [Park, B., Simar, L., Weiner, C., 2000. FDH efficiency scores from a stochastic point of view. Econometric Theory 16, 855–877] and Daouia and Simar [Daouia, A., Simar, L., 2007. Nonparametric efficiency analysis: a multivariate conditional quantile approach. Journal of Econometrics 140, 375–400] to develop an unconditional, hyperbolic, α-quantile estimator of efficiency. Our new estimator is fully non-parametric and robust with respect to outliers; when used to estimate distance to quantiles lying close to the full frontier, it is strongly consistent and converges at rate root-n, thus avoiding the curse of dimensionality that plagues data envelopment analysis (DEA) estimators. Our methods could be used by policymakers to compare inefficiency levels across offices or by managers of individual offices to identify peer offices.     

Input- and Output-Oriented Technical Efficiency of Ukrainian Collective Farms, 1989–1992: Bayesian Analysis of a Stochastic Production Frontier Model

We propose estimation of a stochastic production frontier model within a Bayesian framework to obtain the posterior distribution of single-input-oriented technical efficiency at the firm level. All computations are carried out using Markov chain Monte Carlo methods. The approach is illustrated by applying it to production data obtained from a survey of Ukrainian collective farms. We show that looking at the changes in single-input-oriented technical efficiency in addition to the changes in output-oriented technical efficiency improves the understanding of the dynamics of technical efficiency over the first years of transition in the former Soviet Union.     

A Switching Regime Approach to Measuring the Effects of Technological Change in Ocean Shipping

this study examines the dramatic change in production technology of the U.S. ocean liner shipping industry over the period 1971 through 1982 using panel data on 15 subsidized U.S.-flag liner firms. To estimate the changes in the production function due to the new technology, the switching regime method of Goldfeld and Quandt is applied to a translog variable profit function. Three regimes based on the proportion of the new technology reflected in a firm's fleet are identified. The constant returns to scale fleet size more than doubles across the three regimes.     

Efficiency analysis in the presence of uncertainty

In a stochastic decision environment, differences in information can lead rational decision makers facing the same stochastic technology and the same markets to make different production choices. Efficiency and productivity measurement in such a setting can be seriously and systematically biased by the manner in which the stochastic technology is represented. For example, conventional production frontiers implicitly impose the restriction that information differences have no effect on the way risk-neutral decision makers utilize the same input bundle. The result is that rational and efficient ex ante production choices can be mistakenly characterized as inefficient—informational differences are mistaken for differences in technical efficiency. This paper uses simulation methods to illustrate the type and magnitude of empirical errors that can emerge in efficiency analysis as a result of overly restrictive representations of production technologies.     

Determinants of fundraising efficiency of nonprofit organizations: evidence from US public charitable organizations

Using a translog stochastic production frontier and maximum likelihood estimation method, we estimate fundraising efficiency and examine the determinants of fundraising efficiency in public charitable organizations in the United States. Our study shows that organizational size has a positive impact on fundraising efficiency and government grants have a negative impact on fundraising efficiency. We also show that charities that allocate more resources on fundraising related labor, as compared with fundraising‐related materials and equipments, are more efficient in fundraising. These findings provide important managerial implications for public charities. Copyright © 2010 John Wiley & Sons, Ltd.     

Temporal variations in technical efficiency: evidence from German soccer

This paper applies stochastic production frontier models with time-varying technical efficiency to a panel data set including hitherto unavailable information on team wage bills from the first division in German professional soccer (the “Bundesliga”) covering the years 1981–2003. We demonstrate that individual teams experience significant variation in technical efficiency over an extended period of 22 seasons while the league’s average level of efficiency remains constant over time. More detailed analyses reveal that, first, the decision to fire or to retain the head coach is mainly influenced by changes in managerial efficiency between two adjacent seasons and, second, relegated teams on average experience considerable reductions in technical efficiency compared to the previous season.     

Money and production: A stochastic frontier approach

Considerable controversy surrounds the role of money in the production of goods and services. Previous empirical research has appeared to find that the real money stock affects aggregate output, holding other, more conventional inputs constant. However, the theoretical literature offers no convincing explanation for this empirical finding. One interpretation is that real money balances reduce the extent to which labor and capital are diverted into exchange-related activities instead of being used in production defined in a more narrow sense. To investigate this hypothesis, we estimate a production function augmented with real money balances as an input, using time-series data for the aggregate U.S. economy. A stochastic production frontier is then estimated without real money balances. We use these estimates to establish the presence of technical inefficiency. Finally, we show that the extent of technical inefficiency is negatively correlated with the real money stock. Our results provide a reconciliation between the empirical literature, which finds that real money balances affect output in a production function framework, and the theoretical literature, which suggests that real money balances enhance the technical efficiency of the economy.     

Technical Efficiency of Australian Wool Production: Point and Confidence Interval Estimates

A balanced panel of data is used to estimate technical efficiency, employing a fixed-effects stochastic frontier specification for wool producers in Australia. Both point estimates and confidence intervals for technical efficiency are reported. The confidence intervals are constructed using the multiple comparisons with the best (MCB) procedure of Horrace and Schmidt (1996, 2000). The confidence intervals make explicit the precision of the technical efficiency estimates and underscore the dangers of drawing inferences based solely on point estimates. Additionally, they allow identification of wool producers that are statistically efficient and those that are statistically inefficient. The data reveal at the 95% level that twenty-one of the twenty-six wool farms analyzed may be efficient.