The productivity performance of Irish dairy farms 1984–2000: a multiple output distance function approach

This study measures productivity growth on Irish dairy farms over the period 1984–2000. A total factor productivity index is constructed for the dairy system and is decomposed into technical change, efficiency change, and changes in scale efficiency. This is achieved by estimating a stochastic output distance function model of the production technology in use on Irish dairy farms. Overall, productivity on Irish dairy farms grew by 1.2% per annum over the sample period.

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.

Efficient frontier estimation: a maximum entropy approach

An alternative efficiency estimation approach is developed utilizing generalized maximum entropy (GME). GME combines the strengths of both SFA and DEA, allowing for the estimation of a frontier that is stochastic, without making an ad hoc assumption about the distribution of the efficiency component. GME results approach SFA results as the one-sided inefficiency bounds used by GME shrink. Results similar to DEA are achieved as the bounds increase. The GME results are distributed like DEA, but yield virtually the same rankings as SFA. The results suggest that GME may provide a link between various estimators of efficiency.

Regional variation in productivity: a study of the Danish economy

We develop a model of labor productivity as a combination of capital-labour ratio, vintage of capital stock, regional externalities, and total factor productivity (TFP). The skewness of TFP distribution is related to different growth theories. While negative skewness is consistent with the neo-Schumpeterian idea of catching up with leaders, zero skewness supports the neoclassical view that deviations from the frontier reflect only idiosyncratic productivity shocks. We argue that positive skewness is consistent with an economy where exogenous technology is combined with non-transferable knowledge accumulated in specific sectors and regions. This argument provides the framework for an empirical model based on stochastic frontier analysis. The model is used to analyse regional and sectoral inequalities in Denmark.

Measuring performance in the presence of stochastic demand for hospital services: an analysis of Belgian general care hospitals

Since demand for hospital services is subject to substantial variability, the relationship between uncertain demand, excess capacity, hospital costs and performance should be investigated thoroughly. In this paper a waiting time indicator to proxy hospital standby capacity is incorporated into a multi-product translog cost function for Belgian general care hospitals. The indicator is derived from queuing theory and improves on the conventionally used (inverse of the) occupancy rate. The multi-product stochastic frontier specification allows calculation of cost elasticities and marginal cost of seven hospital departments, as well as the degree of economies of scale and scope and enables identification of differences in efficiency.

Technical efficiency in farming: a meta-regression analysis

A meta-regression analysis including 167 farm level technical efficiency (TE) studies of developing and developed countries was undertaken. The econometric results suggest that stochastic frontier models generate lower mean TE (MTE) estimates than non-parametric deterministic models, while parametric deterministic frontier models yield lower estimates than the stochastic approach. The primal approach is the most common technological representation. In addition, frontier models based on cross-sectional data produce lower estimates than those based on panel data whereas the relationship between functional form and MTE is inconclusive. On average, studies for animal production show a higher MTE than crop farming. The results also suggest that the studies for countries in Western Europe and Oceania present, on average, the highest levels of MTE among all regions after accounting for various methodological features. In contrast, studies for Eastern European countries exhibit the lowest estimate followed by those from Asian, African, Latin American, and North American countries. Additional analysis reveals that MTEs are positively and significantly related to the average income of the countries in the data set but this pattern is broken by the upper middle income group which displays the lowest MTE.

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.

Application of a double bootstrap to investigation of determinants of technical efficiency of farms in Central Europe

The paper provides one of the first applications of the double bootstrap procedure (Simar and Wilson 2007) in a two-stage estimation of the effect of environmental variables on non-parametric estimates of technical efficiency. This procedure enables consistent inference within models explaining efficiency scores, while simultaneously producing standard errors and confidence intervals for these efficiency scores. The application is to 88 livestock and 256 crop farms in the Czech Republic, split into individual and corporate.

Efficiency vectors, efficiency and performance measures: new methods for ranking efficient organizational units

We present and discuss measures for analyzing productivity in deterministic frontier models. A new efficiency measure is introduced allowing for discrimination among efficient organizational units. In addition, a new performance measure for analyzing productivity of organizational units is presented. This measure fulfills various properties of efficiency measures but relaxes the indicator property. Both new approaches are based on the development of efficiency vectors which is a new vector measure for measuring efficiency. The vector components are efficiency measures related to subsets of a production possibility set. The new approaches are applied in the context of data envelopment analysis.

Model selection in stochastic frontier analysis with an application to maize production in Kenya

This paper shows how to compute the standard errors for partial effects of exogenous firm characteristics influencing firm inefficiency under a range of popular stochastic frontier model specifications. We also develop an R²-type measure to summarize the overall explanatory power of the exogenous factors on firm inefficiency. The paper also applies a recently developed model selection procedure to choose among alternative stochastic frontier specifications using data from household maize production in Kenya. The magnitude of estimated partial effects of exogenous household characteristics on inefficiency turns out to be very sensitive to model specification, and the model selection procedure leads to an unambiguous choice of best model. We propose a bootstrapping procedure to evaluate the size and power of the model selection procedure. The empirical application also provides further evidence on how household characteristics influence technical inefficiency in maize production in developing countries.

Debreu’s coefficient of resource utilization, the Solow residual, and TFP: the connection by Leontief preferences

Debreu’s coefficient of resource utilization is freed from individual data requirements. The procedure is shown to be equivalent to the imposition of Leontief preferences. The rate of growth of the modified Debreu coefficient and the Solow residual are shown to add up to TFP growth. This decomposition is the neoclassical counterpart to the frontier analytic decomposition of productivity growth into technical change and efficiency change. The terms can now be broken down by sector as well as by factor input.

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.

Assessing multi-dimensional performance: environmental and economic outcomes

This study examines economic performance, environmental performance, and regulatory activity for plants in three industries: pulp and paper, oil, and steel. Stochastic frontier production function models show significant deviations from production efficiency. Older plants are less efficient in production, but perform no worse on emissions. Plants spending more on pollution abatement tend to do worse on both production efficiency and emissions. Stricter local regulatory pressure is associated with somewhat lower emissions, but has mixed effects on production efficiency. Positive correlations between SUR residuals for emissions and production efficiency suggest unmeasured plant-level characteristics that drive both economic and environmental performance.

Testing for infinite order stochastic dominance with applications to finance, risk and income inequality

In this paper we develop a test of infinite order degree stochastic dominance based on the use of the empirical Laplace transform function. Two applications are considered. One uses the income data of Anderson (Econometrica 64:1183–1193, 1996) and derives results consistent with his. In the other application we examine the dominance between the U.S. and U.K. stock markets. Using data on the S&P 500 and the FTALL-Share we show that the U.S. displays infinite order degree stochastic dominance of the U.K.

Is competition really bad news for cooperatives? Some empirical evidence for Italian producers’ cooperatives

In this paper, we analyse the nature of the relationship between market power and technical efficiency for producers’ cooperatives. More specifically we test two hypotheses: first, we evaluate the extent to which increasing market pressure may help producers’ cooperatives to improve technical efficiency to guarantee positive profits; second, we test whether higher technical efficiency induces producers’ cooperatives to have a larger market share. These hypotheses are tested on a sample of Italian conventional and cooperative firms for the Wine Production and Processing sector, using both frontier analysis and dynamic panel techniques. The results support the hypothesis that increasing market pressure can affect positively the cooperatives′ efficiency, while gains in technical efficiency do not seem to have any impact on the cooperatives’ market share.

Joint estimation of technical efficiency and production risk for multi-output banks under a panel data cost frontier model

This article generalizes production risk from a single output production function to a multiple output cost frontier, which is able to examine input-oriented technical efficiencies and production risk simultaneously in the context of a panel data. Furthermore, the joint confidence interval estimates for technical efficiencies are constructed by means of multiple comparisons with the best approach. Whether taking production risk into account or not offers quite dissimilar implications in terms of the average technical efficiency measure and the identification of multiple efficient banks achieving the optimal cost frontier. It is suggested that inferences drawn on the basis of the confidence intervals of technical efficiency provide much more fruitful and insightful information than the point estimation alone. Bank specific risk parameters are found to be highly and positively correlated with fixed-effect estimates, implying that the more risk-averse a bank is, the more technically efficient it will be.

Matching in local labor markets: a stochastic frontier approach

This paper investigates the technical efficiency of labor market matching from a stochastic frontier approach. The true fixed-effects model (Greene J Prod Anal 23:7–32, 2005a; J Econom 126:269–303, 2005b) is utilised in order to separate cross-sectional heterogeneity from inefficiency, and inefficiency terms are modelled following Battese and Coelli (Empir Econ 20:325–332, 1995). The data set consists of almost 17,000 observations from Local Labor Offices (LLOs) in Finland. According to the results, there are notable differences in matching efficiency between regions, and these differences contribute significantly to the number of filled vacancies. If all regions were as efficient as the most efficient one, the number of total matches per month would increase by over 23%. The heterogeneity of the job-seeker stock is an important determinant of matching efficiency: the weight of the composition of the job-seeker stock in the inefficiency terms is on average 85%.

Closest targets and minimum distance to the Pareto-efficient frontier in DEA

In this paper, we propose a general approach to find the closest targets for a given unit according to a previously specified criterion of similarity. The idea behind this approach is that closer targets determine less demanding levels of operation for the inputs and outputs of the inefficient units to perform efficiently. Similarity can be interpreted as closeness between the inputs and outputs of the assessed unit and the proposed targets, and this closeness can be measured by using either different distance functions or different efficiency measures. Depending on how closeness is measured, we develop several mathematical programming problems that can be easily solved and guarantee to reach the closest projection point on the Pareto-efficient frontier. Thus, our approach leads to the closest targets by means of a single-stage procedure, which is easier to handle than those based on algorithms aimed at identifying all the facets of the efficient frontier.

Efficiency analysis of East European electricity distribution in transition: legacy of the past?

This paper provides a cross-country efficiency analysis of electricity distribution companies in the East European transition countries of Poland, the Czech Republic, Slovakia and Hungary. We use common nonparametric efficiency measurement such as Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH) under different assumptions and apply recent developments of statistical inference in nonparametric frontier models to test our hypotheses. We discuss the empirical problems of cross-country benchmarking approaches, in particular the comparability of different structures of electricity distribution companies. Our results suggest that Poland’s distribution companies are still inefficiently small; the Czech Republic features the highest efficiency; and Slovakia and Hungary occupy the middle range. We also note that privatization has had a positive effect on technical efficiency in the four countries. We use the phrase “legacy of the past” to describe the four countries in comparison to the efficiency of electricity distribution companies we studied in Germany.

The effects of match uncertainty and bargaining on labor market outcomes: evidence from firm and worker specific estimates

In this paper we examine wage dispersion in labor markets across currently employed workers. We argue that differences in the potential productivity of a match (typically assumed to be known in the previous literature) generates a surplus between the minimum wage the worker is willing to accept and the maximum wage the firm is willing to offer for the job. Existence of this surplus leads to wage dispersion due to negotiating over the amounts extracted by each agent. Our objective is to estimate the surplus extracted by each firm-worker pair and the effect of the net extracted surplus on the wage, for each firm-worker pair using the two-tier stochastic frontier model. An empirical application finds that, on average, firms paid workers less than their expected productivity. More specifically, at the mean, the net effect of productivity uncertainty leads to equilibrium wages which are 3.33% below the expected productivity of matches.