Estimating DEA technical and allocative inefficiency using aggregate cost or revenue data

In this paper, we address the question of Data Envelopment Analysis (DEA) evaluation of efficiency when aggregate cost or revenue data must be used. We show that the DEA technical inefficiency measure using total revenues as the single output variable or total costs as the single input variable equals the aggregate technical and allocative inefficiency. We employ this result to estimate allocative inefficiency and construct statistical tests of the null hypothesis of no allocative inefficiency analogous to those of the null hypothesis of no scale inefficiency. We illustrate our method using revenue and personnel data for the top U.S. public accounting firms over 1995–1998. Our empirical results indicate the existence of statistically significant allocative inefficiency in the public accounting industry.

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.

Cost efficiency of Slovenian water distribution utilities: an application of stochastic frontier methods

This study estimates cost inefficiency and economies of scale of Slovenian water distribution utilities over the 1997–2003 period by employing several different stochastic frontier methods. The results indicate that significant cost inefficiencies are present in the utilities. An introduction of incentive-based price regulation scheme might help resolve this problem. However, the inefficiency scores obtained from different cost frontier models are not found to be robust. The levels of inefficiency estimates as well as the rankings depend on the econometric specification of the model. The established lack of robustness can be at least partly explained by different ability of the models to separate unobserved heterogeneity from inefficiency. Newly proposed true fixed effects model (Greene, J Econom 126:269–303, 2005; J Prod Anal 23(1):7–32, 2005) appears to perform better than the conventional panel data models with respect to distinguishing between unobserved heterogeneity and inefficiency. On the other hand, different models produce fairly robust results with respect to estimates of economies of output density, customer density and economies of scale. The optimal size of a company is found to closely corresponds to the sample median. Economies of scale are found in small-sized utilities, while large companies exhibit diseconomies of scale.

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.

Do we estimate an input or an output distance function? An application of the mixture approach to European railways

In this paper, we estimate parametric input and output distance functions and discuss how to estimate a mixture/latent class model (LCM) involving the output and input distance functions in the context of multi-input and multi-output production technology. The proposed technique is applied to a panel data on European Railways (1971–1994). This model allows us to identify determinants of the efficiency orientation, thereby providing useful information that can help researchers to choose between the input and the output-oriented approaches. In addition, we develop cross-indices that can be used to compute input (output) technical inefficiency from the estimates of output (input) distance function.

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.

“The Times They Are a-Changin”: Family Responsibilities Discrimination and the EEOC

Family responsibilities discrimination, bias against workers based on their responsibilities to care for family members is widespread in many organizations and is rapidly becoming a twenty-first century workplace concern. Employers who harass, pass over for promotion, and even terminate workers because they care for children, elderly parents or spouses, or disabled family members have been sued with more frequency and have been paying increasing amounts in verdicts. Recently, the EEOC took an important step toward ending this discrimination by issuing enforcement guidelines that will educate employers and employees about family responsibilities discrimination and caregivers’ rights and responsibilities. The Guidelines explain how federal equal employment opportunity laws apply to workers who struggle to balance work and family, and what firms can do to avoid potential legal problems and accompanying liabilities with respect to family responsibilities and caregiving discrimination.

Opening the black box: Finding the source of cost inefficiency

Parametric and nonparametric procedures are used to identify the apparent source of cost inefficiency in banking. Inefficiencies of 20–25% from earlier studies are reduced to 1–5% when, in addition to commonly specified cost function influences, variables reflecting banks’ external business environment and industry indicators of “productivity” are added. These productivity indicators explain most of the reduction in bank operating cost over 1992–2001 and was 5 times the reduction in the dispersion of inefficiency. Inefficiency appears stable over time because it is small relative to industry-wide cost changes occurring concurrently and because technology dispersion is imperfect.

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%.

Allocative efficiency of rural water supply – a globally flexible SGM cost frontier

This contribution investigates the efficiency of water suppliers in rural areas of East and West Germany. A non-radial measure of input specific allocative inefficiency is used to reduce the distributional dependency with respect to the inefficiency parameters. It is based on the demand system of a flexible cost function for the variable inputs labour, energy and chemicals modelled by applying a modified symmetric generalized McFadden functional form. Concavity restrictions, as required by economic theory, are imposed. The analysis reveals that efforts towards increasing suppliers’ allocative efficiency should focus on the relatively inefficient usage of the input chemicals. The input specific allocative model specification was found to be superior to the overall allocative specification.

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.

Flexible mixture modelling of stochastic frontiers

This paper introduces new and flexible classes of inefficiency distributions for stochastic frontier models. We consider both generalized gamma distributions and mixtures of generalized gamma distributions. These classes cover many interesting cases and accommodate both positively and negatively skewed composed error distributions. Bayesian methods allow for useful inference with carefully chosen prior distributions. We recommend a two-component mixture model where a sensible amount of structure is imposed through the prior to distinguish the components, which are given an economic interpretation. This setting allows for efficiencies to depend on firm characteristics, through the probability of belonging to either component. Issues of label-switching and separate identification of both the measurement and inefficiency errors are also examined. Inference methods through MCMC with partial centring are outlined and used to analyse both simulated and real data. An illustration using hospital cost data is discussed in some detail.

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.

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.

The dynamics of efficiency and productivity growth in U.S. electric utilities

This study recognizes explicitly the efficiency gain or loss as a source in explaining the growth. A theoretically consistent method to estimate the decomposition of dynamic total factor productivity growth (TFP) in the presence of inefficiency is developed which is constructed from an extension of the dynamic TFP growth, adjusted for deviations from the long-run equilibrium within an adjustment-cost framework. The empirical case study is to U.S. electric utilities, which provides a measure to evaluate how different electric utilities participate in the deregulation of electricity generation. TFP grew by 2.26% per annum with growth attributed to the combined scale effects of 0.34%, the combined efficiency effects of 0.69%, and the technical change effect of 1.22%. The dynamic TFP grew by 1.66% per annum for electric utilities located within states with the deregulation plan and 3.30% per annum for those located outside. Electric utilities located within states with the deregulation plan increased the outputs by improving technical and input allocative efficiencies more than those located outside of states with deregulation plans.

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.

The cost of strikes in the Spanish mining sector: modelling an undesirable input with a distance function

In some contexts, firms have to deal with certain elements or factors that affect the production outcome but which are non-market in nature and therefore do not have a price. In this paper we propose a new use of a production economics tool, the input distance function, to empirically measure the effects of these factors. Although we suggest a general use of this methodology, it has been developed in the context of measuring the effects of labor disputes in a particular declining industry, that of Spanish coal mining. We have estimated an equation system comprising an input distance function and cost share equations to calculate the cost generated by strikes.

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.

Efficiency measurements and the gains from trade under transaction costs

The paper investigates the measurement of economic efficiency under transaction costs in a second best world. New measurements of technical efficiency, allocative efficiency, and price efficiency are proposed. They have three desirable properties. First, they measure efficiency loss in monetary units. Second, they are additive and can be conveniently summed into an overall efficiency measure. Third, they allow for transaction costs and their effects on prices and trade incentives. The paper investigates the welfare effects of technology choice, government pricing and trade policy, and market imperfections on efficiency. It provides new insights on the measurement of benefits from trade liberalization when trade affects not only price efficiency, but also technical and allocative efficiency.

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.