The efficiency of Spanish arable crop organic farms,a local maximum likelihood approach

The methodologies that have been used in existing research to assess the efficiency with which organic farms are operating are generally based either on the stochastic frontier methodology or on a deterministic non-parametric approach. Recently, Kumbhakar et al. (J Econom 137:1–27, 2007) proposed a new nonparametric, stochastic method based on the local maximum likelihood principle. We use this methodology to compare the efficiency ratings of organic and conventional arable crop farms in the Spanish region of Andalucía. Nonparametrically encompassing the stochastic frontier model is especially useful when comparing the performance of two groups that are likely to be characterized by different production technologies.

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.

The permanent income hypothesis in five major industrial countries: a multivariate trend-cycle decomposition test

This paper presents a new test of the permanent income hypothesis in five major industrial countries. The test first decomposes consumption and income into their long run trend (permanent) and short run cyclical (transitory) components, using the recently developed multivariate stochastic detrending approach developed by Vahid and Engle (1997), among others. This approach exploits the presence of possible common stochastic trends and cycles among the variables in the system to arrive at a more efficient decomposition of these variables. Using the decomposition results, and in contrast to many articles in the literature, the paper finds support for the permanent income hypothesis. Specifically, the paper finds that, while permanent consumption is related to permanent income, transitory consumption is related to neither permanent nor transitory income.

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.

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.

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.

On the inefficiency of European socialist economies

This paper aims at comparing macroeconomic performance of three European socialist economies (Hungary, Poland, Yugoslavia) with developing and developed countries during the 1970s and the 1980s. Using panel data for 89 countries, we measure macroeconomic performance with two panel data production frontier models: the WITHIN model proposed by (Cornwell et al J Econom 46:185–200, 1990), and the firm effects model developed by (Battese and Coelli J Prod Anal 3:153–169, 1992). We conclude in favor of the underperformance of socialist countries in relation to developed countries but also to developing countries in most cases, which may be explained by the features of the socialist economic system.

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.

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.

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.

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.

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.

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.

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.

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.

An examination of the performance and prospects for the future of internet-primary banks

We study Internet-primary banks for differences in performance versus newly chartered traditional banks from 1996 through 2003. Internet-primary banks are larger, with lower net interest margins and loan losses, and higher wage and physical capital rates than newly chartered traditional banks. Univariate ROE is lower, but profit efficiency is significantly higher on average for Internet-primary banks compared to all newly chartered banks as well as those that survive through the sample period. In multivariate models, Internet-primary banks continue to have significantly higher average profit efficiency, and particularly so when of sufficient size.

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.

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.

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.

Longitudinal analysis of entrepreneurship and competitiveness dynamics in Latin America

This study analyzes the relationship between entrepreneurial dynamics in Latin-American countries and the level of competitiveness these countries show. Based on the research conducted by Wennekers et al. [Small Business Economics, 24(3):293–309, 2005] that demonstrates a U-shaped relationship between the country’s rate of entrepreneurship and its level of competitiveness and economic development, we hypothesize that Latin-American countries have a descending behaviour under the U-shaped curve approach. The results from three regression models support this hypothesis and suggest that competitiveness and economic growth deter entrepreneurial dynamics on Latin-American countries. We discuss that Latin-American countries need to improve some structural factors to achieve a high level of entrepreneurial dynamics.