Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA
TL;DR: The strengths and weaknesses for estimating environmental efficiency of the methods applied are revealed; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA).
Abstract: The objective of this paper is to estimate comprehensive environmental efficiency measures for Dutch dairy farms. The environmental efficiency scores are based on the nitrogen surplus, phosphate surplus and the total (direct and indirect) energy use of an unbalanced panel of dairy farms. We define environmental efficiency as the ratio of minimum feasible to observed use of multiple environmentally detrimental inputs, conditional on observed levels of output and the conventional inputs. We compare two methods for the calculation of efficiency; namely Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA). This paper reveals the strengths and weaknesses for estimating environmental efficiency of the methods applied. Both SFA and DEA can estimate environmental efficiency scores. The mean technical efficiency scores (output-oriented, SFA 89%, DEA 78%) and the mean comprehensive environmental efficiency scores (SFA 80%, DEA 52%) differ between the two methods. SFA allows hypothesis testing, and the monotonicity hypothesis is rejected for the specification including phosphate surplus. DEA can calculate environmental efficiency scores for all specifications, because regularity is imposed in this method.
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01 Jan 1995TL;DR: In this article, the potential applicability of frontier methods in agricultural economics is discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers.
Abstract: In this paper recent developments in the estimation of frontier functions and the measurement of efficiency are surveyed, and the potential applicability of these methods in agricultural economics is discussed. Frontier production, cost and profit functions are discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers. The two primary methods of frontier estimation, econometric and linear programming, are compared. A survey of recent applications of frontier methods in agriculture is also provided. (This abstract was borrowed from another version of this item.)
821 citations
TL;DR: Wang et al. as discussed by the authors employed panel data of 30 China's provinces for the period 2006-2018 to explore the influence of green finance on green total factor productivity, revealing estimation results that green finance development significantly improves the level of green productivity.
330 citations
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01 Jan 2008
TL;DR: The approach, based on a Least Squares Cross Validation procedure (LSCV), provides an optimal bandwidth that minimizes an appropriate (weighted) integrated Squared Error (ISE) and is exemplified with some simulated data with univariate and multivariate environmental factors.
Abstract: In productivity analysis an important issue is to detect how external (environmental) factors, exogenous to the production process and not under the control of the producer, might influence the production process and the resulting efficiency of the firms. Most of the traditional approaches proposed in the literature have serious drawbacks. An alternative approach is to describe the production process as being conditioned by a given value of the environmental variables (Cazals, Florens and Simar, 2002, Daraio and Simar, 2005). This defines conditional efficiency measures where the production set in the input × output space may depend on the value of the external variables. The statistical properties of nonparametric estimators of these conditional measures are now established (Jeong, Park and Simar, 2008). These involve the estimation of a nonstandard conditional distribution function which requires the specification of a smoothing parameter (a bandwidth). So far, only the asymptotic optimal order of this bandwidth has been established. This is of little interest for the practitioner. In this paper we fill this gap and we propose a data-driven technique for selecting this parameter in practice. The approach, based on a Least Squares Cross Validation procedure (LSCV), provides an optimal bandwidth that minimizes an appropriate integrated Mean Squared Error (MSE). The method is carefully described and exemplified with some simulated data with univariate and multivariate environmental factors. An application on real data (performances of Mutual Funds) illustrates how this new optimal method of bandwidth selection outperforms former methods.
186 citations
Additional excerpts
...ISE = ∫ {ĝ(y|X ≤ x, Z = z) − g(y|X ≤ x, Z = z)}(2)m(X ≤ x, z)dW (z)dy, (16)...
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TL;DR: In this article, a hybrid model is proposed to ensure the economically meaningful jointness of good and bad outputs while constraining shadow prices of bad outputs to their expected sign, based on the Law of One Price (LoOP) rule.
Abstract: For three decades a growing interest in the modeling of desirable and undesirable outputs has led to a theoretical and methodological debate in the nonparametric literature on production technology and efficiency. The first main discussion is about the way of modeling ‘bad/undesirables’ as inputs or outputs, or by transformation functions. The second debate concerns the implications of the weak disposability assumption in the modeling of bad outputs, in particular the possibility of assigning unexpected signs to shadow prices of bad outputs. In addition, we point out a current error in the modeling of weak disposability under a variable returns to scale technology. In this paper we introduce a hybrid model to ensure the economically meaningful jointness of good and bad outputs while constraining shadow prices of bad outputs to their expected sign. We argue that it is a sound compromise to model undesirable outputs with a meaningful primal/dual economic interpretation. Finally we propose an extension to define shadow prices for undesirable outputs following the Law of One Price (LoOP) rule. (This abstract was borrowed from another version of this item.)
88 citations
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TL;DR: The results from the UK regional data reveal that economic growth has a negative effect on regions’ environmental performance up to a certain GDP per capita level, where after that point the effect becomes positive, indicating the existence of a Kuznets type relationship between the UK regions‘ environmental performance and economic growth.
Abstract: This paper, by using conditional directional distance functions as introduced by Simar and Vanhems [J. Econometrics 166 (2012) 342-354] modifies the model by Fare and Grosskopf [Eur. J. Operat. Res. 157 (2004) 242-245], examines the link between regional environmental efficiency and economic growth. The proposed model using conditional directional distance functions incorporates the effect of regional economic growth on regions’ environmental efficiency levels. The results from the UK regional data reveal that economic growth has a negative effect on regions’ environmental performance up to a certain GDP per capita level, where after that point the effect becomes positive. This indicates the existence of a Kuznets type relationship between the UK regions’ environmental performance and economic growth.
83 citations
Cites background from "Environmental efficiency with multi..."
...2 Other studies treat the pollutant as input in a DEA framework (Reinhard et al., 2000, Korhonen and Luptacik, 2004)....
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TL;DR: The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs as mentioned in this paper.
Abstract: In management contexts, mathematical programming is usually used to evaluate a collection of possible alternative courses of action en route to selecting one which is best. In this capacity, mathematical programming serves as a planning aid to management. Data Envelopment Analysis reverses this role and employs mathematical programming to obtain ex post facto evaluations of the relative efficiency of management accomplishments, however they may have been planned or executed. Mathematical programming is thereby extended for use as a tool for control and evaluation of past accomplishments as well as a tool to aid in planning future activities. The CCR ratio form introduced by Charnes, Cooper and Rhodes, as part of their Data Envelopment Analysis approach, comprehends both technical and scale inefficiencies via the optimal value of the ratio form, as obtained directly from the data without requiring a priori specification of weights and/or explicit delineation of assumed functional forms of relations between inputs and outputs. A separation into technical and scale efficiencies is accomplished by the methods developed in this paper without altering the latter conditions for use of DEA directly on observational data. Technical inefficiencies are identified with failures to achieve best possible output levels and/or usage of excessive amounts of inputs. Methods for identifying and correcting the magnitudes of these inefficiencies, as supplied in prior work, are illustrated. In the present paper, a new separate variable is introduced which makes it possible to determine whether operations were conducted in regions of increasing, constant or decreasing returns to scale in multiple input and multiple output situations. The results are discussed and related not only to classical single output economics but also to more modern versions of economics which are identified with "contestable market theories."
14,941 citations
TL;DR: In this paper, the authors define the disturbance term as the sum of symmetric normal and (negative) half-normal random variables, and consider various aspects of maximum-likelihood estimation for the coefficients of a production function with an additive disturbance term of this sort.
8,058 citations
6,067 citations
TL;DR: In this article, a stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time, and the best predictor for the technical efficiency of an individual firm at a particular time period is presented for this timevarying model.
Abstract: Frontier production functions are important for the prediction of technical efficiencies of individual firms in an industry. A stochastic frontier production function model for panel data is presented, for which the firm effects are an exponential function of time. The best predictor for the technical efficiency of an individual firm at a particular time period is presented for this time-varying model. An empirical example is presented using agricultural data for paddy farmers in a village in India.
2,884 citations