Returns to scale in convex production technologies

The notion of returns to scale (RTS) is well-established in data envelopment analysis (DEA). In the variable returns-to-scale production technology, the RTS characterization is closely related to other scale characteristics, such as the scale elasticity, most productive scale size (MPSS), and global RTS types indicative of the direction to MPSS. In recent years, a number of alternative production technologies have been developed in the DEA literature. Most of these technologies are polyhedral, and hence are closed and convex sets. Examples include technologies with weakly disposable undesirable outputs, models with weight restrictions and production trade-offs, technologies that include several component production processes, and network DEA models. For most of these technologies, the relationship between RTS and other scale characteristics has remained unexplored. The theoretical results obtained in this paper establish such relationships for a very large class of closed convex technologies, of which polyhedral technologies are an important example

Maintaining the Regular Ultra Passum Law in data envelopment analysis

The variable returns to scale data envelopment analysis (DEA) model is developed with a maintained hypothesis of convexity in input-output space. This hypothesis is not consistent with standard microeconomic production theory that posits an S-shape for the production frontier, i.e. for production technologies that obey the Regular Ultra Passum Law. Consequently, measures of technical efficiency assuming convexity are biased downward. In this paper, we provide a more general DEA model that allows the S-shape.Data envelopment analysis; homothetic production; S-shaped production function; non-convex production set

Efficiency invites Divide and Coercion in the Age of Increasing Returns to Scale

In the presence of (at least locally) increasing returns to scale technologies, the paper asks the question: does there exist an economic system which implements Pareto efficient allocations and respects the voluntary participation principle? To answer this question, the paper formulates an economic system as an allocation rule under economies with non-convex production possibility sets, and proposes a few weaker axioms to represent the voluntary participation principle. Then, the paper shows that any Pareto efficient allocation rule satisfies none of the axioms of the voluntary participation principle. The result suggests that pursuing Pareto efficiency in the presence of increasing returns to scale technologies leads to a dictatorial allocation rule, or forces someone to participate in the economic system without any guarantee of a minimal living standard

Input, Output and Graph Technical Efficiency Measures on Non-Convex FDH Models with Various Scaling Laws: An Integrated Approach Based upon Implicit Enumeration Algorithms

In a recent article, Briec, Kerstens and Vanden Eeckaut (2004) develop a series of nonparametric, deterministic non-convex technologies integrating traditional returns to scale assumptions into the non-convex FDH model. They show, among other things, how the traditional technical input efficiency measure can be analytically derived for these technology specifications. In this paper, we develop a similar approach to calculate output and graph measures of technical efficiency and indicate the general advantage of such solution strategy via enumeration. Furthermore, several analytical formulas are established and some algorithms are proposed relating the three measurement orientations to one another.Data Envelopment Analysis, Free Disposal Hull, technical efficiency

Average revenue efficiency and optimal scale sizes in stochastic data envelopment analysis: A case study of post offices

Estimating the revenue efficiency of entities being evaluated is crucial as it provides valuable information about organizations, assuming that the output prices are known. This research introduces a new definition of optimal scale size (OSS) based on maximizing the average revenue efficiency (ARE). Additionally, the ARE is defined for both convex and non-convex sets, independent of returns to scale and the assumption that the vector of input-output prices of units is uniform. Moreover, to address the presence of uncertain data in real-world applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs, along with approaches for its calculation. Finally, the proposed method is applied in an experimental example, calculating the ARE for a dataset of postal areas in Iran.IntroductionThe concept of optimal scale size has been extensively studied in the field of data envelopment analysis. Cesaroni and Giovannola's research on non-convex FDH technology reveals that the optimal scale size is a point in the production possibility set that minimizes average cost efficiency. Average cost efficiency, a new measure combining scale and allocation efficiencies, provides a more accurate performance assessment compared to cost and scale efficiencies. When evaluating units with known output prices instead of input prices, assessing revenue efficiency can offer more valuable insights. This paper extends the research on cost evaluation to revenue evaluation. It introduces the concepts of average revenue efficiency and optimal scale size based on revenue maximization. The optimal scale size based on revenue maximization is defined as the point in the production possibility set that maximizes the average radial income for the unit under investigation. Average revenue efficiency serves as an evaluation measure of unit revenue, surpassing revenue and scale efficiencies in accuracy. The paper examines methods for calculating average revenue efficiency in both convex and non-convex technologies. It demonstrates that the average revenue efficiency model in convex technology with variable returns to scale is equivalent to the revenue model with constant returns to scale. Furthermore, the relationship between optimal scale size points based on revenue maximization and the most productive scale size is determined. Next, the paper presents the average revenue efficiency model for stochastic sets with the presence of stochastic data. An experimental example is used to calculate the average revenue efficiency and obtain the optimal scale size for a set of postal areas in Iran.Materials and MethodsThe study builds upon Cesaroni and Giovannola's method for calculating average cost efficiency and optimal scale size to develop models for average revenue efficiency and optimal scale size based on revenue. It also utilizes chance-constrained probabilistic models with a deterministic objective function in DEA literature to present average revenue efficiency for stochastic sets. The model is transformed from stochastic to deterministic and then converted into a linear model using the error structure method.Discussion and ResultsThis paper introduces average revenue efficiency and optimal revenue scale size, demonstrating the equivalence between the average revenue efficiency models in convex technology with variable returns to scale and those with constant returns to scale. It also presents the average revenue efficiency model for stochastic sets, enabling the calculation of average revenue efficiency and optimal revenue scale size for units with random inputs and outputs.ConclusionIn many real-world scenarios, particularly when output prices are known, evaluating revenue efficiency holds greater significance than cost efficiency. This study develops the concepts of average cost efficiency and optimal scale size for revenue evaluation, expanding upon the existing literature on data envelopment analysis. The paper demonstrates how average revenue efficiency can be calculated as a valuable and accurate measure of efficiency in convex and non-convex technologies, without making assumptions about returns to scale. By assuming the randomness of input and output variables and employing chance-constrained models, a quadratic deterministic model is presented to calculate average revenue efficiency. It is then transformed into a linear model assuming uncorrelated variables, enabling the determination of average revenue efficiency and optimal scale size based on revenue maximization for random units. The proposed models are applied to a real-world sample, evaluating the average revenue efficiency of twelve postal units. The results highlight the models' ability to provide a more accurate evaluation of revenue efficiency and identify the best revenue scale size as the reference for inefficient units

Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies

Knowledge on the scale economies drives the incentives of regulators, governments and individual utilities to scale-up or scale-down the scale of operations. This paper considers the returns to scale (RTS) in non-convex frontier models. In particular, we evaluate RTS assumptions in a Free Disposal Hull model, which accounts for uncertainty and heterogeneity in the sample. Additionally, we provide a three-step framework to empirically analyze the existence and extent of RTS in real world applications. In a first step, the presence of scale (and scope) economies is verified. Secondly, RTS for individual observations are examined while in a third step we derive the optimal scale for a sector as a whole. The framework is applied to the Portuguese drinking water sector where we find the optimal scale to be situated around 7 to 10 million m3.Free Disposal Hull, economies of scale, optimal size, water sector

Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies.

Knowledge on the scale economies drives the incentives of regulators, governments and individual utilities to scale-up or scale-down the scale of operations. This paper considers the returns to scale (RTS) in non-convex frontier models. In particular, we evaluate RTS assumptions in a Free Disposal Hull model, which accounts for uncertainty and heterogeneity in the sample. Additionally, we provide a three-step framework to empirically analyze the existence and extent of RTS in real world applications. In a .rst step, the presence of scale (and scope) economies is veri.ed. Secondly, RTS for individual observations are examined while in a third step we derive the optimal scale for a sector as a whole. The framework is applied to the Portuguese drinking water sector where we .nd the optimal scale to be situated around 7 to 10 million m3.

Nonparametric estimation of concave production technologies by entropic methods

An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions.convex programming, production functions, entropy

On Intersectoral Asymmetries in Factors Substitutability “Equilibrium Production Possibility Frontiers” and the emergence of indeterminacies

The existence of asymmetries in factors substitutability between the distinct sectors of a given economy will directly rule the influence that spillover effects have upon its determinacy properties. For leading intersectoral spillover effects, the substitutability of the capital good industry together with a potential relative profit shares reversal—itself conditional to the existence of asymmetries between the intrasectoral and intersectoral spillover effects of at least one sector—between the private and the equilibrium level will, e.g., be at the core of the area for local indeterminacies. This proceeds from external dimensions which do not modify the constant returns to scale hypothesis that is retained at the decentralised level of the firm as they directly relate to equilibrium factors costs and outputs prices. The generality of the current approach and the genericity of the associated production set enlighten the role of the irregularities that prevail across the substitutability properties of the various sectors of a given economy but also, in the same vein, of the occurrence of heterogeneities between the intrasectoral and intersectoral spillovers emanating from a given industry, this gap being in turn weighted by the substitutability properties of this industry. It is shown that these multiplicity conclusions directly result from unusual properties of the Equilibrium Production Possibility Frontier that formulate as the occurrence of an equilibrium complementarity between the two outputs.Equilibrium Production Possibility Frontiers; Intersectoral asymmetries in factors substitutability and between Price related intrasectoral and intersectoral spillovers; Irrelevance of returns to scale for local or global indeterminacies; Equilibrium complementarities between the outputs in a world of heterogeneous goods

ENVIRONMENTAL CONSTRAINTS, COMMODITY MIX, AND RESEARCH RESOURCE ALLOCATION

The purpose of this paper is to show how the allocation of research resources among commodities and the effects of such allocations on the output mix depend upon (a) the initial production conditions, (b) the nature of the research production functions, (c) the nature of the demand relations for the commodity outputs, (d) relative factor endowments, and (e) the existence of different types of environmental constraints. The basic model used is a two-factor, two-product model in which certain types of technical change are introduced.Research and Development/Tech Change/Emerging Technologies,