Economic inefficiency measurement of input spending when decision-making units face different input prices

In a recent paper, Kaoru Tone (J Opl Res Soc (2002) 2: 429–444) showed that when the Farrell measure of cost efficiency is estimated for two firms that have different input prices, a firm with higher costs can be deemed more efficient than a firm with lower costs. As an alternative approach, Tone proposed a radial cost efficiency measure that is estimated using levels of spending on each input, rather than input quantities. Thus, firms with higher costs are less efficient than firms with lower costs. In this paper, we extend Tone's approach by allowing for non-radial changes in spending. Our approach builds on earlier work by Luenberger (J Math Econ (1992) 21: 461–481) and Chambers et al (J Econ Theo (1996) 70: 407–419) who use directional distance functions to measure inefficiency. We provide an example and illustration of our approach using Japanese bank data.     

Cost efficiency in data envelopment analysis under the law of one price

To impose the law of one price (LoOP) restrictions, which state that all firms face the same input prices, Kuosmanen, Cherchye, and Sipiläinen (2006) developed the top-down and bottom-up approaches to maximizing the industry-level cost efficiency. However, the optimal input shadow prices generated by the above approaches need not be unique, which influences the distribution of the efficiency indices at the individual firm level. To solve this problem, in this paper, we developed a pair of two-level mathematical programming models to calculate the upper and lower bounds of cost efficiency for each firm in the case of non-unique LoOP prices while keeping the industry cost efficiency optimal. Furthermore, a base-enumerating algorithm is proposed to solve the lower bound models of the cost efficiency measure, which are bi-level linear programs and NP-hard problems. Lastly, a numerical example is used to demonstrate the proposed approach.     

The weighted Russell measure of technical efficiency

Theoretical consideration of technical efficiency has existed since Koopmans [10] defined it for production possibilities for which it is not possible to increase any output without simultaneously increasing any input, ceteris paribus. The nonparametric approach to efficiency measurement known as Data Envelopment Analysis is based on the index of Farrell [9], which measures radial reduction in all inputs consistent with observed output. Even after Farrell efficiency is achieved, however, there may exist additional slack in individual inputs, suggesting that the Farrell index does not necessarily measure Koopmans inefficiency. To solve this problem, the non-radial Russell measure was introduced. This paper shows that problems may arise with the Russell measure due to restrictive assumptions on the implicit weighting of inputs and outputs. This paper develops a new measure, the Weighted Russell measure, that relaxes this assumption. Using simulated data, the new measure is shown to be preferred to existing methods. In addition, the new method is applied to analyze the performance of New York State school districts.     

A cost Malmquist productivity index

This paper develops a productivity index applicable when producers are cost minimisers and input prices are known. The index is inspired by the Malmquist index as extended to productivity measurement. The index developed here is defined in terms of input cost rather than input quantity distance functions. Hence, productivity change is decomposed into overall efficiency and cost technical change. Furthermore, overall efficiency change is decomposed into technical and allocative efficiency change and cost technical change into a part capturing shifts of input quantities and shifts of relative input prices. These decompositions provide a clearer picture of the root sources of productivity change. They are illustrated here in a sample of hospitals; results are computed using non-parametric mathematical programming.     

DEA-based pre-merger planning tool

Data envelopment analysis (DEA) can be used as a pre-merger planning tool to estimate expected cost and profit efficiency gains. Specifically, in this paper, two alternative DEA models are presented, one to minimize post-merger input cost and the other to maximize post-merger profit. The first model assumes that input prices are known, whereas the second assumes that output prices are known. As both models explicitly consider the possibility of closing existing units, they are especially apt for in-market horizontal mergers, in which considerable overlap may exist among the branches of the merging firms. Indicative efficiency ratios are proposed based on the results of the models. The proposed approach is, in addition, rather flexible, allowing the optional inclusion of a variety of features and constraints, such as incompatibility among units, employment guarantees, etc.     

The choice of a technical efficiency measure on the free disposal hull reference technology: A comparison using US banking data

This paper evaluates a variety of technical efficiency measures based on a given nonparametric reference technology, the free disposal hull (FDH). Specifically, we consider the radial measure of Debreu (1951)/Farrell (1957) and the nonradial measures of Färe (1975), Färe and Lovell (1978) and Zieschang (1984). Furthermore, input-based, output-based, and graph efficiency versions of these four measures are computed. Theoretical consideration as to the best choice among these alternative measures is inconclusive; therefore, we examine this problem from an empiricalviewpoint. Calculating thirteen different measures of technical efficiency for a sample of US banks, we compare the measures' efficiency distributions and rankings, paying particular attention to how well the radial measure approximates its nonradial alternatives.     

A comment on “cost efficiency in data envelopment analysis with data uncertainty”

In a recent paper by Mostafaee and Saljooghi [Mostafaee, A., Saljooghi, F.H., 2010. Cost efficiency in data envelopment analysis with data uncertainty. European Journal of Operational Research, 202, 595–603], the authors extend the classical cost efficiency model to address data uncertainty. They claim that the upper bound of the cost efficiency can be obtained at extreme points when the input prices appear in the form of ranges. In this paper, we present our counterexamples and comments on the contention by Mostafaee and Saljooghi.     

The law of one price in data envelopment analysis: Restricting weight flexibility across firms

The Law of One Price (LoOP) states that all firms face the same prices for their inputs and outputs under market equilibrium. Taken here as a normative condition for ‘efficiency prices’, this law has powerful implications for productive efficiency analysis, which have remained unexploited thus far. This paper shows how LoOP-based weight restrictions can be incorporated in Data Envelopment Analysis (DEA). Utilizing the relation between industry-level and firm-level cost efficiency measures, we propose to apply a set of input prices that is common for all firms and that maximizes the cost efficiency of the industry. Our framework allows for firm-specific output weights and for variable returns-to-scale, and preserves the linear programming structure of the standard DEA. We apply the proposed methodology to the evaluation of the research efficiency of economics departments of Dutch Universities. This application shows that the methodology is computationally tractable for practical efficiency analysis, and that it helps in deepening the DEA analysis.     

Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments

This paper enhances cost efficiency measurement methods to account for different scenarios relating to input price information. These consist of situations where prices are known exactly at each decision making unit (DMU) and situations with incomplete price information. The main contribution of this paper consists of the development of a method for the estimation of upper and lower bounds for the cost efficiency (CE) measure in situations of price uncertainty, where only the maximal and minimal bounds of input prices can be estimated for each DMU. The bounds of the CE measure are obtained from assessments in the light of the most favourable price scenario (optimistic perspective) and the least favourable price scenario (pessimistic perspective). The assessments under price uncertainty are based on extensions to the Data Envelopment Analysis (DEA) model that incorporate weight restrictions of the form of input cone assurance regions. The applicability of the models developed is illustrated in the context of the analysis of bank branch performance. The results obtained in the case study showed that the DEA models can provide robust estimates of cost efficiency even in situations of price uncertainty.     

Allocating the fixed cost as a complement of other cost inputs: A DEA approach

In cost allocation problem, traditional DEA approaches allocate the fixed cost among a group of decision making units (DMUs), and treat the allocated cost as an extra input of each DMU. If costs except for the fixed cost are regarded as inputs in the cost allocation problem, then it is obvious that the fixed cost is a complement of other inputs rather than an extra independent input. Therefore it is necessary to combine the allocated cost with other cost measures in cost allocation problem. Based on this observation, this paper investigates the relationship between the allocated cost and the DEA efficiency score and develops a DEA-based approach to allocate the fixed cost among various DMUs. An example of allocating advertising expenditure between a car manufacturer and its dealers is presented to illustrate the method proposed in this paper.     

Reconstructing local volatility using total variation

The aim of this paper is to identify the volatility function in Dupire’s equation from given option prices. This inverse problem is formulated as an infinite-dimensional minimization problem with PDE constraints. The computational cost of solving the discretized problem on a fine discretization level is expensive. A multi-grid method is proposed to explore the hierarchical structures of discretized problems on different levels. Computational examples are presented to demonstrate the efficiency of our method.     

Semi-Lagrangean approach for price discovery in markets with non-convexities

From standard economic theory, the market clearing price for a commodity is set where the demand and supply curves intersect. Convexity is a property that economic models require for a competitive equilibrium, which is efficient and well-behaved and provides equilibrium prices. However, some markets present non-convexities due to their cost structure or due to some operational constraints that need to be addressed. This is the case for electricity markets where the electricity producers incur costs for shutting down a generating unit and then bringing it back on. Non-convex cost structures can be a challenge for the price discovery process, since the supply and demand curves may not intersect, or if they intersect, the price found may not be high enough to cover the total cost of production. We apply a Semi-Lagrangean approach to find a price that can be applied in the electricity pool markets where a central system operator decides who produces and how much they should produce. By applying the model to an example from the literature, we found prices that are high enough to cover the producer’s total costs, and follows the optimal solution for achieving mining cost in production. The prices are an alternative solution to the price discovery problem in non-convexities economies; in addition, they provide nonnegative profits to all the generators without the use of side-payments or up-lifts, and closes the integrality gap.     

Solving the puzzles of structural efficiency

Since the concept of “structural efficiency” first appeared in Farrell [Farrell, M.J., 1957. The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A, Part III 120, 253–281], attempts have been made to derive measures for the performance of a group of production units (often referred to an industry with many firms). Many empirical studies used the technical efficiency of an average unit to measure the structural efficiency of a group, but researchers have been puzzled by the discrepancies between the average of individual efficiency scores and the performance of the group as a whole. In this paper, we point out that the “shadow price model” provides a useful framework for understanding the economic meaning of the structural efficiency as well as its components. By recognizing these components, the puzzles related to the inconsistencies between the individual and group performance can be solved readily.     

The hyperbolic-oriented efficiency measure as a remedy to infeasibility of super efficiency models

The infeasibility problem in traditional super efficiency models has been well established. A generalization of traditional input- or output-oriented super efficiency models, the directional distance function also suffers from infeasibility and related problems. The hyperbolic-oriented efficiency measure provides an alternative to the input-oriented, output-oriented, and directional efficiency measures in super efficiency models and it has the distinct advantage of eliminating the infeasibility problem for positive input/output data. We also show that using a hyperbolic orientation in a super efficiency model allows us to find feasible solutions for certain cases when the requirement for all data to be positive is relaxed. Further we demonstrate the hyperbolic orientated super efficiency method in an outlier detection application. Together, these results establish the use of the hyperbolic orientation in super efficiency analysis as a realistic alternative in practice.     

Cost minimization and the stochastic discount factor

It is shown that a cost function subject to internal costs of adjustment induces a stochastic discount factor (pricing kernel) that is a function of random output, input and output prices, existing capital stock, and investment. The only assumption on firm preferences is that they are increasing in current period consumption and future stochastic consumption. This ensures that the firm will always act to minimize current period cost of providing future consumption, and it is the first-order conditions for this cost minimization problem that generate the stochastic discount factor, which itself can be interpreted as the marginal variable cost of varying stochastic output. A cost-based pricing kernel is estimated using annual time-series data on macroeconomic variables and returns data for the S&P 500 and commercial paper.     

双渠道下制造商现金流套期保值决策研究

由于汇率、利率、商品价格的变化以及双渠道供应链关系的复杂性,企业的现金流存在较大的波动性。本文研究双渠道销售模式下,制造商对现金流进行套期保值的决策问题。重点关注垄断企业在拥有一个分销商和线上销售的双渠道销售模式下,并利用内部融资将现金流用于提高生产效率时,如何根据现金流的波动程度、市场需求、替代产品敏感系数以及批发价格进行套期保值决策。研究了双渠道销售模式下制造商的均衡问题,比较了两种决策下的均衡解,并通过数值分析给出了直观的结论：市场最大需求与替代产品敏感系数增加时,企业更倾向于选择套期保值;现金流波动程度与批发价格增加时,企业更倾向于不选择套期保值。     

Average shadow price and equilibrium price: A case study of tradable pollution permit markets

Shadow prices indicate implicit values of limited resources at the margin and provide important information in decision making for resource management. In continuous economic models, shadow prices associated with demand-supply balance constraints represent consumers’ willingness to pay and producers’ marginal cost, hence they correspond to market equilibrium prices. As well known, however, marginal analysis fails in the case of discrete optimization, such as mixed integer programming. An alternative concept has been introduced in the literature to measure the value of an extra unit of a limited resource in such cases. This concept is based on average rather than marginal values, thus called the average shadow price, and interpreted in the same way as conventional shadow prices. Whether average shadow prices in a discrete economic model can serve as market equilibrium prices has not been addressed in the related literature. The present paper addresses this issue in an empirical setting. Using a tradable pollution permit market as an example, where firms’ YES/NO type technology adoption decisions are represented by binary variables, we show that the average shadow price of tradable permits can be interpreted as the equilibrium price only when certain conditions related to the cost structure and emission levels hold. On the other hand, we show that an iterative procedure based on individual firms’ cost minimizing behavior presents a better approach for finding a price that can eliminate or reduce the gap between demand and supply of permits in the market.     

Fairness versus efficiency in charging for the use of common facilities

The problem of efficiency vs fairness is considered in relation to the splitting of costs for shared facilities between users. This is considered as a result of a problem of sharing the cost of the provision of central computing facilities between different faculties in a large university, but the basic problem is widespread. A linear programming model is considered in order to minimise cost. The dual of this model is shown to correspond to an efficient allocation of costs. An alternative optimal dual solution is shown to give a ‘fair’ solution according to criteria resulting from cooperative game theory.     

Multi-period capacity expansion for a local access telecommunications network

In this paper, we examine a multi-period capacity expansion problem for a local access telecommunications network with a tree topology. Capacity expansion is realized through the installation of concentrators at the nodes and cables on the links of the network. Clearly, the installation of concentrators reduces the need for additional cables, and conversely. The goal is to find the least cost alternative to satisfy the demand. A heuristic approach is proposed to solve this problem, where local installation decisions at each node are propagated in the network. This information is then used to adjust prices that guide the decision process from one iteration to the next, until a fixed point is reached. Numerical results are reported on problem instances based on different cost and demand structures.     

A postscript on aggregate Farrell efficiencies

In this note we derive alternative weighting schemes that complement those of Färe and Zelenyuk (2003) for consistent aggregation of Farrell efficiencies when the technology exhibits (global) constant returns to scale.