Symmetric decompositions of cost variation

In this paper a number of symmetric, empirically implementable decompositions of the cost variation (in difference and ratio form) of a production unit are developed. The components distinguished are price level change, technical efficiency change, allocative efficiency change, technological change, scale of activity change, and price structure change. Given data from a (balanced) panel of production units, all the necessary ingredients for the computation of the various decompositions can be obtained by using linear programming techniques (DEA). An application is provided

The flexible reverse approach for decomposing economic inefficiency:With an application to Taiwanese banks

Profit inefficiency is conventionally decomposed into two mutually exclusive components representing profit loss due to technical inefficiency, and, through duality theory, a residual interpreted as allocative inefficiency. Although conventional models solve technical inefficiencies by reducing inputs and increasing outputs, achieving profit efficiency may require larger than observed input quantities and/or smaller than observed output quantities. However, overcoming the restrictions in the direction of the technical adjustments in input and output quantities demands flexibility that existing models do not offer. Thus, to achieve this flexibility, we introduce an endogenous profit inefficiency measure that reverses the subordinate role played by allocative inefficiency. The new measure is based on a monetized version of the weighted additive model seeking maximum feasible profit gains without restricting inputs and output adjustments. This prevents the conflicting prescriptions that the conventional model may offer in the form of non-monotonic input and output changes, thereby reducing adjustment costs. We apply the proposed model to real data from financial institutions. The differences in the managerial and policy recommendations for optimal resource allocation are relevant, with the conventional model wrongly recommending reductions in inputs in terms of the amounts and scale required to maximize profit.</p

The measurement of profit, profitability, cost and revenue efficiency through data envelopment analysis: A comparison of models using BenchmarkingEconomicEfficiency.jl

We undertake a systematic comparison of existing models measuring and decomposing the economic efficiency of organizations. For this purpose we introduce the package BenchmarkingEconomicEfficiency.jl for the open-source Julia language including a set of functions to be used by scholars and professionals working in the fields of economics, management science, engineering, and operations research. Using mathematical programming methods known as Data Envelopment Analysis, the software develops code to decompose economic efficiency considering alternative definitions: profit, profitability, cost and revenue. Economic efficiency can be decomposed, multiplicative or additively, into a technical (productive) efficiency term and a residual term representing allocative (or price) efficiency. We include traditional decompositions like the radial efficiency measures associated with the input (cost) and output (revenue) approaches, as well as new ones corresponding to the Russell measures, the directional distance function, DDF (including novel extensions like the reverse DDF, modified DDF, or generalizations based on Hölder norms), the generalized distance function, and additive measures like the slack based measure, their weighted variants, etc. Moreover, regardless the underlying economic efficiency model, many of these technical inefficiency measures are available for calculation in a computer software for the first time. This article details the theoretical methods and the empirical implementation of the functions, comparing the obtained results using a common dataset on Taiwanese BanksJosé L. Zofío thanks the grant PID2019-105952 GB-I00 funded by Ministerìo de Ciencia e Innovación/ Agencia Estatal de Investigación /10.13039/50110001103