Decomposing profit efficiency using a slack-based directional distance function

This paper develops a slack-based decomposition of profit efficiency based on a directional distance function. It is an alternative to Cooper, Pastor, Aparicio, and Borras (2011)

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

The Directional Profit Efficiency Measure: On Why Profit Inefficiency is either Technical or Allocative

The directional distance function has been introduced in the efficiency literature with the intention of relaxing the fixed orientations represented by its classical input and output counterparts. However, the criteria underlying the choice of its associated directional vector are numerous. When market prices are observed and firms have a profit maximizing behavior, it seems natural to choose as directional vector that projecting inefficient firms towards profit maximizing benchmarks. Based on that choice of directional vector, we introduce the profit efficiency measure and show that, in this general setting, profit inefficiency can be categorized as either technical -for firms situating in the interior of the technology- or allocative -for firms lying on the frontier. We implement and illustrate the analytical model by way of Data Envelopment Analysis techniques, where the profit maximizing benchmark may not be unique, and introduce the necessary optimizing program for profit inefficiency measurement.Directional Distance Function; Profit Efficiency; Technical Efficiency; Allocative Efficiency; Data Envelopment Analysis.

A material balance approach for modelling banks’ production process with non-performing loans

The aim of this to study is to examine how non-performing loans on the balance sheets of Japanese banks affect their performance by adopting a material balance principle. The paper outlines how the material balance conditions can be applied when modelling banks’ production process in the presence of non-performing loans. The paper utilizes the generalized weak G-disposability principle which accounts for the heterogeneity among banks’ input quality. We test how an input-oriented model (non-performing loans are treated as an input), the weak disposability assumption and the adopted material balance approach, affect banks’ performance levels. We apply our test on a sample of Japanese banks over the period 2013 to 2019. Our findings indicate that the input-oriented model and the material balance estimator even if they present similar distributions, they account differently the effect of non-performing loans’ fluctuations over the examined period. In addition, the results under the weak disposability assumption are found to be different compared to the material balance measures and less sensitive to banks’ non-performing loans variation levels. We also provide evidence that the generalized weak G-disposability assumption captures better banks’ performance fluctuations that has been caused by the restructuring of the Japanese banking industry

A Data Envelopment Analysis Toolbox for MATLAB

The Data Envelopment Analysis Toolbox is a new package for MATLAB that includes functions to calculate the main data envelopment analysis models. The package includes code for the standard radial input, output and additive measures, allowing for constant and variable returns to scale, as well as recent developments related to the directional distance function, and including both desirable and undesirable outputs when measuring efficiency and productivity; i.e., Malmquist and Malmquist-Luenberger indices. Bootstrapping to perform statistical analysis is also included. This paper describes the methodology and implementation of the functions, and reports numerical results using a reliable productivity database on US agriculture to illustrate their use

The measurement of revenue inefficiency over time: An additive perspective

In this paper, we measure and decompose revenue inefficiency over time while accounting for all sources of technical inefficiencies. Our proposed decomposition exploits the dual relationship between the weighted additive distance function and revenue inefficiency in Aparicio et al. [1]. With the aid of the Luenberger indicator, we decompose this indicator into productivity change, and overall allocative change components. The importance of such decomposition is that it provides a complete picture of the sources of productivity change, thus obtaining a slack free allocative component. Finally, the model is ap- plied to the French wine sector to illustrate its practicality: we track how revenue inefficiency evolves in French wine regions over the 2004–2013 period, before and after the implementation of Common Market Organization policies in Europe in 200

A Data Envelopment Analysis Toolbox for MATLAB

The Data Envelopment Analysis Toolbox is a new package for MATLAB that includes functions to calculate the main data envelopment analysis models. The package includes code for the standard radial input, output and additive measures, allowing for constant and variable returns to scale, as well as recent developments related to the directional distance function, and including both desirable and undesirable outputs when measuring efficiency and productivity; i.e., Malmquist and Malmquist-Luenberger indices. Bootstrapping to perform statistical analysis is also included. This paper describes the methodology and implementation of the functions, and reports numerical results using a reliable productivity database on US agriculture to illustrate their use

Single period Markowitz portfolio selection, performance gauging and duality : a variation on Luenberger's shortage function

Markowitz portfolio theory (1952) has induced research into the efficiency of portfolio management. This paper studies existing nonparametric efficiency measurement approaches for single period portfolio selection from a theoretical perspective and generalises currently used efficiency measures into the full mean-variance space. Therefore, we introduce the efficiency improvement possibility function (a variation on the shortage function), study its axiomatic properties in the context of Markowitz efficient frontier, and establish a link to the indirect mean-variance utility function. This framework allows distinguishing between portfolio efficiency and allocative efficiency. Furthermore, it permits retrieving information about the revealed risk aversion of investors. The efficiency improvement possibility function thus provides a more general framework for gauging the efficiency of portfolio management using nonparametric frontier envelopment methods based on quadratic optimisation

Evaluating the european bank efficiency using data envelopment analysis : evidence in the aftermath of the recent financial crisis

This paper seeks to contribute to the analysis of the bank efficiency in the European Union in the aftermath of the recent crisis, using Data Envelopment Analysis (DEA) and considering a sample of 485 banks from all current EU member-states between 2011 and 2017. The results obtained confirm the existence of bank inefficiency, and that this inefficiency is mostly due to inefficient managerial performance and bad combinations of the considered bank inputs and outputs. The results also provide enough evidence of appropriate scale production and dynamic technological changes during the considered interval. Moreover, the results obtained using panel estimates to explain the bank total factor productivity changes allow us to conclude that the choices of the banks in terms of the fixed assets, the profit before tax to the average assets, as well as the ratio of the off-balance sheet items to total assets contribute positively to the productivity changes. On the other side, the ratio of the impaired loans to equity, and the bank interest margins are not in line with the total factor productivity changes of the EU banking sector.info:eu-repo/semantics/publishedVersio