A Probabilistic Approach for Assessing the Significance of Contextual Variables in Nonparametric Frontier Models: an Application for Brazilian Banks

This article presents an empirical application illustrating the use of a nonparametric frontier model relying on a probabilistic definition of the production frontier. The significance of the variable nonperforming loans in productive efficiency is assessed, for a sample of Brazilian banks, using the concepts of condicional and unconditional efficiency measures, in a context where it is not necessary to impose any particular distribution for the production data. The analysis is robust relative to the assumptions of separability.

Fractional regression models for second stage DEA efficiency analyses

Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models are the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed.Second-stage DEA; Fractional data; Specification tests; One outcomes; Two-part models.

Technological regimes, Schumpeterian patterns of innovation and firm level productivity growth

The paper investigates the relationships between technological regimes and firm-level productivity performance, and it explores how such a relationship differs in different Schumpeterian patterns of innovation. The analysis makes use of a rich dataset containing data on innovation and other economic characteristics of a large representative sample of Norwegian firms in manufacturing and service industries for the period 1998-2004. First, we decompose TFP growth into technical progress and efficiency changes by means of data envelopment analysis. We then estimate an empirical model that relates these two productivity components to the characteristics of technological regimes and a set of other firm-specific factors. The results indicate that: (1) TFP growth has mainly been achieved through technical progress, while technical efficiency has on average decreased; (2) the characteristics of technological regimes are important determinants of firm-level productivity growth, but their impacts on technical progress are different from the effects on efficiency change; (3) the estimated model works differently in the two Schumpeterian regimes. Technical progress has been more dynamic in Schumpeter Mark II industries, while efficiency change has been more important in Schumpeter Mark I markets.TFP growth; technical progress; technical efficiency; technological regimes; Schumpeterian patterns of innovation; CIS data

Evaluating the Effect of Operational Conditions and Practices on Warehouse Performance

Analyzing warehouse performance across different environments is critical to improving overall productivity and reducing costs. Although two-stage DEA estimators have been shown to be statistically consistent, the finite sample bias of DEA in the first stage carries over to the secondstage regression, which causes bias in the estimated coefficients of the contextual variables. The bias is particularly severe when the contextual variables are correlated with inputs. To address this shortcoming, we apply insights from Johnson and Kuosmanen (2010), who demonstrate that DEA can be formulated as a constrained special case of the Convex Nonparametric Least Squares (CNLS) regression to develop a new semiparametric one-stage estimator. The new model is applied to a set of warehouses to illustrate its performance

Management of agricultural research center in Brazil: a DEA application using a dynamic GMM approach.

In this paper, we measure the performance for each of the Brazilian Agricultural Research Corporation research center by means of a Data Envelopment Analysis model. Performance data are available for a panel covering the period 2002-2009. The approach is instrumentalist, inte sense of Ramalho, Ramalho, and Henriques (2010). We investigate the effects onf performance of contextual variable indicator related to the intensity of partnerships and revenue generation. For this purpose, we propose a fractional nonlinear regression model and dynamic GGM 9Generalized Method of Moments) estimation. We do not rule out the endogeneity of the contextual variables, cross-sectional correlation or autocorrelation within the panel. We conclude that revenue generation and previous performance scores are statistically significant and positively associated with actual performance

Bank Efficiency and Default in Brazil: Causality Tests

Periods of Financial Stability are associated to low bank efficiency and high non-performing loans in credit portfolios. Therefore, this paper studies the relationship between bank efficiency and non-performing loans. To evaluate the bank efficiency, we employ a Data Envelopment Analysis. We employ the Arelano-Bond dynamic panel approach and a panel-VAR to test whether non-performing loans Granger cause bank efficiency (bad luck hypothesis) or whether bank efficiency affects loan quality (management with risk aversion). Empirical results for the Brazilian case corroborate the second hypothesis.

Determinants of Scale Efficiency in the Brazilian Third-Party Logistics Industry from 2001 to 2009

This article investigates the Brazilian third-party logistics (3PL) sector which, increasingly competitive, offers clients a wide variety of services/information technologies in the quest to bolster efficiency. The main research objective is to determine which variables significantly impact 3PLs scale efficiency by applying two-stage DEA (Data Envelopment Analysis). Based on an unbalanced panel model, data from the annual study published by Revista Tecnologística (years 2001–2009) were analyzed. Results corroborate evidence in the literature that coordination mechanisms in the supply chain, supported by the availability of real time information and inventory synchronization, favor a more rational allocation of resources (inputs) to client demands (outputs)

Efficiency Measurement in the Local Public Sector: Econometric and Mathematical Programming Frontier Techniques

Local government in advanced economies is undergoing a period of rapid reform aimed at enhancing its efficiency and effectiveness. Accordingly, the definition, measurement and improvement of organisational performance is crucial. Despite the importance of efficiency measurement in local government it is only relatively recently that econometric and mathematical frontier techniques have been applied to local public services. This paper attempts to provide a synoptic survey of the comparatively few empirical analyses of efficiency measurement in local government. We examine both the measurement of inefficiency in local public services and the determinants of local public sector efficiency. The implications of efficiency measurement for practitioners in local government are examined by way of conclusion.

The Impact of Supervisory Monitoring On High-End Retail Sales Productivity

Based on a two-stage analysis of a panel of data on 12 outlets of a high-end retailer for 24 months, we investigate how the level of supervisory monitoring affects retail sales productivity. In the first stage, we use Data Envelopment Analysis (DEA) to compute the relative productivity of retail outlets in using their labor and capital resources to generate store sales. In the second stage, we regress the logarithm of DEA scores on contextual variables to obtain consistent estimators of the impact of contextual variables on productivity (Banker and Natarajan in Operation Research 56:48-58, 2008). Contrary to agency theoretic prediction that supervisory monitoring leads to an increase in retail sales productivity, our empirical results indicate that the higher the level of supervisory monitoring, the lower is the retail sales productivity for high-end retail outlets

Identification of Segments of Thermo Energy Plants with a Latent Class Model

This paper identifies different groups in a cost function framework of thermo energy plants belonging to EDP-Electricity of Portugal. In particular, we have clustered the sample - comprising data for years 1987 to 2006 - into two groups. To do so, we have implemented a stochastic frontier latent class model, a procedure that also permits us to analyze also the efficiency of the thermo energy plants with respect to their own frontiers. The results reveal that some of the plants could improve their efficiency levels substantially.cost efficiency; latent class model; thermo energy plants; stochastic frontier.