Assessing dynamic inefficiency of the Spanish construction sector pre- and post-financial crisis

2016

SSRN Journal

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This article contributes to the efficiency literature by defining, in the context of the data envelopment analysis framework, the directional distance function approach for measuring both technical and scale inefficiencies with regard to the use of individual inputs. The input-specific technical and scale inefficiencies are then aggregated in order to calculate the overall inefficiency measures. Empirical application focuses on a large dataset of Spanish and Portuguese construction companies between 2002 and 2010 and accounts for three inputs: materials, labor and fixed assets. The results show, first, that for both Spanish and Portuguese construction companies, fixed assets are the most technically inefficient input. Second, the most inefficient scale concerns the utilization of material input in both samples; the reason for this inefficiency is that firms tend to operate in the increasing returns to scale portion of technology set. Third, in both samples, large firms have the lowest input-specific technical inefficiencies, but the highest input-specific scale inefficiencies, compared to their small and mediumsized counterparts, and tend to suffer from decreasing returns to scale. Finally, in both samples, input-specific technical inefficiency under constant returns to scale increased during the period of the recent financial crisis, mainly due to the augmentation in scale inefficiency.

Section: Overall and Input-specific Technical And Scale Inefficienciesmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring Inefficiency for Specific Inputs Using Data Envelopment Analysis: Evidence from Construction Industry in Spain and Portugal

2016

SSRN Journal

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“…Therefore, the main aim of the paper is to develop a dynamic production framework for making comparisons across groups of firms (program inefficiency) and within groups of firms (managerial inefficiency). The introduction of production dynamics in models of efficiency is based on Stefanou (2003, 2007) who estimate hyperbolic efficiency measures, and their further extensions to dynamic directional distance functions by Serra et al (2011), Kapelko et al (2014) and Silva et al (2015). Furthermore, this paper builds on the study of Kapelko and Oude Lansink (2017), who developed a dynamic multidirectional inefficiency model (dynamic MEA), but did not distinguish program inefficiency from managerial inefficiency 4 .…”

Section: Introductionmentioning

confidence: 99%

“…One group of studies within this line develop dynamic network models which take the view of multistage production systems (for example, Färe and Grosskopf 1996;Chen 2009;Fukuyama and Weber 2015). In the other group of studies, the firms' production decisions are linked over time through adjustment costs associated with changes in quasi-fixed factors of production Stefanou 2003, 2007;Kapelko et al 2014;Silva et al 2015) 3 . Previous studies did not consider the dynamics of firms production decisions when developing models for measuring the efficiency of groups of firms functioning under heterogeneous technologies.…”

Section: Introductionmentioning

confidence: 99%

Managerial and program inefficiency for European meat manufacturing firms: A dynamic multidirectional inefficiency analysis approach

2017

J Prod Anal

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This paper proposes a dynamic multidirectional inefficiency analysis approach within the context of Data Envelopment Analysis to measuring input-and investmentspecific managerial and program inefficiency for groups of firms characterized by different technologies. Dynamic managerial inefficiency refers to the distance to the firms' group-specific dynamic frontier of best practices, and dynamic program inefficiency measures the difference between the group-specific dynamic frontier and the pooled dynamic frontier. The empirical application focuses on panel data of large meat processing firms in Eastern, Western and Southern Europe over the period [2005][2006][2007][2008][2009][2010][2011][2012]. The results show that Eastern European firms have the highest dynamic managerial inefficiency for all inputs, but have the smallest values for dynamic program inefficiency. Western European firms perform worst in terms of program inefficiency for all inputs, while Southern European firms are the best with regard to dynamic managerial inefficiency. The results also reveal that regardless the dynamic inefficiency dimension considered, investments is the most inefficient input, followed by labor, and materials.

Measuring firms' dynamic inefficiency accounting for corporate social responsibility in the U.S. food and beverage manufacturing industry

Applied Eco Perspectives Pol

2022

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This article proposes an innovative approach to evaluate firms' inefficiency accounting for corporate social responsibility. In the first step, we estimate dynamic inefficiency for each factor of production using data envelopment analysis. Next, we explore differences in inefficiencies between groups of firms of which participation is determined using latent class analysis. The empirical application focuses on the United States food and beverage manufacturing firms over the period 2004-2018. The results distinguish three classes of firms that differ in terms of their inefficiency, their association with external covariates as well as in their input-output profiles.