A nonparametric methodology for evaluating convergence in a multi-input multi-output setting

A nonparametric methodology for evaluating convergence in a multi-input multi-output setting

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Article ID: iaor201527324
Volume: 246
Issue: 2
Start Page Number: 554
End Page Number: 561
Publication Date: Oct 2015
Journal: European Journal of Operational Research
Authors: ,
Keywords: statistics: data envelopment analysis, decision, construction & architecture
Abstract:

This paper presents a novel nonparametric methodology to evaluate convergence in an industry, considering a multi‐input multi‐output setting for the assessment of total factor productivity. In particular, we develop two new indexes to evaluate s‐convergence and ß‐convergence that can be computed using nonparametric techniques such as Data Envelopment Analysis. The methodology developed is particularly useful to enhance productivity assessments based on the Malmquist index. The methodology is applied to a real world context, consisting of a sample of Portuguese construction companies that operated in the sector between 2008 and 2010. The empirical results show that Portuguese companies tended to converge, both in the sense of s and β, in all construction activity segments in the aftermath of the financial crisis.

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