Probabilistic frontier regression model for multinomial ordinal type output data

Meena Badade () and T. V. Ramanathan ()
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Meena Badade: Savitribai Phule Pune University
T. V. Ramanathan: Savitribai Phule Pune University

Journal of Productivity Analysis, 2020, vol. 53, issue 3, No 4, 339-354

Abstract: Abstract This paper proposes a probabilistic frontier regression model for multinomial ordinal type output data. We consider some of the output categories as ‘categories of interest’ and the reduction in probability of an output falling into these categories is attributed to the lack in technical efficiency (TE) of the decision-making unit. A measure for TE is proposed to determine the deviations of individual units from the probabilistic frontier of ‘categories of interest’. Simulation results show that the average estimated TE is close to its true value. An application of the proposed model is provided to the data related to the Indian companies, where the categorical output variable is an indicator of return on equity (ROE). Individual TE is obtained for each of the decision-making units (companies under consideration).

Keywords: Multinomial ordinal type output data; Probabilistic frontier regression models; Technical efficiency (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11123-020-00581-x

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