Quantile estimation of stochastic frontier models with the normal–half normal specification: A cumulative distribution function approach

Shirong Zhao

Economics Letters, 2021, vol. 206, issue C

Abstract: In this paper, based on the cumulative distribution function (CDF) method (Jradi et al., 2021) for finding the optimal quantile when estimating stochastic frontier models (SFM) with normal–exponential composite error term, we derive an expression to find the optimal quantile for the SFM with normal–half normal composite error term. We then use Monte-Carlo simulations and the same data set as Jradi et al. (2019) to compare the difference of iteration method (Jradi et al., 2019) and CDF method for the SFM with normal–half normal specification. The simulations and empirical application illustrate that both methods work well.

Keywords: Stochastic frontier models; Quantile regressions; Skewed normal distribution; Efficiency (search for similar items in EconPapers)
JEL-codes: C1 C3 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:206:y:2021:i:c:s0165176521002755

DOI: 10.1016/j.econlet.2021.109998

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