Estimation and testing of stochastic frontier models using variational Bayes
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DOI: 10.1007/s11123-018-0531-0
Abstract: We show how a wide range of stochastic frontier models can be estimated relatively easily using variational Bayes. We derive approximate posterior distributions and point estimates for parameters and inefficiency effects for (a) time invariant… read more here.
Keywords: variational bayes; using variational; estimation testing; frontier models ... See more keywords
Cross-constrained Measuring the Cost-environment Efficiency in Material Balance Based Frontier Models
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DOI: 10.1016/j.ecolecon.2017.06.006
Abstract: Frontier models based on the material balance principle (MBP) constitute a major group of environmentally-adjusted efficiency methods that produce environmental and economic outcomes, but fail to integrate them with measures of allocative efficiency in order… read more here.
Keywords: material balance; frontier models; allocative efficiency; cross constrained ... See more keywords
Quantile stochastic frontier models with endogeneity
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DOI: 10.1016/j.econlet.2020.108964
Abstract: In this paper, we extend Jradi et al. (2019). First, we use the asymmetric Laplace distribution which is a more reasonable assumption in quantile models. Second, we address the issue of statistical inference for the… read more here.
Keywords: endogeneity quantile; frontier models; stochastic frontier; jradi 2019 ... See more keywords
Quantile estimation of stochastic frontier models with the normal–half normal specification: A cumulative distribution function approach
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DOI: 10.1016/j.econlet.2021.109998
Abstract: 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… read more here.
Keywords: stochastic frontier; cumulative distribution; frontier models; normal half ... See more keywords
Dynamic quantile stochastic frontier models
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DOI: 10.1016/j.ijhm.2020.102588
Abstract: Abstract This paper introduces the concept of dynamic quantile regression to the context of stochastic frontier models. We develop a Dynamic Quantile Stochastic Frontier (DQSF) in a Bayesian framework to take into account possible shifts… read more here.
Keywords: dynamic quantile; model; frontier models; stochastic frontier ... See more keywords