
doi: 10.1561/0800000042
Quantile regression has become one of the standard tools of econometrics. We examine its compatibility with the special goals of stochastic frontier analysis. We document several conflicts between quantile regression and stochastic frontier analysis. From there we review what has been done up to now, we propose ways to overcome the conflicts that exist, and we develop new tools to do applied efficiency analysis using quantile methods in the context of stochastic frontier models. The work includes an empirical illustration to reify the issues and methods discussed, and catalogs the many open issues and topics for future research.
quantile regression, deterministic frontier, Statistics, inefficiency, conditional quantile function, heteroskedasticity, non-linear quantile estimator, stochastic noise
quantile regression, deterministic frontier, Statistics, inefficiency, conditional quantile function, heteroskedasticity, non-linear quantile estimator, stochastic noise
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