Frontier Techniques: Contrasting the Performance of (Single-) Truncated Order Regression Methods and Replicated Moments

Ana Paula Martins

EERI Research Paper Series from Economics and Econometrics Research Institute (EERI), Brussels

Abstract: This research contrasts three econometric alternatives for stochastic efficiency frontier analysis: order – inter-quantile – and inverse order regression under the assumption of truncated error term distribution, and replicated moment estimation. The demonstration departs from a simple linear regression form of the effective frontier; truncated (at zero) errors are then added to it for simulation purposes. For order regression, experiments with the standard normal, uniform, exponential, Cauchy and logistic error terms are provided. For complex error structures we rely on normal distributions only. The three alternatives would perform satisfactorily for simple error disturbances, especially if they are normal. With more than one residual added to the dependent variable, the weight of the unrestricted range one can blur the conclusions regarding observation efficiency.

Keywords: Stochastic Frontier Model; Generalized Method of Order Statistics; Minimum Distance Method of Order Statistics; Inverse Order Regression; Replicated Moments; Linear Models. (search for similar items in EconPapers)
JEL-codes: C10 C24 (search for similar items in EconPapers)
Date: 2010-08-10
New Economics Papers: this item is included in nep-ecm and nep-eff
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.eeri.eu/documents/wp/EERI_RP_2010_37.pdf (application/pdf)

Related works:
Journal Article: Frontier Techniques: Contrasting the Performance of (Single-)Truncated Order Regression Methods and Replicated Moments (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eei:rpaper:eeri_rp_2010_37

Access Statistics for this paper

More papers in EERI Research Paper Series from Economics and Econometrics Research Institute (EERI), Brussels Contact information at EDIRC.
Bibliographic data for series maintained by Julia van Hove ().