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Stochastic Frontiers using Stata

Authors: BELOTTI, FEDERICO; DAIDONE, SILVIO; ILARDI, GIUSEPPE; ATELLA, VINCENZO;

Stochastic Frontiers using Stata

Abstract

This paper describes sfcross and sfpanel, two new Stata commands for the estimation of cross-sectional and panel data stochastic frontier models. sfcross extends the ocial frontier capabilities by including additional models (Greene 2003; Wang 2002) and command functionality, such as the possibility to manage complex survey data characteristics. Similarly, sfpanel allows to estimate a much wider range of time-varying ineciency models compared to the ocial xtfrontier command including, among the others, the Cornwell et al. (1990) and Lee and Schmidt (1993) models, the exible model of Kumbhakar (1990), the ineciency eects model of Battese and Coelli (1995) and the \true" xed and random-eects models developed by Greene (2005a). A brief overview of the stochastic frontier literature, a description of the two commands and their options and illustrations using simulated and real data are provided.

Country
Italy
Related Organizations
Keywords

panel data, cross-sectional, stochastic frontier analysis, st000, stochastic frontier analysis, cross-sectional, panel data, Settore SECS-P/05 - ECONOMETRIA, 310, st000

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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