Why is SFA/ SPF more commonly used with PSM instead of DEA?

31 January 2020 1 10K Report

A number of research papers (Bravo-Ureta et al. 2011; Rodriguex et al. 2007; Greene 2010, etc.) investigating the effect of a treatment on the some kind of technical efficiency (TE) consider stochastic production frontier (SPF) for technical efficiency estimation, employing Stochastic Frontier Analysis (SFA) instead of Data Envelopment Analysis (DEA), which is followed by matching approach like Propensity Score Matching to eliminate bias in impact evaluation. Is there any assumption/ limitation within DEA that restricts its use with matching algorithms or is there any added benefit of using matching together with SFA or is it just a research gap that can be explored?

Anirban Pal

Thank you Ahmed Mohamed Habib

for your reply. I agree with your point that the application of either DEA or SFA for efficiency estimation is fairly common and each method has its own set of benefits and drawbacks. However, what I am looking to understand is why research comparing technical efficiency (TE) across treatment and control groups prefer to use SFA instead of DEA as in

Article Technical Efficiency Analysis Correcting for Biases from Obs...

and other similar studies.

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