EconPapers    
Economics at your fingertips  
 

Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection

Arun Advani, Toru Kitagawa and Tymon Słoczyński
Additional contact information
Toru Kitagawa: University College London and cemmap

CAGE Online Working Paper Series from Competitive Advantage in the Global Economy (CAGE)

Abstract: We consider two recent suggestions for how to perform an empirically motivated Monte Carlo study to help select a treatment effect estimator under unconfoundedness. We show theoretically that neither is likely to be informative except under restrictive conditions that are unlikely to be satisfied in many contexts. To test empirical relevance, we also apply the approaches to a real-world setting where estimator performance is known. Both approaches are worse than random at selecting estimators which minimise absolute bias. They are better when selecting estimators that minimise mean squared error. However, using a simple bootstrap is at least as good and often better. For now researchers would be best advised to use a range of estimators and compare estimates for robustness.

Keywords: empirical Monte Carlo studies; program evaluation; selection on observables; treatment effects JEL Classification: C15; C21; C25; C52 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5) Track citations by RSS feed

Downloads: (external link)
https://warwick.ac.uk/fac/soc/economics/research/c ... /411-2019_advani.pdf

Related works:
Journal Article: Mostly harmless simulations? Using Monte Carlo studies for estimator selection (2019) Downloads
Working Paper: Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection (2019) Downloads
Working Paper: Mostly Harmless Simulations? Using Monte Carlo Studies for Estimator Selection (2019) Downloads
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:cge:wacage:411

Access Statistics for this paper

More papers in CAGE Online Working Paper Series from Competitive Advantage in the Global Economy (CAGE) Contact information at EDIRC.
Bibliographic data for series maintained by Jane Snape ().

 
Page updated 2021-06-22
Handle: RePEc:cge:wacage:411