Two-Way Models for Gravity
Koen Jochmans
The Review of Economics and Statistics, 2017, vol. 99, issue 3, 478-485
Abstract:
Empirical models for dyadic interactions between n agents often feature agent-specific parameters. Fixed-effect estimators of such models generally have bias of order n −1 , which is nonnegligible relative to their standard error. Therefore, confidence sets based on the asymptotic distribution have incorrect coverage. This paper looks at models with multiplicative unobservables and fixed effects. We derive moment conditions that are free of fixed effects and use them to set up estimators that are n -consistent, asymptotically normally distributed, and asymptotically unbiased. We provide Monte Carlo evidence for a range of models. We estimate a gravity equation as an empirical illustration.
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (32)
Downloads: (external link)
http://www.mitpressjournals.org/doi/pdf/10.1162/REST_a_00620 (application/pdf)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Two-Way Models for Gravity (2017)
Working Paper: Two-Way Models for Gravity (2017)
Working Paper: Two-way models for gravity (2015) 
Working Paper: Two-way models for gravity (2015) 
Working Paper: Two-way models for gravity (2015) 
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:tpr:restat:v:99:y:2017:i:3:p:478-485
Ordering information: This journal article can be ordered from
https://mitpressjour ... rnal/?issn=0034-6535
Access Statistics for this article
The Review of Economics and Statistics is currently edited by Pierre Azoulay, Olivier Coibion, Will Dobbie, Raymond Fisman, Benjamin R. Handel, Brian A. Jacob, Kareen Rozen, Xiaoxia Shi, Tavneet Suri and Yi Xu
More articles in The Review of Economics and Statistics from MIT Press
Bibliographic data for series maintained by The MIT Press ().