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Alternative Techniques for Estimation of Cross‐Section Gravity Models
Author(s) -
Egger Peter
Publication year - 2005
Publication title -
review of international economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.513
H-Index - 58
eISSN - 1467-9396
pISSN - 0965-7576
DOI - 10.1111/j.1467-9396.2005.00542.x
Subject(s) - estimator , econometrics , economics , estimation , contrast (vision) , dimension (graph theory) , cross section (physics) , per capita , cross sectional data , section (typography) , hausman test , gravity model of trade , mathematics , statistics , fixed effects model , panel data , macroeconomics , computer science , physics , population , demography , management , quantum mechanics , artificial intelligence , sociology , pure mathematics , operating system
This paper compares four different estimators with respect to their suitability for cross‐section gravity model estimation. In many circumstances, a Hausman–Taylor approach can be recommended. This framework may provide consistent parameter estimates, when OLS or the traditional random‐effects model are biased. In contrast to the fixed‐effects approach, it allows to estimate parameters of variables such as GDP or GDP per capita, which vary only in a single dimension. The Hausman–Taylor model deserves attention in the estimation of cross‐sectional gravity models.