Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79334
Authors: 
Hausman, Jerry
Newey, Whitney
Chao, John
Swanson, Norman
Year of Publication: 
2007
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP22/07
Abstract: 
It is common practice in econometrics to correct for heteroskedasticity.This paper corrects instrumental variables estimators with many instruments for heteroskedasticity.We give heteroskedasticity robust versions of the limited information maximum likelihood (LIML) and Fuller (1977, FULL) estimators; as well as heteroskedasticity consistent standard errors thereof. The estimators are based on removing the own observation terms in the numerator of the LIML variance ratio. We derive asymptotic properties of the estimators under many and many weak instruments setups. Based on a series of Monte Carlo experiments, we find that the estimators perform as well as LIML or FULL under homoskedasticity, and have much lower bias and dispersion under heteroskedasticity, in nearly all cases considered.
Subjects: 
Instrumental Variables , Heteroskedasticity , Many Instruments , Jackknife
JEL: 
C12
C13
C23
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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