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Title:Instrumental variable estimation with heteroskedasticity and many instruments PDF Logo
Authors:Hausman, Jerry A.
Newey, Whitney K.
Woutersen, Tiemen
Chao, John
Swanson, Norman
Issue Date:2011
Series/Report no.:Working Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,11
Abstract:This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic efficiency in a range of cases. The standard errors are easy to compute, being like White's (1982), with additional terms that account for many instruments. They are consistent under standard, many instrument, and many weak instrument asymptotics. Based on a series of Monte Carlo experiments, we find that the estimators perform as well as LIML or Fuller (1977) 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
Document Type:Working Paper
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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