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Jackknife Instrumental Variables Estimation

29 Pages Posted: 14 Jul 2000  

Joshua D. Angrist

Massachusetts Institute of Technology (MIT) - Department of Economics; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

Guido W. Imbens

Stanford Graduate School of Business

Alan B. Krueger

Princeton University - Industrial Relations Section; National Bureau of Economic Research (NBER); IZA Institute of Labor Economics

Date Written: February 1995

Abstract

Two-stage-least-squares (2SLS) estimates are biased towards OLS estimates. This bias grows with the degree of over-identification and can generate highly misleading results. In this paper we propose two simple alternatives to 2SLS and limited-information-maximum-likelihood (LIML) estimators for models with more instruments than endogenous regressors. These estimators can be interpreted as instrumental variables procedures using an instrument that is independent of disturbances even in finite samples. Independence is achieved by using a `leave-one-out' jackknife-type fitted value in place of the usual first-stage equation. The new estimators are first-order equivalent to 2SLS but with finite-sample properties superior to those of 2SLS and similar to LIML when there are many instruments. Moreover, the jackknife estimators appear to be less sensitive than LIML to deviations from the linear reduced form used in classical simultaneous equations models.

Suggested Citation

Angrist, Joshua D. and Imbens, Guido W. and Krueger, Alan B., Jackknife Instrumental Variables Estimation (February 1995). NBER Working Paper No. t0172. Available at SSRN: https://ssrn.com/abstract=225083

Joshua Angrist (Contact Author)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
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IZA Institute of Labor Economics

P.O. Box 7240
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Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

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Cambridge, MA 02142
United States
617-253-8909 (Phone)
617-253-1330 (Fax)

Guido W. Imbens

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Alan B. Krueger

Princeton University - Industrial Relations Section ( email )

Princeton, NJ 08544-2098
United States
609-258-4046 (Phone)
609-258-2907 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

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