Essays on instrumental variables

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Abstract/Contents

Abstract
This paper concerns inference on the coefficient of a single endogenous variable in the instrumental variables model when some knowledge of the first stage sign is known to the researcher. To study the properties of tests in the IV model that have correct size under weak instruments, current literature often focus on tests that are invariant to orthogonal transformations of the instruments. In the homoskedastic case, the conditional likelihood ratio (CLR) test is considered "near optimal" because, in most cases, the power of the CLR test is shown to be close to that of the two-sided power envelope for this class of invariant tests. We present novel size-correct tests that presume knowledge of the sign of the first-stage coefficients, and are not invariant. We find that when the sign of the first-stage sign is known, one of these tests numerically dominates both CLR and the two-sided invariant power envelope in terms of asymptotic power. To demonstrate the ubiquity of first-stage sign knowledge in empirical work, we survey papers published in the American Economic Review 2014-2018 that use instrumental variables and find that over 80% presume knowledge of the first-stage sign. These findings suggest a larger class of tests that researchers may consider, both in studying the optimality of tests, and in empirical research

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2020; ©2020
Publication date 2020; 2020
Issuance monographic
Language English

Creators/Contributors

Author Mills, Benjamin Sean
Degree supervisor Hong, Han
Thesis advisor Hong, Han
Thesis advisor Romano, Joseph P, 1960-
Thesis advisor Wolak, Frank A
Degree committee member Romano, Joseph P, 1960-
Degree committee member Wolak, Frank A
Associated with Stanford University, Department of Economics

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Benjamin Mills
Note Submitted to the Department of Economics
Thesis Thesis Ph.D. Stanford University 2020
Location electronic resource

Access conditions

Copyright
© 2020 by Benjamin Sean Mills

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