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- From: thompson@atlas.socsci.umn.edu (T. Scott Thompson)
- Newsgroups: sci.math.stat
- Subject: Re: A Simple Question about Instrumental Variables
- Message-ID: <thompson.724526579@kiyotaki.econ.umn.edu>
- Date: 16 Dec 92 17:22:59 GMT
- Article-I.D.: kiyotaki.thompson.724526579
- References: <1gm0ruINNee9@matt.ksu.ksu.edu>
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- Reply-To: thompson@atlas.socsci.umn.edu
- Organization: Economics Department, University of Minnesota
- Lines: 41
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-
- bubai@matt.ksu.ksu.edu (Priyabroto) writes:
-
- >Hi,
-
- >I had a small question:
-
- >Let Y = Xb + u (in matrix notation)
-
- >such that Cov(X,u) is not equal to zero.
-
- >Now, we use Z as an instrumental variable where:
-
- >Cov(X,Z) is not equal to zero but,
- >Cov(Z,u) is equal to zero.
-
- >Then, WHY is it that b hat(instr. var) = (Z'X)inverse * Z'y?
-
- I don't understand the question. This is the _definition_ of the IV
- estimator (assuming that Z and X have the same dimensions). The
- statistical motivation for the estimator comes from the fact that
-
- Inverse(Z'X)*Z'y = b + Inverse(Z'X/n)*(Z'u/n)
-
- and the last term converges to zero in large samples due to the law of
- large numbers and the assumption that E(Z'u) = 0.
-
- >As we know b hat = (X'X)inverse * X'y.
-
- This is the definition of the least squares estimator, which is not
- the same as the IV estimator, and which does not converge to b in
- large samples when X and u are correlated.
-
- Perhaps you are asking how to show that the IV estimator and the least
- squares estimator are the same thing. This cannot be done in general.
- The least squares estimator can be thought of as a special case of the
- IV estimator obtained by setting Z = X.
-
- --
- T. Scott Thompson email: thompson@atlas.socsci.umn.edu
- Department of Economics phone: (612) 625-0119
- University of Minnesota fax: (612) 624-0209
-