Thanks Professor for the very detailed explanation.
Best regards,
Juehui Shi (Richard)
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RA, TA, and Lecturer
PhD Management Candidate
University at Buffalo, SUNY
School of Management
Department of Operations Management and Strategy
Jacobs Management Center
Buffalo, NY 14260-4000
Contact information
Tel.: (716) 334-9757 [preferred]
Email1: juehuish(a)buffalo.edu
Email2: rchrdshi(a)gmail.com
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https://www.linkedin.com/in/richardrjs
http://ssrn.com/author=2339807
On Sun, Oct 23, 2016 at 8:31 AM, Riccardo (Jack) Lucchetti <
r.lucchetti(a)univpm.it> wrote:
On Wed, 19 Oct 2016, Juehui Shi wrote:
Thanks, Prof. Cottrell.
>
> Professors, I have one additional question.
>
> Although the coefficient estimates of HIP match those of Stata IV Probit
> exactly, I have found that the endogeneity test (Wald) result is a little
> bit different. For example, the HIP give me Wald (t = 4.06864, p =
> 0.0437),
> but the Stata gives me Wald (t = 3.68, p = 0.0551). My sample size N =
> 2204. Cragg-Donald shows 107.096 and both AR and Wald tests reject the
> null
> of weak instruments.
>
> As shown, this is a delicate situation. My question is that should I
> reject
> or not to reject the null of exogeneity in this case? and What might
> attribute to the difference in the test? Thanks.
>
Stata and HIP compute the endogeneity test in a slightly different way,
that is equivalent asymptotically but will give different results in finite
samples.
What I would do if I were you is keep in mind what a test statistic
ultimately is: it's a number that should be "small" in "most"
cases if your
hypothesis was true. The p-value is just a rough indicator of how "small"
your number is. In your case, your number is right on the threshold that we
conventionally use to make a decision and even small modifications in
irrelevant details can push your test either side of the boundary. This
means that any decision you make should be considered as tentative and
provisional.
However, the hypothesis is in this case that your regressor is exogenous.
Fortunately, the consequence of making the wrong decision are rather
benign, because your IV estimates would be consistent anyway (assuming no
other problems, of course). Using an IV estimator when the null is true
only implies that your procedure could be a little inefficient compared to
ordinary, non-IV probit; but OTOH, why care? In the end, you're just
trading some (possible) inefficiency for the sake of robustness.
HTH,
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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