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From |
"Danny Cohen-Zada" <[email protected]> |

To |
<[email protected]> |

Subject |
Re: st: conditional likelihood ratio test when the cluster option is used in ivreg (weak instrument). |

Date |
Thu, 28 Feb 2008 18:54:19 +0200 |

Professor Austin,

Your advise helped me very much. I performed the AR test with the cluster option and obtained very good result. I only want to be sure that I did everything ok.

Our basic model was

ivreg2 y1 x1 x2 (y2 = z1 ), ffirst robust cluster (x3)

(by the way the clustered t -statistic in this estimation was -2.08)

Since my instrument was potentially weak I wanted a correct p-value (or t -statistic) for the test that the coefficient of y2 is different from zero (in this case y1-y2b0 =y1).

Thus, i regress the following regression:

regress y1 z1 x1 x2, robust cluster (x3)

the t-statisic for the coefficient of z1 is the correct t-statistic for the test that the coefficient of y2 is equal to zero (am i correct?).

I obtained even stronger results. The t-statistic is -2.43.

Am i correct that now i can claim that y2 as a significnat negative effect on y1 based on the -2.43.

Thanks,

Danny

----- Original Message ----- From: "Austin Nichols" <[email protected]>

To: <[email protected]>

Sent: Thursday, February 28, 2008 4:00 PM

Subject: Re: st: conditional likelihood ratio test when the cluster option is used in ivreg (weak instrument).

Danny--

The answer is no, you cannot "trust this result" from a command that

does not allow cluster-robust estimation when you must use clustered

standard errors in the IV (ivreg2) estimation. If clustering is

important, and you have said that it is, and you have a weak

instruments problem, you must either improve the quality of your

instruments by adding/finding more excluded instruments, in which case

you probably want the LIML/CUE options on -ivreg2- (and overID tests),

or you can use a method of inference robust to the presence of weak

instruments that allows clustering, namely Anderson-Rubin tests/conf

regions. I discussed this in some detail at NASUG5, and some of the

material appears in the slides at

http://www.stata.com/meeting/5nasug/wiv.pdf and some in Stata Journal

7(4). On Anderson-Rubin tests/conf regions, see the Dufour and

Taamouti ref linked from http://www.stata.com/meeting/5nasug/wiv.pdf

(though I prefer constructing the confidence region rather than the

projection onto individual axes that they advocate--the latter can be

deceptive if, say, there are two variables measuring a similar

quantity and you can reject that both coefs are simultaneously zero

because the conf ellipse does not include the origin, but the

projections might both overlap zero). Tests are easier than

confidence regions for this approach, obviously.

On Thu, Feb 28, 2008 at 8:09 AM, Danny Cohen-Zada <[email protected]> wrote:

I will try to edit my question to be clearer.

Suppose that i estimate the following iv model with the cluster option.

ivreg2 y1 x1 x2 (y2 = z1 ), ffirst cluster (x3)

I tested that my instrument is weak (using the clustered f-statistic) and

found that my instrument is weak.

Then i run the conditional likelihood ratio test

condivreg y1 x1 x2 (y2= z1)

This command does not have the cluster option.

Supose that i find that the p-value of this test is 0.000 . Can i trust this

result even when i use clustered standard errors in my ivreg estimation.

Thanks

Danny

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