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Re: st: First stage F stats - xtivreg
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: st: First stage F stats - xtivreg
Date
Tue, 21 Jun 2011 08:20:53 -0400
Agnese Romiti <[email protected]>
In that case the cluster-robust SE will be biased downward slightly,
resulting in overrejection and your first-stage F stat overstated, but
I expect it will still outperform the SE and F clustering by
region-year. You would have to do simulations matching your exact
setup to be sure; see e.g.
http://www.stata.com/meeting/13uk/nichols_crse.pdf
On Tue, Jun 21, 2011 at 3:27 AM, Agnese Romiti <[email protected]> wrote:
> Hi,
> Thanks again
> In my data I have 19 regions, and around 18 percent of the data in the
> largest region.
>
> Agnese
>
>
> 2011/6/21 Austin Nichols <[email protected]>:
>> Agnese Romiti <[email protected]>:
>> No, you should cluster by region to correctly account for possible
>> serial correlation,
>> assuming you have sufficiently many regions in your data; how many are there?
>> What percent of the data is in the largest region?
>>
>> On Mon, Jun 20, 2011 at 5:19 PM, Agnese Romiti <[email protected]> wrote:
>>> Many thanks Austin,
>>>
>>> I'm actually clustering the standard errors at region-year level
>>> rather than at region because I have one regressor with variability at
>>> region-year level. Is that correct?
>>> Do you think that the high first stage F stats might be a signal of a
>>> bad instrument?Like a failure of the exogeneity requirement?
>>>
>>> Agnese
>>>
>>>
>>> 2011/6/20 Austin Nichols <[email protected]>:
>>>> Agnese Romiti <[email protected]>:
>>>> Are you clustering by region to account for the likely correlation of
>>>> errors within region?
>>>> Also see
>>>> http://www.stata.com/meeting/boston10/boston10_nichols.pdf
>>>> for an alternative model that allows your dep var to be nonnegative.
>>>>
>>>> On Mon, Jun 20, 2011 at 3:49 AM, Agnese Romiti <[email protected]> wrote:
>>>>> Dear Statalist users,
>>>>>
>>>>> I'm running a fixed effect model with IV (xtivreg2) , my dependent
>>>>> variable is a measure of labor supply at the individual level (working
>>>>> hours). Whereas I have an endogenous variable with variation only at
>>>>> regional-year level.
>>>>> My question is about the First stage statistics, the Weak
>>>>> identification test results in an F statistics extremely high which
>>>>> makes me worry about something wrong, i.e. F=3289.
>>>>> Do you have any clue about potential reasons driving this odd result?
>>>>>
>>>>> Many thanks in advance for your help.
>>>>>
>>>>> Agnese
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