st: std error on rho post estimate for xtregar

[Alice Nader <Alice.Nader@sabin.org>]

Dear Stata users,

I am having trouble finding the standard error for rho (i.e. rho_fov) after running my unbalanced panel dataset through xtregar.  I have tried the different rhotypes (i.e. onestep, theil, nagar), but these commands all produce different slopes, but none provide the standard errors for rho.

I would much appreciate if someone could provide some assistance and guidance on this matter.  

Best Regards, 
Alice Nader

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Melisa Haytasingh
Sent: Tuesday, November 19, 2013 2:40 PM
To: statalist
Subject: Re: st: How to interpret time dummies in simple difference in difference regression

Hi guys,
thanks for taking the time to help me.

I have to stick with my regressions as they are (i know they seem simple but its ok for now), and just include some notes about it in my study.
I still am not sure about how to interpret the coefficients. Here are the results of the 2 regressions i described before,

                                         GDPpercapita                 Inflation
time                                       3.664***                       0.002

TnT_no_resources            -1734.545                   -1.029

TnTresources                    1708.438                      4.903

barbados_before1970     -2086.949                    1.528

barbados_after1970         2177.933                      2.641

I just need help to interpret one of the coefficients and then I can go from there.

Thanks again guys.

Cheers,
Melisa.

On 18 November 2013 18:46, Austin Nichols <austinnichols@gmail.com> wrote:
> Melisa Haytasingh <prettymelisa@gmail.com>:
> Probably you want to define a new variable RelTim=time-1970 for time 
> relative to the discovery of resources, and then interact that with 
> dummies for each country. Graph your predictions to see that the coef 
> on the dummy for TnT will be the level jump in gdp_percapita and the 
> coef on TnTxRelTim will be the difference in time trends before and 
> after discovery. Using time instead of relative time makes it easy to 
> project your comparisons back to the nonexistent year zero, rather 
> then making comparisons at 1970. It's not clear to me why you would 
> want to assume constant linear growth in gdp_percapita in all 
> countries as your baseline (counterfactual), but linear time trends 
> are popular in these kinds of regressions.
>
> On Mon, Nov 18, 2013 at 7:24 AM, Melisa Haytasingh 
> <prettymelisa@gmail.com> wrote:
>> Hi guys,
>>
>> I'm doing a regression to analyse the difference between 
>> resource-rich Trinidad & Tobago and their resource-poor Caribbean 
>> neighbour, Barbados. I am treating resources (oil and gas) as the 
>> endogenous variable and regressed GDP on 5 variables: a time trend, 
>> dummy taking
>> 1 for all observations for T&T before resources (before 1970), dummy 
>> taking 1 after discovery of resources, dummy taking 1 for obs of 
>> Barbados before 1970 and dummy taking 1 for obs of Barbados after 
>> 1970. The regression looks like this in Stata:
>>
>> -          regression 1:
>>
>> reg gdp_percapita time TnT_no_resources TnTresources
>> barbados_before1970 barbados_after1970, nocons
>>
>> -          regression 2:
>>
>> reg inlfation time TnT_no_resources TnTresources barbados_before1970 
>> barbados_after1970, nocons
>>
>>
>> I am having trouble figuring out how to interpret the results. I 
>> think I need to find the difference between the coefficients like this:
>>  (barbados_before1970 - TnT_no_resources) and (barbados_after1970 -
>> TnTresources) and then compare those figures with each other. But I 
>> am not sure. Also, I am not sure about how to interpret the 
>> coefficient itself on each of the dummies. I tried to look for 
>> similar regressions online and I got a better overall understanding 
>> but still confused about how to interpret. :(
>>
>>
>> Thank you very much for any help.
>>
>>
>> Sincerely,
>>
>> Melisa
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