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Re: st: Panel unit root test


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: Panel unit root test
Date   Mon, 21 Nov 2011 16:58:25 +0000

No; this is not good advice. The d. operator is a better way to do it.
It does the right thing if there are gaps.

Nick

On Mon, Nov 21, 2011 at 3:05 PM, Muhammad Anees <[email protected]> wrote:
> Check creating differenced variables by
>
> bysort ypv: gen dyv=yv-yv[_n-1]
>
> where ypv and yv means your panel variable and your variable of
> interest. Hope this works
>
> On Mon, Nov 21, 2011 at 7:54 PM, Tong, Tingting <[email protected]> wrote:
>> Dear Sir/Madam,
>>
>> I think I should create first differenced variable to see if they are stationary or not.
>> Only after that, I can proceed to check if they have cointegration issues.
>>
>> If they are all stationary, I  just want to use the fixed effect method instead of others.
>>
>> I am sorry if I asked so easy questions. I know there must be some missing observations after make the first difference.
>>
>> Do you know how to deal with these missing variables so I can run the unitroot test on them?
>>
>> When I do unitroot test in Time series variables, it has the missing variable. But the ADF test can still run.
>>
>> Thank you.
>> Tong
>>
>> ________________________________________
>> From: [email protected] [[email protected]] on behalf of Muhammad Anees [[email protected]]
>> Sent: Monday, November 21, 2011 9:45 AM
>> To: [email protected]
>> Subject: Re: st: Panel unit root test
>>
>> The problem inheritedly is because you have missing observations in
>> your data. Before going to explore other issues, you must check of
>> creating such first differenced variables really is what you want.
>>
>> On Mon, Nov 21, 2011 at 7:23 PM, Tong, Tingting <[email protected]> wrote:
>>> Dear All,
>>>
>>> I am very new in Stata and I am going to use PMG method in my thesis.
>>>
>>> I have a question about panel unit root test. My data has 44 panels from 1958 to 2005.
>>>
>>> For the panel unitroot test, i use "help xtunitroot" in stata and it gives me some describtions. I used IPS and had the result like followings:
>>>
>>> . xtunitroot ips lnvadd, lag(aic 8) trend
>>>
>>> Im-Pesaran-Shin unit-root test for lnvadd
>>> -----------------------------------------
>>> Ho: All panels contain unit roots           Number of panels  =     44
>>> Ha: Some panels are stationary            Number of periods =     48
>>> AR parameter: Panel-specific                Asymptotics: T,N -> Infinity
>>> Panel means:  Included                                        sequentially
>>> Time trend:   Included
>>> ADF regressions: 1.14 lags average (chosen by AIC)
>>> ------------------------------------------------------------------------------
>>>                    Statistic      p-value
>>> ------------------------------------------------------------------------------
>>>  W-t-bar              4.6401        1.0000
>>> ------------------------------------------------------------------------------
>>> I think this means lnvadd has unitroot since p-value is very big.
>>>
>>> Then I want to see if i take the first difference of lnvadd, does it still have unit root or become stationary.
>>>
>>> I used generate code and it reported that 44 missing values. I am not sure if this the the right way to get the first difference data in Stata.
>>>
>>> generate lnvaddd1=d1.lnvadd
>>> (44 missing values generated)
>>>
>>> Then I run the unitroot test again for the d1.lnvadd variable i just generated.
>>> . xtunitroot ips  lnvaddd1, lag(aic 8) trend
>>> Im-Pesaran-Shin unit-root test for lnvaddd1
>>> -------------------------------------------
>>> Ho: All panels contain unit roots           Number of panels  =      0
>>> Ha: Some panels are stationary              Number of periods =     47
>>> AR parameter: Panel-specific                Asymptotics: T,N -> Infinity
>>> Panel means:  Included                                        sequentially
>>> Time trend:   Included
>>> ADF regressions: 0.00 lags average (chosen by AIC)
>>> ------------------------------------------------------------------------------
>>>                    Statistic      p-value
>>> ------------------------------------------------------------------------------
>>>  W-t-bar                   .             .
>>> ------------------------------------------------------------------------------
>>>
>>> It is obviously wrong since the number of panels become zero.
>>>
>>> I donot know where goes wrong. All I want to know is that the variable is not stationary in level, so I take first difference, see if they are stationary.
>>> If the data are stationary after taking first difference, then I want to say they are I(1), then I can go to next step to test the cointegration.
>>>

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