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Re: st: How to generate a table with the outcomes of unit-root tests from unbalanced panel?
From
Yuval Arbel <[email protected]>
To
[email protected]
Subject
Re: st: How to generate a table with the outcomes of unit-root tests from unbalanced panel?
Date
Fri, 18 Nov 2011 10:14:14 +0200
Eventually, I found the following solution to the problem:
. bysort appt: gen reduct1=reduct_per[_n-1]
(9547 missing values generated)
. bysort appt: gen dreduct=reduct_per-reduct_per[_n-1]
(9547 missing values generated)
. bysort appt: reg dreduct reduct1,noconstant
-------------------------------------------------------------------------------------------------------------------
-> appt = 2851
Source | SS df MS Number of obs = 27
-------------+------------------------------ F( 1, 26) = 0.83
Model | 6.97026022 1 6.97026022 Prob > F = 0.3703
Residual | 218.02974 26 8.38575922 R-squared = 0.0310
-------------+------------------------------ Adj R-squared = -0.0063
Total | 225 27 8.33333333 Root MSE = 2.8958
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | .0061958 .0067958 0.91 0.370 -.0077733 .0201648
------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------
-> appt = 2862
Source | SS df MS Number of obs = 36
-------------+------------------------------ F( 1, 35) = 0.00
Model | 0 1 0 Prob > F = 1.0000
Residual | 625 35 17.8571429 R-squared = 0.0000
-------------+------------------------------ Adj R-squared = -0.0286
Total | 625 36 17.3611111 Root MSE = 4.2258
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | 0 .0509647 0.00 1.000 -.1034639 .1034639
------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------
-> appt = 2906
Source | SS df MS Number of obs = 93
-------------+------------------------------ F( 1, 92) = 1.22
Model | 91.7955488 1 91.7955488 Prob > F = 0.2731
Residual | 6946.26495 92 75.5028799 R-squared = 0.0130
-------------+------------------------------ Adj R-squared = 0.0023
Total | 7038.0605 93 75.6780699 Root MSE = 8.6892
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | -.0265432 .0240726 -1.10 0.273 -.0743535 .0212672
------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------
-> appt = 2907
Source | SS df MS Number of obs = 102
-------------+------------------------------ F( 1, 101) = 3.28
Model | 90.3682494 1 90.3682494 Prob > F = 0.0732
Residual | 2784.53244 101 27.5696281 R-squared = 0.0314
-------------+------------------------------ Adj R-squared = 0.0218
Total | 2874.90069 102 28.1853009 Root MSE = 5.2507
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | -.0418621 .0231222 -1.81 0.073 -.0877303 .0040061
------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------
-> appt = 2908
Source | SS df MS Number of obs = 98
-------------+------------------------------ F( 1, 97) = 0.00
Model | 0 1 0 Prob > F = 1.0000
Residual | 7225 97 74.4845361 R-squared = 0.0000
-------------+------------------------------ Adj R-squared = -0.0103
Total | 7225 98 73.7244898 Root MSE = 8.6304
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | 0 .0195403 0.00 1.000 -.0387822 .0387822
------------------------------------------------------------------------------
-------------------------------------------------------------------------------------------------------------------
-> appt = 2912
Source | SS df MS Number of obs = 84
-------------+------------------------------ F( 1, 83) = 0.00
Model | 0 1 0 Prob > F = 1.0000
Residual | 4900 83 59.0361446 R-squared = 0.0000
-------------+------------------------------ Adj R-squared = -0.0120
Total | 4900 84 58.3333333 Root MSE = 7.6835
------------------------------------------------------------------------------
dreduct | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
reduct1 | 0 .0234018 0.00 1.000 -.0465453 .0465453
------------------------------------------------------------------------------
On Fri, Nov 18, 2011 at 9:02 AM, Muhammad Anees <[email protected]> wrote:
> As the -help dfuller- suggest -dfuller- only saves the following
> Scalars in r() about which you would already be familiar:
>
>
> r(N) number of observations
> r(lags) number of lagged differences
> r(Zt) Dickey-Fuller test statistic
> r(p) MacKinnon approximate p-value (if there is a constant or
> trend in associated regression)
>
> In running the -reg- and -esttab- is of limited help in earlier
> example. You need to seek help of the ado which results the
> interpolated Dickey-Fuller t-statistic. I hope this shed some light on
> what you need to do.
>
> On Fri, Nov 18, 2011 at 10:52 AM, Yuval Arbel <[email protected]> wrote:
>> I believe what I need is to construct a macro with -foreach- command
>> and for each appt number to carry out the -dfuller- command.
>> However, I don't know how exactly to construct such a macro. Can you assist me?
>>
>> On Thu, Nov 17, 2011 at 5:58 PM, Austin Nichols <[email protected]> wrote:
>>> Yuval Arbel <[email protected]>:
>>> I doubt you really want -dfuller- output. You should read at minimum:
>>> http://www.econ.cam.ac.uk/faculty/pesaran/lm.pdf
>>> http://www.econ.cam.ac.uk/faculty/pesaran/wp11/Interpretation-Panel-Unit-September-2011.pdf
>>> and see especially the lit review in the second for recent work.
>>>
>>> On Thu, Nov 17, 2011 at 10:05 AM, Muhammad Anees <[email protected]> wrote:
>>>> -Dfuller- runs regression where the Z(t) is the coefficient of the
>>>> estimated lagged Dep.Var with D.(Dep.Var) as the dependent variable.
>>>> Using the estout option after the regress command could do what you
>>>> want.
>>>>
>>>> example is give from my results
>>>> energyusekt | Coef. Std. Err. t P>|t| [95% Conf. Interval]
>>>> -------------+----------------------------------------------------------------
>>>> energyusekt |
>>>> L1. | .0349052 .0078295 4.46 0.000 .018976 .0508345
>>>> |
>>>> _cons | 384.8409 365.0711 1.05 0.299 -357.9018 1127.584
>>>> ------------------------------------------------------------------------------
>>>>
>>>> . estimates store a
>>>>
>>>> . esttab
>>>>
>>>> ----------------------------
>>>> (1)
>>>> D.energyus~t
>>>> ----------------------------
>>>> L.energyus~t 0.0349***
>>>> (4.46)
>>>>
>>>> _cons 384.8
>>>> (1.05)
>>>> ----------------------------
>>>> N 35
>>>> ----------------------------
>>>> t statistics in parentheses
>>>>
>>>> Now using other Stata tools, it can easily be exported.
>>>> regress d.energyusekt l.energyusekt
>>>> On Thu, Nov 17, 2011 at 7:49 PM, Yuval Arbel <[email protected]> wrote:
>>>>> Dear statalist participants,
>>>>>
>>>>> I have an unbalanced panel of apartments, which contains 9,547 apartments.
>>>>>
>>>>> I ran the following commands:
>>>>>
>>>>> . tsset t
>>>>> time variable: t, 1 to 507798
>>>>> delta: 1 unit
>>>>>
>>>>> . dfuller reduct_per if appt==2851
>>>>>
>>>>> Dickey-Fuller test for unit root Number of obs = 27
>>>>>
>>>>> ---------- Interpolated Dickey-Fuller ---------
>>>>> Test 1% Critical 5% Critical 10% Critical
>>>>> Statistic Value Value Value
>>>>> ------------------------------------------------------------------------------
>>>>> Z(t) -0.891 -3.736 -2.994 -2.628
>>>>> ------------------------------------------------------------------------------
>>>>> MacKinnon approximate p-value for Z(t) = 0.7910
>>>>>
>>>>> . dfuller reduct_per if appt==2862
>>>>>
>>>>> Dickey-Fuller test for unit root Number of obs = 37
>>>>>
>>>>> ---------- Interpolated Dickey-Fuller ---------
>>>>> Test 1% Critical 5% Critical 10% Critical
>>>>> Statistic Value Value Value
>>>>> ------------------------------------------------------------------------------
>>>>> Z(t) -6.784 -3.668 -2.966 -2.616
>>>>> ------------------------------------------------------------------------------
>>>>> MacKinnon approximate p-value for Z(t) = 0.0000
>>>>>
>>>>> . dfuller reduct_per if appt==2906
>>>>>
>>>>> Dickey-Fuller test for unit root Number of obs = 94
>>>>>
>>>>> ---------- Interpolated Dickey-Fuller ---------
>>>>> Test 1% Critical 5% Critical 10% Critical
>>>>> Statistic Value Value Value
>>>>> ------------------------------------------------------------------------------
>>>>> Z(t) -1.313 -3.518 -2.895 -2.582
>>>>> ------------------------------------------------------------------------------
>>>>> MacKinnon approximate p-value for Z(t) = 0.6233
>>>>>
>>>>> . dfuller reduct_per if appt==2907
>>>>>
>>>>> Dickey-Fuller test for unit root Number of obs = 103
>>>>>
>>>>> ---------- Interpolated Dickey-Fuller ---------
>>>>> Test 1% Critical 5% Critical 10% Critical
>>>>> Statistic Value Value Value
>>>>> ------------------------------------------------------------------------------
>>>>> Z(t) -2.647 -3.509 -2.890 -2.580
>>>>> ------------------------------------------------------------------------------
>>>>> MacKinnon approximate p-value for Z(t) = 0.0836
>>>>>
>>>>> Now, I would like to produce a table where for each apartment I attach
>>>>> the full output of dfuller
>>>>>
>>>>> I wonder, how can I produce such a table in a way that it can be
>>>>> exported in xls. or csv. formats:
>>>>>
>>>>> I thank you in advance for your assistance.
>>>
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/statalist/faq
>>> * http://www.ats.ucla.edu/stat/stata/
>>>
>>
>>
>>
>> --
>> Dr. Yuval Arbel
>> School of Business
>> Carmel Academic Center
>> 4 Shaar Palmer Street, Haifa, Israel
>> e-mail: [email protected]
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
>>
>
>
>
> --
>
> Regards
> ---------------------------
> Muhammad Anees
> Assistant Professor
> COMSATS Institute of Information Technology
> Attock 43600, Pakistan
> www.aneconomist.com
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Dr. Yuval Arbel
School of Business
Carmel Academic Center
4 Shaar Palmer Street, Haifa, Israel
e-mail: [email protected]
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/