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Re: st: mean group


From   Markus Eberhardt <[email protected]>
To   [email protected]
Subject   Re: st: mean group
Date   Tue, 21 Jun 2011 15:04:50 +0100

Well, Stata dropped your lagged dependent variable because it's not a
lagged dependent variable in the panel sense! "lngdpc0", I would
guess, is log of GDP per capita IN THE BASE YEAR. You cannot have a
variable that does not change over time in these dynamic regressions.
This is different from a cross-section regression, like in Mankiw,
Romer & Weil (1992, QJE). You need to have a variable which represents
the level of GDP IN THE PREVIOUS PERIOD (t-1), not in the base year.
Also, why do you label all variables with the prefix d-, even if they
seem to be levels variables?
In the example you quote, which is from my demo ado, you can see that
there are growth rates (d-  prefix) and lagged levels (l- prefix) to
clearly distinguish them from each other. If you use this setup you'll
be able to run an ECM which delivers the results you're looking for.
m

Markus Eberhardt
ESRC Post-doctoral Research Fellow, Centre for the Study of African
Economies, Department of Economics, University of Oxford
Stipendiary Lecturer, St Catherine's College, Oxford

web: http://sites.google.com/site/medevecon/home
email: [email protected]
twitter: http://twitter.com/sjoh2052
mail: Centre for the Study of African Economies, Department of
Economics, Manor Rd, Oxford OX1 3UQ, England




On 21 June 2011 14:56, Nahla Samargandi <[email protected]> wrote:
> Thank you indeed for replying.
> There are more that one command regarding the MG which of them that use to estimate Error correction Model  - TO estimate a long - short Run relationship  (ARDL ) Autoregressive distributed lag )
>
> 1-
>  ECM - MG
> xtmg dlY llY llW llK dlW dlK , trend robust
>
> 2-
> nlcom ((_b[llW])/(-_b[llY])) ((_b[llK])/(-_b[llY])) , post
>
> I got this result from the first one,
> gen dgdp=l.gdp etc
>
>  xtmg  dgdpg lngdpc0   deducation  dlnca  dlnpop  dfl1, trend
>
> Pesaran & Smith (1995) Mean Group estimator
> All coefficients present represent averages across groups (cou)
> Coefficient averages computed as unweighted means
> Mean Group type estimation                      Number of obs      =      1306
> Group variable: cou                             Number of groups   =        52
>                                                Obs per group: min =        12
>                                                               avg =      25.1
>                                                               max =        28
>                                                Wald chi2(4)       =     36.51
>                                                Prob > chi2        =    0.0000
> ------------------------------------------------------------------------------
>       dgdpg |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
>     lngdpc0 |  (omitted)
>  deducation |    8.75228   11.61385     0.75   0.451    -14.01045    31.51501
>       dlnca |   5.732087   1.806081     3.17   0.002     2.192234     9.27194
>      dlnpop |   500.2783   321.8142     1.55   0.120    -130.4659    1131.022
>        dfl1 |  -6.580965   1.245776    -5.28   0.000    -9.022641    -4.13929
>  __000007_t |   .2274885    .151299     1.50   0.133    -.0690521    .5240291
>       _cons |  -11.20187   8.003771    -1.40   0.162    -26.88897    4.485233
> ------------------------------------------------------------------------------
> Root Mean Squared Error (sigma): 4.1932
> Variable __000007_t refers to a group-specific linear trend.
> Share of group-specific trends significant at 5% level: 0.038 (= 2 trends)
>
> however , I cant interpret the result, because I need to know the short and long run effect , I don't think the estimation above is the right one for this.
>
> regarding this command
>
> nlcom ((_b[llW])/(-_b[llY])) ((_b[llK])/(-_b[llY])) , post
> could you tell me is this the right one ? if yes, where i have to replace my variable?
>
> Best regards,
> Nahla
>
> ________________________________________
> From: [email protected] [[email protected]] On Behalf Of Markus Eberhardt [[email protected]]
> Sent: 21 June 2011 14:20
> To: [email protected]
> Subject: Re: st: mean group
>
> xtpmg (Blackburn and Frank) with option -mg- gives you an ECM version
> (well, it reports the implied long-run results as well as the
> short-run results; an option to see the results country by country is
> also given).
>
> ARDL means autoregressive distributed lag, which is a levels
> regression with lagged dependent variable and contemporaneous and
> lagged covariates. This is mathematically equivalent to an ECM, which
> has the first difference of y as dependent variable and then adds
> lagged levels of y and x as well as contemporaneous and lagged
> differences of x (and lagged ones of y, too) as covariates. Hendry
> (1995) 'Dynamic Econometrics' has a discussion for a single time
> series how ARDL is the encompassing specification for a lot of dynamic
> models, including ECM. In terms of interpretation of coefficients you
> will get the same long-run results, although they're constructed
> differently. Furthermore, an ECM approach allows you to impose a
> long-run relationship (y-beta*x) as 'ecm' variable in order to focus
> on short-run dynamics and the speed of convergence/error correction
> mechanism.
>
> If you create lags manually (gen lx=l.x etc.) you can also use my xtmg command.
>
> Both xtpmg and xtmg commands can be found using -findit- in Stata.
>
> Best
> m
>
> Markus Eberhardt
> ESRC Post-doctoral Research Fellow, Centre for the Study of African
> Economies, Department of Economics, University of Oxford
> Stipendiary Lecturer, St Catherine's College, Oxford
>
> web: http://sites.google.com/site/medevecon/home
> email: [email protected]
> twitter: http://twitter.com/sjoh2052
> mail: Centre for the Study of African Economies, Department of
> Economics, Manor Rd, Oxford OX1 3UQ, England
>
>
>
>
> On 21 June 2011 13:30, Nahla Samargandi <[email protected]> wrote:
>> Hi,
>> I would like know the right command for mean group MG  estimator in error correction model form (ARDL)developed by Pesaran 1999,
>>
>> thank you in advance for your help
>> *
>> *   For searches and help try:
>> *   http://www.stata.com/help.cgi?search
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>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
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>

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