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From |
Nahla Samargandi <Nahla.Samargandi@brunel.ac.uk> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: mean group |

Date |
Tue, 21 Jun 2011 20:01:43 +0100 |

Dear Markus, Thank you indeed for your illistartion. I understood why Stata dropped my lagged dependent variable, MY data over the period 1980 to 2008 And you said that I need the level of GDP IN THE PREVIOUS PERIOD (t-1) SO IF I want to have the initial gdp per capita in the dynamic panel data , can i calculate it like this 1981-1980 , 1982-1981 , etc And then I will get no value in 1980 It seems to me like taking the difference, Regarding why I labelled the variables, because I tried to apply the mg using the same formula in your demo lab2, but unfortunately I could not. This the pmg result xtpmg d.gdpg d.lntradegdp d.education d.lnca d.lnpop d.fl1, lr( l2.gdpg fl1) pmg replace ec(ec) Iteration 0: log likelihood = -3332.5242 Iteration 1: log likelihood = -3332.3657 Iteration 2: log likelihood = -3332.3647 Iteration 3: log likelihood = -3332.3647 Pooled Mean Group Regression (Estimate results saved as pmg) Panel Variable (i): cou Number of obs = 1303 Time Variable (t): year Number of groups = 52 Obs per group: min = 12 avg = 25.1 max = 28 Log Likelihood = -3332.365 ------------------------------------------------------------------------------ D.gdpg | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- ec | fl1 | 1.55204 .6458759 2.40 0.016 .2861466 2.817934 -------------+---------------------------------------------------------------- SR | ec | -.0517315 .0498468 -1.04 0.299 -.1494294 .0459665 lntradegdp | -.7894347 1.204742 -0.66 0.512 -3.150686 1.571817 | education | D1. | 1.046573 7.152161 0.15 0.884 -12.97141 15.06455 | lnca | D1. | 5.211071 2.081382 2.50 0.012 1.131637 9.290505 | lnpop | D1. | -124.6077 94.11905 -1.32 0.186 -309.0777 59.86222 | fl1 | D1. | -6.441647 1.344954 -4.79 0.000 -9.077709 -3.805585 | _cons | 7.016672 6.00329 1.17 0.242 -4.74956 18.7829 ------------------------------------------------------------------------------ xtpmg d.gdpg d.lntradegdp d.education d.lnca d.lnpop d.fl1, lr( l2.gdpg fl1) pmg replace ec(ec) now to order to estimate the mg 1-I generate gen dgdp= d.gdpg (difference) gen dfl1=d.fl1 (lag) gen lgdpg= l. gdpg nothing found where name expected r(198); Still I can’t apply mg using your command in my variables, I don’t know why, please could you help me.? > 2- then > ECM - MG > xtmg dgdp llY llW llK dlW dlK , trend robust > > 2- nlcom ((_b[llW])/(-_b[llY])) ((_b[llK])/(-_b[llY])) , post > b[llY])) , post finally , how I cam impose the dummy variable in the pmg and mg , because when I typed xtpmg d.gdpg d.lntradegdp d.education d.lnca d.lnpop d.fl1, lr( l2.gdpg fl1) pmg replace ec(ec) if dincome= =1 It says option if not allowed r(198); Best regards, N ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Markus Eberhardt [markus.eberhardt@economics.ox.ac.uk] Sent: 21 June 2011 15:04 To: statalist@hsphsun2.harvard.edu Subject: Re: st: mean group 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: markus.eberhardt@economics.ox.ac.uk 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 <Nahla.Samargandi@brunel.ac.uk> 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: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Markus Eberhardt [markus.eberhardt@economics.ox.ac.uk] > Sent: 21 June 2011 14:20 > To: statalist@hsphsun2.harvard.edu > 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: markus.eberhardt@economics.ox.ac.uk > 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 <Nahla.Samargandi@brunel.ac.uk> 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 >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ >> > > * > * 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/ > * > * 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/ > * * 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/ * * 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/

**Follow-Ups**:**RE: st: mean group***From:*Nahla Samargandi <Nahla.Samargandi@brunel.ac.uk>

**References**:**st: mean group***From:*Nahla Samargandi <Nahla.Samargandi@brunel.ac.uk>

**Re: st: mean group***From:*Markus Eberhardt <markus.eberhardt@economics.ox.ac.uk>

**RE: st: mean group***From:*Nahla Samargandi <Nahla.Samargandi@brunel.ac.uk>

**Re: st: mean group***From:*Markus Eberhardt <markus.eberhardt@economics.ox.ac.uk>

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