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From |
L P <pas2612@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: unit-root test |

Date |
Wed, 22 Aug 2012 16:29:58 +0200 |

Dear Muhammad, Many thanks for your suggestion. If I can take some more minutes of your time, I would like to share what follows: 1. as I said I am using STATA 9. For this reason when I typed the command . ssc install xtunitroot I got the message ssc install: "xtunitroot" not found at SSC, type -findit xtunitroot- (To find all packages at SSC that start with x, type -ssc describe x-) r(601); 2. as suggested in the error message I typed . findit xtunitroot and STATA opened a page with the link to four unit-root tests packages, which I installed all. Among them, I found the XTFISHER test (which is referred to be suitable for unbalanced data). I have tried to run the test and it looks like things are working in the right way now. For example, I run xtfisher Ln_MKTopn_2, lag(1) and the result is Fisher Test for panel unit root using an augmented Dickey-Fuller test (1 lags) Ho: unit root chi2(60) = 119.9346 Prob > chi2 = 0.0000 My questions: 1. what is the right interpretation of this result? I think I have to reject the null hyothesis because the p-value is < or = to 0.05. Hence, I can conclude that the variable is stationary and its use in the specification model is valid. Am I right? 2. what should be the right ammount of lags to be considered in the lag option? 3. does this test must be run for each single independent variable I consider in my model specification? 4. shall I run the test for the dependent variable as well? Thanks again for your really helpful support. 2012/8/22 Muhammad Anees <anees@aneconomist.com>: > Hello, > > You can find more information on theoritical part from the references > given in the helpfile. > > Moreoever, alternative sources of information is available from: > -xtunitroot- Check from Stata's command line if -help xtunitroot- > gives you these and if not then install it from -ssc install > xtunitroot- or find it using -xtunitroot-. > > The help file contains more information but there are some points > which can be used to answer your questions: > > 1. You can not use varlist, so it means you have to run the command > for varname. It means may be using it for one variable at a time or > for each variable seperately. > 2. You can not use -xtunitroot- for data with gaps or what we can say > some observations on some series are missing. The data should be > strongly balanced. > 3. Once confirmed, you can use the first difference to overcome the > issue of non-stationarity or this can be confirmed that the series are > stationary in first difference. > > I hope more discussion will help us learn more on these issues. Also I > hope this helps you somehow. > > -- > > Best > --------------------------- > Muhammad Anees > Assistant Professor/Programme Coordinator > COMSATS Institute of Information Technology > Attock 43600, Pakistan > http://www.aneconomist.com > http://elearning.aneconomist.com > > > > On Wed, Aug 22, 2012 at 6:13 PM, L P <pas2612@gmail.com> wrote: >> Hi there, >> >> I would be grateful if I could receive your help since I am new to >> econometrics and STATA. >> >> I am using STATA 9.0 an I am working on a panel data based on >> observations for 30 countries (id) and 25 years from 1981 to 2005 >> (time). The database is unbalanced since it contains gaps in id and >> time dimensions. The model specification looks like >> >> Ln Emissions[it] = a + b1 Ln GDP[it] + b2 LnGDP^2[it] + b3 Ln >> Trade(lag-1)[id] + ... + e >> >> According to what I read in statalist, I am trying to test the >> variables of my model specification for stationarity with >> Levin-Lin-Chu test and the use of the followwing STATA commands: >> >> . tsset id year >> >> . levinlin variable name, lag(1) >> >> My questions: >> >> 1. shall I run the test for each single dependent variable? What about >> the independent variable? >> 2. how can I overtake the problem of the gaps to allow the test for >> those variables characterised by gaps in the databse? >> >> Furthermore, if I find a p-value > or = 0.05, I have to accept the >> null hypothesis (that is the panels contain unit-roots). With the aim >> of overtaking this problem, is it enough to build first differences of >> the variable performing in this way? >> >> Thanks in advance. >> >> Lino >> * >> * 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: unit-root test***From:*Nick Cox <njcoxstata@gmail.com>

**References**:**st: unit-root test***From:*L P <pas2612@gmail.com>

**Re: st: unit-root test***From:*Muhammad Anees <anees@aneconomist.com>

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