tag:blogger.com,1999:blog-2198942534740642384.comments2015-11-24T16:56:45.879-08:00Econometrics Beat: Dave Giles' BlogDave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comBlogger3114125tag:blogger.com,1999:blog-2198942534740642384.post-12627888146998229602015-11-24T16:56:45.879-08:002015-11-24T16:56:45.879-08:00OK - thanks for explaining. I don;t know the answe...OK - thanks for explaining. I don;t know the answer - I suggest you go to the EViews users' forum and ask there.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-67626183176449496642015-11-24T15:45:00.076-08:002015-11-24T15:45:00.076-08:00THANK YOU PROF. FOR REPLY. BUT MY DATA ARE PANEL D...THANK YOU PROF. FOR REPLY. BUT MY DATA ARE PANEL DATA, SO THE OPTION FOR STABILITY DIAGNOSTIC IS NO THERE IN EVIEWS 9 WHEN RUNNING ARDL MODEL AS IN CASE OF RUNNING ARDL FOR TIME SERIES, PLEASE PROF. ADVICE ME WHAT SHOULD I TO PREFORM STABILITY TEST IN CASE OF PANEL DATAMUSTAFAnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-71483651159100215782015-11-24T13:06:49.575-08:002015-11-24T13:06:49.575-08:00The R-square is reported in the output. As with an...The R-square is reported in the output. As with any OLS regression, click on the "VIEW" tab and you can get RESIDUAL DIAGNOSTICS, and STABILITY DIAGNOSTICS, as usual.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-52464672237747046722015-11-24T12:18:15.561-08:002015-11-24T12:18:15.561-08:00Hi, dear Prof.
I have run ARDL model using eviews...Hi, dear Prof.<br />I have run ARDL model using eviews 9 and I have got the result. My question<br />Is how can I check for serial correlation and stability and R square? Thank youMustafanoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-15839597439871534102015-11-22T21:30:20.985-08:002015-11-22T21:30:20.985-08:00Anonymous: What you can say about the single inter...Anonymous: What you can say about the single interval is, barring other available information that would make such a statement absurd, that you believe the true value is in it. People run into the most trouble trying to wrap such statements in probabilities not understanding that after the interval is calculated there aren't any known ones for the interval (without additional work). But consider the confidence in the procedure. If you perform a procedure that is correct 95% of the time it's perfectly rational to then just act as if the procedure gave you the correct answer even if you have no idea the exact probability that you're correct this particular time. I always find it fascinating that people have no problem acting as if their decision following a typical test is correct even though they may be wrong at a much higher rate than for a CI but can't do the same with a CI. The difference is that you're not stating sig./non-sig. but instead saying that mu is here.Unknownhttp://www.blogger.com/profile/00227235335343168838noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-19279137974876191022015-11-20T09:26:01.810-08:002015-11-20T09:26:01.810-08:00This could be happening for a number of reasons.
...This could be happening for a number of reasons. <br />Keep in mind that unit root tests typically have pretty low power, so depending on the tests you're using, you may be getting a "false positive" that one or more of your series are I(1).<br />Structural breaks tend to lead unit root tests to "discover" unit roots that aren't there, so once again, it may be the case that not all of your series are really I(1).<br />If you are using seasonally unadjusted quarterly or monthly data, the unit roots that you are detecting at the zero frequency may only be part of the story. There may also be unit roots at the seasonal frequencies - these can be detected using the HEGY tests. This will mess up your cointegration testing.<br />In short, there could be lots of reasons why your unit root/cointegration tests may be giving false signals. There may not be cointegration at all.<br /><br />In addition, if you're using the Johansen methodology to test for cointegration, you need to be sure that the VAR model that is used as the basis for this testing is properly specified with respect to lag lengths, serial independence of the errors, and normality of the errors.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-88348822373362864732015-11-19T21:47:07.298-08:002015-11-19T21:47:07.298-08:00Dear Prof. Dave
I am facing a peculiar problem. Al...Dear Prof. Dave<br />I am facing a peculiar problem. All my tests for cointegration between non stationary time series are suggesting the presence of cointegration, but my error correction term is turning out to be either positive or insignificant or an absolute value of more than 1. How should I interpret this result?Ruchi Guptahttp://www.blogger.com/profile/10557169555440504758noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-51033714038073862092015-11-18T15:22:38.431-08:002015-11-18T15:22:38.431-08:00No, it's not in this case.No, it's not in this case.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-67667206033883159462015-11-18T15:07:32.177-08:002015-11-18T15:07:32.177-08:00Hi Dave,
If one of the AR root falls on the unit ...Hi Dave,<br /><br />If one of the AR root falls on the unit circle would you call the VAR is stable?<br />Thanks.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-26317638599018589332015-11-18T10:41:39.797-08:002015-11-18T10:41:39.797-08:00Thank You a lot Sir.
I have some clarifying questi...Thank You a lot Sir.<br />I have some clarifying questions with regard to your answers for #3.<br />4. Thus, if we reject the null, (that is, we conclude that LOG_GAS is stationary with a break in 2008), accounting for the break (with a dummy) is must. Is it correct?<br />5. Even if we don't reject the null, (that is we conclude LOG-CRUDE is non-stationary) since the programs gives a break date, is it still necessary to account for the break (assuming the break date different from the other variable)?<br />6. This is with regard to answer #2. Suppose i have 4 variables in my model. And i get 4 different break dates. According to your answer i should account for all the break dates. I did that. But my results became pretty bad. Plus, some break dummies are found to be insignificant. Can you suggest any better way to handle multiple breaks in a model? Is it reasonable to have ONE BREAK DUMMY FOR THE DEPENDENT VARIABLE? <br />7. If the break point generated by EViews 9 "unit root test with break point" is not correlated with any economic/financial/oil/war/ shock, do we still need to account for the break?<br /><br />Dear Sir, Kindly clarify the above doubts.<br /><br />Thank you a lot.<br />--------<br />Regards<br />Santosh Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-12318157850366847252015-11-17T14:23:26.101-08:002015-11-17T14:23:26.101-08:00Please define k and dmax.Please define k and dmax.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-60524285929259180182015-11-15T08:46:46.060-08:002015-11-15T08:46:46.060-08:00Santosh:
1. Yes, I would do that.
2. In that case...Santosh:<br /><br />1. Yes, I would do that.<br />2. In that case, two different dummy variables would be used.<br />3.That is correct.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-55656319501544219512015-11-15T01:45:21.452-08:002015-11-15T01:45:21.452-08:00Prof. Giles,
This question is wrt your blockbuste...Prof. Giles,<br /><br />This question is wrt your blockbuster post "ARDL Modelling in EViews 9". Even after accounting for breaks in the unit root test (URT), LOG_CRUDE series has unit root at the 5% significance level. And LOG_GAS does not have a unit root at the 5% significance level. In both cases, the break date is 1929. I have three questions wrt this.<br />1. If it was found that both LOG_CRUDE and LOG_GAS have unit root, will we still account for breaks in ARDL? That is, should we create the dummy, SHOCK?<br />2. If both the variables have separate break dates, then how to account for it<br />3. The null is that the LOG_CRUDE is non-stationary. Alternative is LOG_CRUDE is stationary with a break in the trend and intercept. Thus, if we fail to reject the null, what will be the conclusion? That LOG_CRUDE HAS A UNIT ROOT. Is it correct? <br />I request you to kindly clarify it.<br /><br />Santosh<br />Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-80519892354513888102015-11-14T06:53:44.984-08:002015-11-14T06:53:44.984-08:00Hi, sir if I have k+dmax=2 (where lag length =1 an...Hi, sir if I have k+dmax=2 (where lag length =1 and the variables are integrated at I(1)), can I still go ahead with the TY non-granger causality test?www.rabiuone.blogs.pot.comhttp://www.blogger.com/profile/04277933431309926053noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-12856317500295062862015-11-13T12:02:51.582-08:002015-11-13T12:02:51.582-08:00Thanks _ I realise there is a problem. EViews issu...Thanks _ I realise there is a problem. EViews issued a "patch" to the package so the old code won't run. I'll get to it as soon as I have a chance.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-64295201000831371332015-11-13T10:50:07.498-08:002015-11-13T10:50:07.498-08:00Dear Prof.
Thank you for your elaborate post. It ...Dear Prof. <br />Thank you for your elaborate post. It really helps us. I downloaded your linked Eviews Code but there is some error. It is not opening. Kindly fix it. Thank you.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-34795457804488813302015-11-11T14:33:53.516-08:002015-11-11T14:33:53.516-08:00Great collection of historic visualization example...Great collection of historic visualization examples .Nelson Cronehttp://www.blogger.com/profile/01694951341437734882noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-62386558639856578702015-11-11T07:20:40.482-08:002015-11-11T07:20:40.482-08:00why should be also negative? is significant not en...why should be also negative? is significant not enough?<br />Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-60888192425972492542015-11-02T01:31:33.990-08:002015-11-02T01:31:33.990-08:00Dear Professor Giles,
Can you explain to me - as ...Dear Professor Giles,<br /><br />Can you explain to me - as someone with only a modest grasp of econometrics - how to interpret unit root tests on variables that one would think have strict limits, for example ratios that can vary between 0 and 1, such as the ratio of government expenditure to total expenditure. Doesn't a unit root imply the variable has an infinite variance and so can end up anywhere? I have seen people apply these tests to such variables without any qualms. Are they correct to do so? <br /><br />Thank you. Nigelhttp://www.blogger.com/profile/13635711480098551913noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-45151366673434506022015-11-02T00:45:52.439-08:002015-11-02T00:45:52.439-08:00This comment has been removed by a blog administrator.Nigelhttp://www.blogger.com/profile/13635711480098551913noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-10656016027538036992015-11-01T15:30:38.277-08:002015-11-01T15:30:38.277-08:00This comment has been removed by the author.Abdulrahman Nadanihttp://www.blogger.com/profile/01985374447707407961noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-54518244092168728172015-10-30T13:54:33.751-07:002015-10-30T13:54:33.751-07:00I(0) variables can't be cointegrated, by defin...I(0) variables can't be cointegrated, by definition.Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-33032555674958275842015-10-30T13:52:36.930-07:002015-10-30T13:52:36.930-07:00Dear Dr. Giles,
I first want to express my sincer...Dear Dr. Giles,<br /><br />I first want to express my sincere thanks for your blog filled with extraordinary knowledge. As far as I understand your comments correctly we cannot use VECM Granger causality unless all variables are I(1) and co-integrated. However, I am wondering what are the reasons why we cannot apply VECM Granger causality to a mix of I(1) and I(0) co-integrated variables.Eyup Dogannoreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-627765947650675262015-10-28T08:49:33.168-07:002015-10-28T08:49:33.168-07:00As with any regression, there is no "cut off ...As with any regression, there is no "cut off number".Dave Gileshttp://www.blogger.com/profile/05389606956062019445noreply@blogger.comtag:blogger.com,1999:blog-2198942534740642384.post-17129211871332408572015-10-28T08:45:41.567-07:002015-10-28T08:45:41.567-07:00So what should be my cutoff number of regressors t...So what should be my cutoff number of regressors to use with a sample of 42 annual observations? Tchirwahttp://www.blogger.com/profile/12528247895410454878noreply@blogger.com