19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 1/22

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Econometrics Beat: Dave Giles' Blog: Testing for Granger CausalityApr 29, 2011 ... In my earlier posting, I mentioned that I had followed the Toda and Yamamoto ( 1995) procedureto test for Granger causality. If you check out ...davegiles.blogspot.com

Questions About Granger Causality Testing ‐ The Fine PrintMay 27, 2014 ... The reasons for this, and for adopting a modified testing procedure, such as that proposed by Toda andYamamoto (1995), or that of Dolado ...davegiles.blogspot.com

VAR or VECM When Testing for Granger Causality?Oct 25, 2011 ... An easy way to deal with this is to use the following procedure proposed by Toda and Yamamoto (1995) ‐more details are provided in my ...davegiles.blogspot.com

ARDL Models ‐ Part II ‐ Bounds TestsJun 19, 2013 ... In that case, the problem is resolved by using the Toda‐Yamamoto (1995) procedure, to ensure that the Waldtest statistic is asymptotically ...davegiles.blogspot.com

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ARDL Modelling in EViews 9

My previous posts relating to ARDL models (here and here) have drawn a lot of hits. So, it's great to see that EViews9  (now in Beta release ‐ see the details here) incorporates an ARDL modelling option, together with the associated"bounds testing".

This is a great feature, and I just know that it's going to be a "winner" for EViews.

It certainly deserves a post, so here goes!

First, it's important to note that although there was previously an EViews "add‐in" for ARDL models (see here and here),this was quite limited in its capabilities. What's now available is a full‐blown ARDL estimation option, together with boundstesting and an analysis of the long‐run relationship between the variables being modelled.

Here, I'll take you through another example of ARDL modelling ‐ this one involves the relationship between the retail priceof gasoline, and the price of crude oil. More specifically, the crude oil price is for Canadian Par at Edmonton; and thegasoline price is that for the Canadian city of Vancouver. Although crude oil prices are recorded daily, the gasoline pricesare available only weekly. So, the price data that we'll use are weekly (end‐of‐week), for the 4 January 2000 to 16 July2013, inclusive.

The oil prices are measured in Candian dollars per cubic meter. The gasoline prices are in Canadian cents per litre, andthey exclude taxes. Here's a plot of the raw data:

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 2/22

The data are available on the data page for this blog. The EViews workfile is on the code page.

I'm going to work with the logarithms of the data: LOG_CRUDE and LOG_GAS. There's still a clear structural break in thedata for both of these series. Specifically there's a structural break that occurs over the weeks ended 8 July 2008 to 30December 2008 inclusive. I've constructed a dummy variable, BREAK, that takes the value one for these observations, andzero everywhere else.

The break doesn't occur at just a single point in time. Instead, there's a change in the level and trend of the data thatevolves over several periods. We call this an "innovational outlier", and in testing the two time series for unit roots, I'vetaken this into account.

In a recent post I discussed the new "Breakpoint Unit Root Test" options that are available in EViews 9. They're perfectlysuited for our current situation. Here's how I've implemented the appropriate test of a unit root in the case of theLOG_CRUDE series:

The result is:

We wouldn't reject the hypothesis of a unit root at the 5% significance level, and the result is marginal at the 10% level.

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 3/22

The corresponding result for the LOG_GAS series is:

In this case we'd reject the null hypothesis of a unit root at the 5% significance level, but not at the 1% level. Overall, theresults are somewhat inconclusive, and this is precisely the situation that ARDL modelling and bounds testing is designedfor. Applying the unit root tests to the first‐differences of each series leads to a very clear rejection of the hypothesis thatthe data are I(2), which is important for the legitimate application of the bounds test below.

Now, let's go ahead with the specification and estimation of a basic ARDL model that explains the retail price of gasolinein terms of past values of that price, as well as the current and past values of the price of crude oil. We can do this in thesame way that we'd estimate any equation in EViews, but we select the "Estimation Method" to be "ARDL" (see below):

Notice that I've set the maximum number of lags for both the dependent variable and the principal regressor to be 8. Thismeans that 72 different model specifications will be considered, allowing for the fact that the current  value ofLOG_CRUDE can be considered as a regressor. Also, notice that I've included the BREAK dummy variable, as well as anintercept and linear trend as (fixed) regressors. (That is, they won't be lagged.)

Using the OPTIONS tab, let's select the Schwarz criterion (SC) as the basis for determining the lag orders for the regressors:

The model which minimizes SC will be chosen. This results in a rather parsimonious model specification, as you can see:

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 4/22

I mentioned in an earlier post on Information Criteria that SC tends to select a simpler model specification than someother information criteria. So, instead of SC, I'm going to use Akaike's Information Criterion (AIC) for selecting the lagstructure in the ARDL model. There's a risk of "over‐fitting" the model, but I definitely don't want to under‐fit it. Here'swhat we get:

It's important that the errors of this model are serially independent ‐ if not, the parameter estimates won't be consistent(because of the lagged values of the dependent variable that appear as regressors in the model. To that end, we can usethe VIEW tab to choose, RESIDUAL DIAGNOSTICS; CORRELOGRAM ‐ Q‐STATISTICS, and this gives us the following results:

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 5/22

The p‐values are only approximate, but they strongly suggest that there is no evidence of autocorrelation in the model'sresiduals. This is good news!

Now, recall that, in total, 72 ARDL model specifications were considered. Although an ARDL(4,2) was finally selected, wecan also see how well some other specifications performed in terms of minimizing AIC. Selecting the VIEW tab in theregression output, and then choosing MODEL SELECTION SUMMARY; CRITERIA GRAPH from the drop‐down, we see the "TopTwenty" results:

(You can get the full summary of the AIC, SC, Hannan‐Quinn, and adjusted R2 statistics for all 72 model specifications ifyou select CRITERIA TABLE, rather than CRITERIA GRAPH.)

One of the main purposes of estimating an ARDL model is to use it as the basis for applying the "Bounds Test". This test isdiscussed in detail in one of my earlier posts. The null hypothesis is that there is no long‐run relationship between thevariables ‐ in this case, LOG_CRUDE and LOG_GAS.

In the estimation results, if we select the VIEW tab, and then from the drop‐down menu choose COEFFICIENTDIAGNOSTICS; BOUNDS TEST, this is what we'll get:

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 6/22

We see that the F‐statistic for the Bounds Test is 32.38, and this clearly exceeds even the 1% critical value for the upperbound. Accordingly, we strongly reject the hypothesis of "No Long‐Run Relationship".

The output at this point also shows the modified ARDL model that was used to obtain this result. The form that this modeltakes will be familiar if you've read my earlier post on bounds testing.

In the estimation results for our chosen ARDL model, if we select the VIEW tab, and then from the drop‐down menu chooseCOEFFICIENT DIAGNOSTICS; COINTEGRATION AND LONG RUN FORM, this is what we'll see:

The error‐correction coefficient is negative (‐0.2028), as required, and is very significant. Importantly, the long‐runcoefficients from the cointegrating equation are reported, with their standard errors, t‐statistics, and p‐values:

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 7/22

Posted by Dave Giles at 12:40 PM

Labels: ARDL Models, Cointegration, Information theory, Structural breaks, Time series, unit roots

So, what do we conclude from all of this? 

First, not surprisingly, there's a long‐run equilibrium relationship between the price of crude oil, and the retail price ofgasoline. 

Second, there is a relatively quick adjustment in the price of gasoline when the price of crude oil changes. (Recall thatthe data are observed  weekly.) 

Third, a 10% change in the price of crude oil will result in a long‐run change of 7% in the price of retail gasoline. 

Whether or not these responses are symmetric with respect to price increases and price decreases is the subject of someon‐going work of mine.

© 2015, David E. Giles

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133 comments:

Anonymous January 9, 2015 at 2:41 PM

As usual fantastic! The more detailed instructions, the better for this amateur. I enjoy trying to duplicate your steps.Sometimes the code is too complicated however. Thank you. It is very enjoyable to see economic issues of the dayanalyzed, along with explanations that help one to learn how to replicate the processes. Right now the price of Brentrelated to world excess supply or deficit supply compared to world demand seems confusing. There seems to be norelationship. Any chance of a post on the relationship of Brent price to the excess or deficit supply When I figure‐out howto select a profile other than anonymous.

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JAWAD KAZMI January 13, 2015 at 12:51 AM

Sir, Can we apply ARDL bound testing to analyze two co‐integration relations between the same variables (x and y). e.g. Xc Y and Y c X.

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Dave Giles January 13, 2015 at 9:32 AM

If X is cointegrated with Y, then Y MUST be cointegrated with X.

Anonymous January 18, 2015 at 9:11 PM

Thank you very much for this wonderful blog Prof. Giles! I have questions concerning ARDL(p,q) bounds‐testing. Assume I have X‐variable(s) which cannot have a unit‐root; for instance a dummy‐variable for certain events (likemacroeconomic shocks) and its lagged values. Can I include this (these) variable(s) in the "ARDL bounds‐testing approach"?Such a dummy‐variable, name it SHOCK, would be rather similar to your “BREAK” variable, I guess. The coefficient onD_SHOCK would then pinpoint the short‐run effect of the shock and the coefficient on SHOCK would represent the long‐run impact of the macroeconomic shock (although SHOCK is I(0) and cannot be cointegrated with Y)? The bounds‐test forcointegration would be an F‐test on joint significance of the lagged Y and lagged X variables (not including SHOCK)?

Thank you very much again!

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Dave Giles January 19, 2015 at 8:25 AM

That's correct.

Anonymous September 15, 2015 at 11:13 PM

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 8/22

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Dear Prof. Dave, I have a model with one dummy variable (crisis). This dummy is set from 1997‐1999 for crisis (1)and other years (0) for non‐crisis. Then, when I run breakpoint unit root test in level, I got different breakdate for different variables. But when I run it in 1st difference, I got the same break date (1997) for differentvariables, all variables stationary in 1st difference. So, can I still put this dummy variable using 1997‐1999 inthe model? or only 1997 ? The problem is, if I put only 1997 as crisis year, the dummy has insignificantcoefficient. Thank you

Dave Giles September 16, 2015 at 7:58 AM

If you have the dummy set to for just one period, that's equivalent to just omitting that observation from themodel (see my "Dummies for Dummies" post). I haven't seen your model or data, but I would suggest you leavethe dummy set for 1997‐1999.

Anonymous February 17, 2015 at 12:39 PM

Another excellent post! Thanks for all the information.

Question ‐ when I downloaded and plotted the data for gas and oil in a scatter, they appeared to have a linearrelationship. In some work I'm doing, the variables seem to have an exponential relationship. Something like y = x1 + x1^2+ x2 seems to fit the data much better than y = x1 + x2. Would an ALDR still work in this case? Would I want to includelags of of the x1^2? Would it enter the model a "Fixed Regressor" like "BREAK" in your example?

Unfortunately, I am stuck with Eviews 8 for now. The lag selection tools are making me green with envy.

Thanks sir!

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Dave Giles February 17, 2015 at 12:44 PM

Yes, that's correct on all counts. If you have a legitimate version of EViews 8.1 on your machine, you candownload the Beta version of EViews 9 for free from here: http://register1.eviews.com/beta/

Oyeleye Olalekan February 19, 2015 at 1:07 AM

please sir, can you give an example on how to go through the nonlinear ARDL model

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resbaby July 13, 2015 at 4:07 AM

that was also my question

Anonymous March 12, 2015 at 11:56 AM

plz sir clear my confusion about F test... can we use Pesaran et al. table for small sample size or will go for Naryan table?plz answer me as soon as possible thnx

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Dave Giles March 12, 2015 at 1:12 PM

Naryan table.

ham you August 17, 2015 at 4:05 AM

Critical values for ARDL bounds Tests (Narayan, 2004): "Reformulating Critical Values for the Bounds Fstatistics Approach to Cointegration: An Application to theTourism Demand Model for Fiji". http://www.researchgate.net/publication/268048533_Reformulating_Critical_Values_for_the_Bounds_F‐_statistics_Approach_to_Cointegration_An_Application_to_the_Tourism_Demand_Model_for_Fiji

Anonymous April 16, 2015 at 8:11 AM

Dear Dave

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 9/22

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Thank you ofr all these explanations. Howver, I would to ask you please how we can do short and long run multipliersgraphics with Eviews.

Sincerely

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Hiển Bùi Quang April 18, 2015 at 8:05 PM

Can I get eview 9 demo since Apr.19? I have submitted form but I didn't find any email reply.Did you know how to get it?Thank you very much!

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Dave Giles April 18, 2015 at 8:21 PM

You'll have to contact EViews ‐ I don't work for them!

Hiển Bùi Quang May 7, 2015 at 9:16 AM

Dear Prof.,Regarding to "Breakpoint Unit Root Test" compare with "Unit Root Test", is there any benefit or improvement?Thank you!

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Dave Giles May 7, 2015 at 10:25 AM

If you have structural breaks you should not use the usual unit root tests (e.g., ADF) without modification.

Muhammed Şehid GÖRÜŞ May 7, 2015 at 11:06 AM

Hello Sir.I run ARDL bound test method and find cointegration bw variables. Than I employ short‐run and long‐runanalysis. In the short‐run, I found min. in akaike in X(0to‐1) =‐4,54 rather than X(0to‐5) =‐4,53. But, there is a normality(JB)problem in the first one. May I choose 0to‐5 or ignore the normality problem in the first one. Moreover, I haveheteroskedasticity problem in my estimations both bound test, short‐run and ECM granger causality tests. Is it a signiicantproblem for time series. Thx for interest and help.

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Dave Giles May 7, 2015 at 11:14 AM

I would use 0 to ‐5, and I wouldn't be too worried about teh heteroskedasticity issue.

Muhammed Şehid GÖRÜŞ May 7, 2015 at 11:19 AM

appreciation prof.

gazman May 23, 2015 at 12:14 PM

Thanks for this post, it's really illuminating. However, I would like to know how we can do a causality test in the ARDLframework. Specifically, if Bounds test shows that X and Y are cointegrated, then (we recall from your earlier post thatwhen variables are cointegrated, there would be at least a unidirectional causality between them) how can we do theGranger causality test in Eviews 9?

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Dave Giles May 23, 2015 at 2:52 PM

By estimating a VAR model ‐ not an ARDL model. I have several posts about this.

ΠΑΛΑΙΟΣ ΠΑΝΑΓΙΩΤΗΣ May 24, 2015 at 6:11 PM

I have a model which is not linear...y=c(1)+c(2)*(x^2)+c(3)*(z^2). Can I apply the ARDL method for cointegration in thismodel ? If yes, how can I transfrom this model in a ARDL model ?

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 10/22

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Dave Giles May 25, 2015 at 12:23 PM

Your model is, in fact, linear ‐ linear in the parameters, and that's all that matters. Just re‐label X1=X^2, andX2=Z^2, and then proceed in the usual way.

ΠΑΛΑΙΟΣ ΠΑΝΑΓΙΩΤΗΣ May 25, 2015 at 1:02 PM

Thank you very much.

ΠΑΛΑΙΟΣ ΠΑΝΑΓΙΩΤΗΣ May 25, 2015 at 1:08 PM

One more question...What about this model? y=c(1)+c(2)*x*w+c(3)*(z^2) ? Do I re‐label x*w as, lets say q, andproceed in the usual way?

Dave Giles May 25, 2015 at 2:23 PM

Yes, that's right.

mar sk May 26, 2015 at 8:43 AM

Can I cointegrate a Cobb Douglas function with an ARDL(or with any other method for cointegration), without using itslogarithmic form?

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Dave Giles May 26, 2015 at 9:43 AM

No, certainly not exactly. If |x| < 1 you could use the Taylor series approximation for log(1+x), namely, log(1+x)= x ‐ (x^2)/2 + .......... and go from there.

mar sk May 26, 2015 at 8:44 AM

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Anonymous May 28, 2015 at 11:39 AM

Dear Sir,

My data seems to have several structural breaks...do I need to correct for those using Bai‐Perron...can this be done ineviews 9

Reply

Dave Giles May 28, 2015 at 1:45 PM

EViews 9 includes the Bai‐Perron test.

Anonymous May 28, 2015 at 9:45 PM

Dear Sir

Thanks for the reply regarding Bai‐Perron test...however I could not find it in eviews9..

1. if you could pls tell the location.

2. I am dealing with interest rate date, on quarterly basis since 1996q1, which is showing immense oscillations over theentire period and is following no set pattern...should this be taken as structural breaks or can be adjusted by only takingtime.

3. When I attempted doing without any dummy variables in microfit, it does not pass the CUSUMQ test and suggests toincorporate a dummy variable for cr.

4. For optimal no. of lags in ardl, can we get them from eviews9 via the automatic lag selection criteria and then carrythe work in microfit. Similarly suggest the same for the structural break.

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 11/22

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Dave Giles May 28, 2015 at 10:19 PM

In EViews, the HELP tab will give you the information you need to locate and use Bai‐Perron.

Anonymous May 29, 2015 at 4:22 PM

Keep up the good work Dave! I just ran the ARDL model using monthly data and obtained results, BUT, my model exhibitsserial correlation past the 11th lag. The Q‐stats from lag 0‐11 are not serially correlated but past that, (12 to lag 36) areserially correlated. I have (1) included dummies (2) ran the top 8 models as selected by AIC (3) even tried using logs..

Any thoughts on this? I truly appreciate your help.

Reply

Dave Giles July 2, 2015 at 2:05 PM

Please see my reply to "Anonymous" immediately below. Given what you've tried already, I'd suspect omittedregressors.

Anonymous May 31, 2015 at 12:32 PM

Thanks for the post Dave. I'm running the same type of model (ARDL) using monthly data but I cannot seem to get rid ofserial correlation appearing after the 11th lag in the Q‐stats despite trying different specifications.

Any thoughts?

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Dave Giles May 31, 2015 at 12:48 PM

It could be the functional form ‐ logs or levels? The other thing that comes to mind is a mis‐specificationthrough the omission of one or more regressors. Are the data seasonally adjusted, or have you includedseasonal dummy variables? If the latter, explore if they should be simply additive, or if they should interactwith one or more of the regressors. Bottom line ‐ remaining autocorrelation is probably a result of model mis‐specification.

Anonymous May 31, 2015 at 1:20 PM

Thanks! I'm looking at the relationship between unemployment and oil prices using both logs and levels. I have also usedthese dummies as regressors: @EXPAND(@MONTH, @DROPFIRST) Still getting Serial correlation after the 11th lag. What do you think?This is fun but it can get old :)

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Dave Giles May 31, 2015 at 4:01 PM

It sounds to me as if you are missing some relevant regressors.

Anonymous June 2, 2015 at 11:57 AM

Thanks Dave.

Anonymous June 10, 2015 at 10:36 PM

Dear Prof,In ARDL model Is there a way to get impulse response functions from error correction model (not from VECM) with eviews

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 12/22

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9 or manually by excel?

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Dave Giles June 11, 2015 at 9:08 AM

Not that I'm aware of, but why not ask on the EViews User Forum at http://forums.eviews.com/ .

Anonymous June 13, 2015 at 8:28 AM

I am so glad to see your power posts. My questions are that after running ARDL cointegration test for a multivariate timeseries, which method should i use for causality test? is it possible to use ecm‐ARDL results to determine causalitybetween variables?

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Dave Giles June 14, 2015 at 9:35 AM

My preference would be to use a VAR model and the MWALD (Toda‐Yamamoto test). I have sevseral posts aboutthis that may help.

Najid Iqbal June 16, 2015 at 10:54 AM

Dear Prof, How to check stability diagnostics in ARDL eviews9? I am talking about CUSUM and CUSUM SQUARE

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Dave Giles June 16, 2015 at 11:17 AM

One suggestion: save the residuals from the ARDL. Then regress these residuals just on a constant using OLSand go from there.

Yasmine Rashed July 4, 2015 at 3:02 AM

Try this, from the estimated model window, choose View‐‐>stability diagnostic‐‐> recursive estimation

Anonymous September 8, 2015 at 6:22 AM

Dear Prof. Dave,Does the stability test (Cusum&Cusum sqr) really matter in the ARDL? What if I don't include it in my analysis,just like what you have explained in this blog? Thank you.

Dave Giles September 8, 2015 at 11:29 AM

These tests have nothing to do with ARDL modelling and Bounds Testing, per se. With any estimated model youmay be concerned about the model's stability ‐ hence the use of such tests.

Anonymous December 19, 2015 at 7:13 PM

Dear Prof. Dave, i tried the trick (One suggestion: save the residuals from the ARDL. Then regress theseresiduals just on a constant using OLS and go from there.). When i regressed resid on c, i find c is insignificantand R_sqr is zero. What to do?

Anonymous June 18, 2015 at 9:50 AM

Dear Prof,I have used two softwares Eviews9 and Microfit4.1 for doing bounds test for my trivariate model but in some cases theresults were not the same. Which one is reliable? for my sample (1960‐2012 yearly) how many lags should i define as maxlags number?

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Dave Giles June 18, 2015 at 10:41 AM

You should address the first question to the suppliers of those packages. With your annual sample, I'd try,maybe, 12 years as a maximum and use SIC to determine the preferred lag length. The latter will undoubtedlybe much smaller than 12.

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 13/22

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Anonymous June 18, 2015 at 9:52 AM

for ARDL cointegration test and having a sample of less than 50 observations (yearly data), which kind ofHeteroskedastisity i should use and how many lags i should determine for doing that test?

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Dave Giles June 18, 2015 at 10:43 AM

I doubt if het. is an issue with your time‐series data, but you could White's test as it applies to a very generalclass of types of het. Use SIC to determine the lag length.

Muhammad Ahad June 18, 2015 at 5:48 PM

Sir, you are doing great work. Can you tell me how i can run ARDL approach by using E‐views 7.? because throughestimation it does not provide ARDL method in Method section. so how i can apply ARDL in E‐views 7.thank you. i really appreciate your efforts.

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Dave Giles June 18, 2015 at 6:23 PM

See this post: http://davegiles.blogspot.ca/2013/06/ardl‐models‐part‐ii‐bounds‐tests.html

All you need is OLS. There is also an EViews "add‐in" for ARDL modeling that will run in EViews 7. See this post:http://davegiles.blogspot.ca/2014/01/an‐ardl‐add‐in‐for‐eviews.html

Anonymous June 23, 2015 at 1:17 AM

Dear ProfesorAfter running ARDL bounds tests, Ramsey rest test null hypothesis is not rejected. firstly i do not know how determinenumber of fitted values for this test secondly by not rejection of this test what should i do?

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Dave Giles June 26, 2015 at 10:51 AM

The number of fitted values is somewhat ad hoc. You can't use just one ‐ usually people use 2, 3, or 4.The Ramsey test is testing if the coefficients of these extra variables are zero, You want them to be. That is,you do not want to reject the null hypothesis. A rejection is signalling mis‐specification of the model, either interms of functional form, or perhaps omitted regressors. Also, please see http://davegiles.blogspot.ca/2015/06/readers‐forum‐page.html

Pascal Kamana June 26, 2015 at 9:29 AM

Dear Sir,

I was wondering if you could have an idea of how to find lag lengths using Gretl package.

Thanks!

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Dave Giles June 26, 2015 at 9:30 AM

Lag lengths for what, exactly?

Also, please see http://davegiles.blogspot.ca/2015/06/readers‐forum‐page.html

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Pascal Kamana June 29, 2015 at 12:51 AM

Dear Prof,

I was asking how to determine optimal p&q while using Gretl package and if possible how to do bounds test.

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 14/22

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Thanks for your insights!

Dave Giles June 29, 2015 at 9:35 AM

Pascal ‐ try combinations of p and q and minimize SIC. To do the bounds test, all you need is access to OLS ‐see my earlier post on this in this blog.

Also, please see http://davegiles.blogspot.ca/2015/06/readers‐forum‐page.html

Sidra June 27, 2015 at 4:20 AM

Sir your example uses two variables. I wanted to ask that can we replicate the same example using multiple variables.Plus how can we find the causality taking the variables in pairs. . Also please letme know is it necessary to take the valuein log for the model? Thanks

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Dave Giles June 27, 2015 at 9:14 AM

Sidra ‐ yes, you can do the same thing with three or more variables. The causality testing should be doneseparately in the context of a VAR model. You don't have to take logarithms of the data.

Sidra July 1, 2015 at 5:43 AM

Sir can ARDL model be used of all the variables are I(1) and none is I(0) or I(2) ?

Dave Giles July 1, 2015 at 8:30 AM

Yes.

Sidra July 5, 2015 at 1:39 AM

I have replicated the above example with multiple variables. It is found to have a long run relationship ,butone of my long run coefficients is showing the value 0 (although t statistic is significant) what does this meanand how to interpret it .The equation is Cointeq = LOG(REAL_PER_CAPITA_INCOME) ‐ (0.0008 *ELEC_PER_CAPITA + 0.0000*TOTAL_LABOUR_FORCE + 1.1345 *GFCF__OF_GDP + 9.6866 ) The dependent variable is taken in log and the others in level.Many thanks

Dave Giles July 6, 2015 at 11:50 AM

Looks to me like a scale issue. The value is zero to 4 decimal places, but it's not really zero. Try re‐runningeverything after dividing your TOTAL_LABOUR_FORCE series by (say) 10,000. All this will do is scale (multiply)the estimated coefficient by 10,000. The you'll probably see an effect. No interpretations or other will beaffected by doing this, and the t‐statistic will be identical to what it is now.

Anonymous June 29, 2015 at 5:47 AM

hello , i have dependant var I(0) , 6 independant var are I(1) , 1 independant var is I(0) and one I(2) ,, im confusedbetween VAR and ARDL model , which one is the appropriate?

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Dave Giles June 29, 2015 at 9:36 AM

VAR, using Toda‐Yamamoto method ‐ see my earlier posts. As I state in this post, you can't use ARDL if you haveI(2) data.Also, see http://davegiles.blogspot.ca/2015/06/readers‐forum‐page.html

Anonymous June 29, 2015 at 12:23 PM

Dear ProfessorAccording to one paper i found Long‐run parameters and standard errors estimaed by ARDL method are biased specially insmall sample data. That paper suggested using bias‐corrected bootstrap method instead of delta method. Now myquestion is that how is it possible to do this in eviews 9.0?

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 15/22

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Dave Giles June 29, 2015 at 12:53 PM

Yes ‐ but you'd have to write an EViews program to do it.

Anonymous July 5, 2015 at 8:52 PM

Are the bounds F‐ and t‐tests for level relationships still valid in a conditional unrestricted ECM with a linear *and*quadratic trend? And in a more general ARDL?

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Dave Giles July 6, 2015 at 10:33 AM

The tables of critical values given by Pesaran et al. allow for various intercept‐linear trend combinations, butthey won;t be valid of you have a quadratic trend in the model. If by a "more general ARDL" model you meanone with more than two variables, then yes. The parameter, k, in the Pesaran et al. tables is for the numberof "x" variables in the model.

Anonymous July 10, 2015 at 9:38 PM

Dear Mr. Dave Giles

I have a question. How do I make the Granger causality test? because I have seen it in the papers mentioned alwaysperformed test. Another question. Is it necessary to analyze the causality in the short and long term?

Thank you very much for your answer

Regards

Andres

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Dave Giles July 19, 2015 at 12:40 PM

Andres ‐ see these posts:

http://davegiles.blogspot.ca/2011/04/testing‐for‐granger‐causality.htmlhttp://davegiles.blogspot.ca/2011/10/var‐or‐vecm‐when‐testing‐for‐granger.htmlhttp://davegiles.blogspot.ca/2012/04/surplus‐lag‐granger‐causality‐testing.html

Anonymous July 15, 2015 at 1:34 AM

In the case of the model used ARDLWhen the joint integration testing there I find no long‐term relationshipDo not I continue to pause, or search for causal between variables

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Dave Giles July 19, 2015 at 12:31 PM

I'd do some causality testing. Here's why.If there HAD BEEN cointegration, then there HAS to be Granger causality one way or the other. If there NOCOINTEGRATION, then there may or may not be G‐causality. It's worth testing for it.

Anonymous July 22, 2015 at 8:27 PM

HELLO,Thanks for the great post. However i have a question, is it okay to include a dummy variable to capture a break the datafor a long period of time say (20002Q1‐2010Q4,if you have justification of an event that is likely to cause such break in theseries) 2) when using a VAR (from your ARDL 2 POST) to obtain the lag of the dependent variable, are we to specify thedummy variable as an exogenous variable(in difference and in lagged level) as well? 3) what if i find no cointegration arethere any conventional model to test the short run effect as Granger causality test only tells the direction of causality?lastly,(not related to this post) please do you have a post on stochatic simulation method of forecasting or any forecastingrelated post?i l really look forward to your reply. Thanks very many.

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 16/22

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Dave Giles July 23, 2015 at 1:31 PM

That would be fine if you're really sure that there is just the one break. Keep in mind that the dummyvariable is simply shifting the intercept in the model, so this give you the answer to your second question ‐ youwould treat the dummy variable in exactly the same way that treat the intercept. So, you would not bedifferencing/lagging it. If there is no cointegration, then a simple ARDL model (not the sort used for boundstesting) would provide a useful basis for examining short‐run effects. For instance, seehttp://davegiles.blogspot.ca/2013/03/ardl‐models‐part‐i.html . Finally, I don't have any posts on stochasticsimulation ‐ why not leave me a request on the "Readers' Forum" page and I'll see what I can do. If you use the"Search" on the blog page (right sidebar) you'll find a handful of posts on forecasting.

Anonymous July 23, 2015 at 3:09 AM

hi dave,asthis is the most recent post you get to reply, i have question concerning T‐Y granger causality test in your previouspost. Does the AR graph really matter? because when i estimated a VAR(4) model selected by the information criteria,there was no problem of Auto correlation but however the on AR graph,few of the points where outside the circle. wheni estimated a var(3) all the points where inside but there was a problem on auto correlation...please what do you think iswrong? thanks...~valerie

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Dave Giles July 23, 2015 at 8:20 AM

There are 2 quite different things going on here, One is testing for autocorrelation in the residuals of themodel. The other is checking to see if the estimated coefficients of the VAR model imply a dynamically stableautoregressive structure. Unless the inverse roots of the characteristic equation associated with VAR lagstructure are all inside the unit circle, the model is dynamically unstable ‐ a shock to the model will just growand grow. You wouldn't want to use a model with that feature.

Anonymous July 23, 2015 at 8:41 AM

thank you.two final questions please. are there any scenario where the specified lag length chosen by the informationcriteria, does not still remove the problem of autocorrelation?if there is, are we allowed to increase the lag lengthourselves? secondly, if the lag length chosen is e.g 7 and which solves the AC problem in the residuals + the ARcondition,then estimating the var(7) in which case we include one extra lag (p+m, variables are all I(1)) when specifyingthe exogenous do we still have to check the AC and AR graph of the new specified model? just wondering. thanks ~Valerie

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Dave Giles July 23, 2015 at 1:23 PM

Valerie: Yes, this often happens, perhaps not surprisingly because the IC are looking at the "fit" of the model(with a penalty for complexity), whereas autocorrelation may be arising because of incorrect functional form,etc. If this occurs, you often need to increase the max. lag length that's suggested by the IC. That's OK. Themain thing is to be happy with the specification of the "base" model. It sounds as if you are referring to the TYprocedure where you then add lags of the variables (but don't include these extra lags in the null hypothesis)when testing for Granger non‐causality. Adding them is just a "trick" to ensure that the test statistic you'reusing has the usual asymptotic distribution. That being so, you don;t have to be so concerned about the ACetc. in the "final" model on which the testing is based.

Seyi August 25, 2015 at 6:38 AM

Dear Professor,

Is it not necessary to check that the underlying variables are not I(2) when structural breaks are present?

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Dave Giles August 25, 2015 at 7:26 AM

The ARDL bounds testing requires that no variables be I(2), whether or not there are breaks.

ahmed Nusair August 26, 2015 at 12:03 PM

Dear Prof.

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 17/22

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If I have, for example, five variables. The null hypothesis of no‐cointegration would be H0: α1=α2=α3=α4=α5=0. What is thecorrect form for the alternative hypothesis of cointegration? Is it 1) (α1≠α2≠α3≠α4≠α5≠0), or 2) At least one the α's is not zero, or3) α1≠0, α2≠0, α3≠0, α4≠0, α5≠0, or4) Some other form

Could you also please explain.

Thanks

Sal

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Dave Giles August 26, 2015 at 12:16 PM

Sal ‐ option (2), for reasons given in the original paper.

Anonymous September 1, 2015 at 8:52 AM

Dear professor before I estimate the ardl should I have to perform the causality test? if the answer is yes, then howshould I proceed if I have some variables that are I(1) and some I(0), because I know can estimate the ardl with differentintegrated series, but I cannot perform the causality test. Thanks

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Dave Giles September 1, 2015 at 10:11 AM

No, you don't.

Anonymous September 2, 2015 at 8:52 AM

Good DayWith respect to the direction of influence, I am not certain how this should be interpreted. Apart from referring totheory, how should the signs be interpreted out of Eviews9.

My confusion stems from the fact that in Johanson Test result in eviews8 the signs in the cointegration equation wereswapped i.e. if they were ‐ve they were to be interpreted as +ve.

My Eviews9 ARDL results are below

Cointeq = GVT_BONDS – (‐0.2733*GDP__ + 0.9637*CPI__ ‐1.7030*CA_GDP__ + 0.3897*BD_GDP__ ‐0.1901*LEADING_INDICATOR‐0.0006*NET_BORROWING + 0.0001*NET_PURCHASES + 20.9160 )

Variable Coefficient Prob.GDP__ ‐0.273306 0.2663CPI__ 0.963655 0.0049CA_GDP__ ‐1.702984 0.0042BD_GDP__ 0.389691 0.2213LEADING_INDICATOR ‐0.190125 0.0001NET_BORROWING ‐0.000605 0.0027NET_PURCHASES 0.000053 0.8282C 20.915959 0.0000

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Dave Giles September 2, 2015 at 9:04 AM

I suggest you address this to the EViews forum.

Anonymous September 13, 2015 at 9:45 PM

Dear Prof.

Looking at your example of bivariate equation with the same break period, now, If one has a multivariate equation (e.g.having five variables), and each variable has a different break date. Can we include all the break point in our estimation?

Reply

19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 18/22

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Dave Giles September 13, 2015 at 10:18 PM

Yes, you can.

Ibrahim M. A. September 18, 2015 at 2:17 AM

Thank you Prof. Another question on multivariate equation with different break period. I use test for structuralbreak purposely to further confirm that non of the variable is I(2), after that i did not include dummy for thebreak period in the regression instead i use CUSUM and CUSUMSQ test to test the overall stability of theparameters, and there are stable within the 5% significance level. Does this procedure appropriate?

Dave Giles September 18, 2015 at 9:54 AM

That seems reasonable.

Ibrahim Mohammed Adamu September 18, 2015 at 11:57 PM

Thank you Prof.

عدولة دال September 14, 2015 at 9:35 AM

Thank you very much, Professor, I have a question: I want to measure the impact of the development of the bankingsector on economic growth using ARDL model , and I have six variables, you follow the same steps?

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Dave Giles September 14, 2015 at 9:45 AM

Yes, you do.

عدولة دال September 17, 2015 at 11:12 AM

Dear Prof. How is insert BREAK a the program EViews 9

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Dave Giles September 17, 2015 at 11:59 AM

Create a dummy variable.

عدولة دال September 19, 2015 at 3:33 AM

Dear Prof. How should I "Breakpoint Unit Root Test" for six variables?, How is the expression within the form?, Did you seethat 35 of the observations adequate ?, variables are:  Real gross domestic product per capita variable dependentMatrix variable banking developmentConsumer prices inflationGovernment spending ratio GDPRatio of capital accumulation to GDPTrade openness variableWaiting for your answer, thank you Professor

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Dave Giles September 19, 2015 at 9:37 AM

I don't wish to sound rude, but I just don't have time for this. Sorry!

Anonymous October 9, 2015 at 3:46 AM

Dear Sir, Thank you for your helpful post!How can i get Eviews 9 demo? I’m a student and i have no organization, so i can’t fill the required fields…How can i solve this problem?

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 19/22

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Dave Giles October 9, 2015 at 8:27 AM

You will need to contact EViews directly ‐ I don;t work for them! :‐)

Unknown October 14, 2015 at 6:52 AM

Thank you for this wonderful explanation.For beginners in ARDL models, like me, it is of great help.

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Angeline Hirita Bata'anisia October 19, 2015 at 3:20 PM

hello Sir, Thank you for providing this valuable post!I want to ask how to test for unit root for single structural break using Philips Perron Root Unit test as well as test formultiple structural break in eviews 9? Does the noted Breakpoint test above already account for this or is there anothercommand I need to use in eviews?Many thanks and appreciate the help,Angeline

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Dave Giles October 19, 2015 at 3:21 PM

Angeline ‐ the breakpoint tests in EViews 9 give you all that you need.

Tchirwa October 27, 2015 at 9:43 PM

Dear Professor Giles,

Just wanted to thank you for the blog on ARDL estimation which has helped me a lot. I wanted to ask you a questionrelated to ARDL. I am running three country‐growth equations in Eviews 9 and I have 42 observations for each country(1970‐2013). However, I am concerned about the number of regressors (both fixed and dynamic) that are being generatedfrom my ARDL growth equations ‐ at least 22 parameters (including both short and long‐run coefficients). Can I stillproceed with this regression estimation and what would be the effect on degrees of freedom. Or in other words, what isthe limit on the number of regressors that I can include with a sample with 42 observations. The regressors that I haveincluded are investment, human capital, population growth, government consumption, real interest rate, real exchangerate, inflation and fixed regressors (dummy variable for multiparty democracy, foreign aid, commodity price and foreigndirect investment). In total I have 11 regressors with a sample of 42 annual observations.

I look forward to hearing from you on this important matter Sir.

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Dave Giles October 28, 2015 at 8:32 AM

Obviously, you have enough degrees of freedom to fit the model. However, your degrees of freedom will belimited and your inferences will not be very "sharp".

Tchirwa October 28, 2015 at 8:45 AM

So what should be my cutoff number of regressors to use with a sample of 42 annual observations?

Dave Giles October 28, 2015 at 8:49 AM

As with any regression, there is no "cut off number".

Anonymous November 13, 2015 at 10:50 AM

Dear Prof. Thank you for your elaborate post. It really helps us. I downloaded your linked Eviews Code but there is some error. It isnot opening. Kindly fix it. Thank you.

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Dave Giles November 13, 2015 at 12:02 PM

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 assoon as I have a chance.

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

http://davegiles.blogspot.ca/2015/01/ardlmodellingineviews9.html#udssearchresults 20/22

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Mustafa November 24, 2015 at 12:18 PM

Hi, dear Prof.I have run ARDL model using eviews 9 and I have got the result. My questionIs how can I check for serial correlation and stability and R square? Thank you

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Dave Giles November 24, 2015 at 1:06 PM

The R‐square is reported in the output. As with any OLS regression, click on the "VIEW" tab and you can getRESIDUAL DIAGNOSTICS, and STABILITY DIAGNOSTICS, as usual.

MUSTAFA November 25, 2015 at 5:39 AM

THANK YOU FOR REPLY, BUT MY DATA IS PANEL DATA, AND THERE IS NO STABILITY DIAGNOSTIC WHEN WE SELECT RESIDUALDIAGNOSTIC IN EVIEWS 9, WHAT SHOULD WE DO TO TEST STABILITY OR JUST IGNORE THE TEST? THANK YOU

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Dave Giles November 25, 2015 at 9:21 AM

That's what the CUSUM information is for.

oz December 21, 2015 at 11:12 PM

Hi Professor,My all variables are I(1), not mix of I(0)&I(1). Can I still use ARDL instead of ECM as I get better results using ARDLmodel.Thank you.Oz

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Dave Giles December 21, 2015 at 11:24 PM

Oz ‐ yes, you certainly can.

oz December 22, 2015 at 8:59 AM

Thank you so much for the prompt response.Best Regards

oz December 23, 2015 at 10:48 PM

Hi professor,you said in the last part "Third, a 10% change in the price of crude oil will result in a long‐run change of 7% in the price ofretail gasoline. "

is it 7% or 70% ?

Thanks

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Dave Giles December 24, 2015 at 9:15 AM

No 7% is correct. A 1% change leads to a 0.7% change, or a 10% change leads to a 7% change.

TELLA OLUWATOBA IBRAHIM January 2, 2016 at 7:28 AM

Sir, can you tell the different correlogram q statistics and lm serial correlation test and which is more important as a testin ARDL estimation.

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

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Dave Giles January 2, 2016 at 9:12 AM

See this post: http://davegiles.blogspot.ca/2015/05/alternative‐tests‐for‐serial.html

Anonymous January 10, 2016 at 10:51 AM

Dear Professor,

Thank you for your fantastic blog.

In your example you use 2 variables but do we know why EViews reports k=1 (in the bounds testing output)? In theoriginal Pesaran et al. (2001) paper k stands for the number of regressors which in this case is k=2. Also EViews reportsthe k=1 critical bounds (p. 301 from Pesaran et al., 2001) while should report k=2. Thank you very much.

Reply

Dave Giles January 10, 2016 at 10:55 AM

I suggest you check with the EViews forum at http://forums.eviews.com/viewforum.php?f=18

Anonymous January 16, 2016 at 7:28 AM

Dear professor, I really appreciate your very helpful blog on ARDL model. I am running ARDL for my master thesis.However, I did not include the linear trend in the specification (I choose rest. constant), and the results are veryreasonable. Today after reading your blog, I tried selecting the linear trend and the results become not staticallysignificant for most of the variables. Can I exclude the trend ? Can you explain why there is a big difference whenincluding and excluding the trend. Is it necessarily include the trend all the time?? Thank you in advance for yoursupport!

Reply

Dave Giles January 16, 2016 at 11:09 AM

You don;t have to include the trend term ‐ if it's insignificant, then by all means drop it.

Anonymous January 16, 2016 at 8:59 PM

many thanks professor for your prompt explanation! Your econometrics blog is amazing!!

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19/01/2016 Econometrics Beat: Dave Giles' Blog: ARDL Modelling in EViews 9

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