ARDL Model

1. What is ARDL model?
Professor Steve Makambi commented as such>> There is no doubt that Eviews 9 is the
best when estimating ARDL model because of the following reasons:
1. Lag length criteria: Appropriate no. of lags for each of the independent variable and the
most parsimonious model is chosen automatically.
2. It estimates Pesaran et al., ARDL model which may include I(1) and I(0) variables (but not
I(2))
3. Tests for co-integration using bound test approach is provided for in the module
4. It includes a provision of estimating the error term (co-integrating coefficient), short run
and long run coefficients directly.

2.How to run ARDL model using STATA?
Professor Aymen Ammari commented as such>
1. First calculate the F-Value by Bound testing approach, by getting the F-value you can be
in position whether cointegration exist among your indicators or not. After confirmation the
cointegarion in your model you can get ARDL(Long run) and ECM (short run) results,
2- Command is “ardl depvarriable indepvar1 indepvar2 indepvar3 … , aic ec regstore
(ecreg)”
Other general command are:
“estat dwatson” (Durbin Watson statistics, at 1st order autocorrelation).
“estat archlm” (ARCH LM test for higher order autocorrelation)
“estat bgodfrey” (Breusch Godfrey LM test for higher order autocorrelation)
“estat hottest” (Breusch Pagan Heteroscedasticity test)
“estat ovtest” (Ramsey RESET test)
“estat vif” (Test for the Multicollinearity

3. What is ARDL model?
Professor Abebe Derbie commented as such > ARDL is a model which is consist of lag of
the dependent variable and lags and leads for othe variables too. And it may contain both
the long run and short run(ecm) daynamics.

4. Sample size in ARDL model and cointegration
Professor Nasiru Inuwa commented as such>> Conventional cointegartion techniques that
requires large observations can be applied let alone ARDL that can produce robust result
even in small observations.

5. What is ARDL?
Professor Andhyka Nugraha commented about ARDL Model as such >>> Commonly we
thing authors on academic papers put all diagnostic test result from first model ARDL (the
variables of model at level) on last result, but on reality the diagnostic result first model (for
Ardl Bound Testing) and last model (cointegrating form and long-run coefficient) is different.
i was asking in this forum and another forum statistic but nobody tell me how to do. most of
them suggest me to present diagnostic result and testing robustness for first model (which
all variables at level). i seach byself and then i found that "the keys" is "equation longrun" on
"cointegration form" from first model. we must "generate" equation long-run and making new
variable with name ECT. then estimate cointegrating model on least square to present short
and long run coefficient (final result).

6. Estimate ARDL model using STATA
Professor Noman Arshed has estimated ARDL model using STATA as such>
https://nomanarshed.wordpress.com/2015/08/16/estimating-ardl-with-cointegrating-bounds-
in-stata/

7. How to run ARIMA Model
Professor Ehtesham Ashraf​ has given a source as below>>
https://www.otexts.org/fpp/8/


8. EVIEWS-9 is the best for ARDL
Professor Steve Makambi commented as such>> There is no doubt that Eviews 9 is the
best when estimating ARDL model because of the following reasons:   
1. Lag length criteria: Appropriate no. of lags for each of the independent variable and the
most parsimonious model is chosen automatically.  
2. It estimates Pesaran et al., ARDL model which may include I(1) and I(0) variables (but not
I(2)) ******* this for me was a Eureka moment*****  
3. tests for co-integration using bound test approach is provided for in the module
4. It includes a provision of estimating the error term (co-integrating coefficient), short run
and long run coefficients directly


9. How to remove serial correlation from ARDL model?
Noman Arshed commented> Try bigger lag order.

Seye Olasehinde-Williams commneted> Serial correlation is not a problem in ardl if you
choose sufficient lags.

Tella Oluwatoba Ibrahim commented> practical experience has shown that the problem can
be solved changing the lag selection. I am sure he didn't use 1-1 lag model... so he needs to
be careful in lag selection to prevent the problem of micronumerousity

Seye Olasehinde-Williams commented> Check Stock & Watson page 612

Zia Eco Marwat commented > its not aproblem because ARDL handel the serial correlation
prob ...

Oussama BA commented> The aim of ardl model is to remove serial correlation. But you
must choose the correct lags. If you chooses your lags as suggested by Aic and Sbc criteria
your model must be good. But think about choosing different lags for your different variables.

Sheikh Muzammil Naseer commented> Just run the model with default lag...


10. How to interpret the ARDL model result?
Sheikh Muzammil Naseer posted this figure below. (Jan 13, 2017)















Sayed Hossain commented> The error correction term (-1.292) here is negative and
significant meaning that there is a long run causality running from independent variables to
dependent variable. It also confirms that all the variables are cointegrated or have long run
relationship. We can also say that about 129.27 percent gap between long run equilibrium
value and the actual value of the dependent variable(FDI) has been corrected. It can be
also said that speed of adjustment towards long run equilibrium is 129.27 percent annually
(provided data is annual). Also we can say that system corrects its previous period
disequilibrium at a speed of 129.27% annually. But the speed or adjustment at 129.27%
seems to be over adjusted or may not be practical.

Himmy Khan commented> The error correction coeff should not be lesser then (-1). Not
good for the model. Recheck your data and model.

December Man commented> speed of adjustment to equilibrium is 129%.

Abdul Rahman Nizamani commented> And it also means there is a significant long run
relationship among the variables.

Noman Arshed commented> It is over correcting. Not a sustainable equilibrium.

Olasehinde Timilehin commented> Noman Arshed had said it all. Something must be
wrong....error correction term shows that... .equilibrium convergence does not exist....Model
may needs remodification...Linear model may not be best option. There may be need to
correct for break...Almost, it can reveal the true nature of the data (leave it and find its
Causes)

Jijie Housburg commented> Normally we should get -1<ect<0

Olasehinde Timilehin commented> because there must be short run dynamic that drive the
economy towards a steady state (long run).. Since the coefficient of equilibrium correction is
not valid economically.Long run relationship is not feasible here

Nadia Ameer commented> This might becoz of not selecting appreciate lag length....I also
faced same problems in my model...

Saud Ahmad error correction term must be between 0 to -1

Udegbunam Norris Chinonso commented> Equilibrium convergence does not exist.


11, Lag selection in ARDL
Burcu Özcan posted the following ARDL lag selection figure.
























Aleem Akhtar commented> You can choose whatever lags you want on the basis of lowest
AIC/SIC values. Moreover if you are not getting significant results, you can change lags in
both options.

Saud Ahmad commented> You can use the automatic selection criteria initially. And then
you can reduce your model by testing ristrictions through wald test. As your data is not large
enough so I suggest to take less number of lags to avoid degree of freedom problem.
Usually for annual data 1 or 2 lags are enough and for quarterly 4 lags are enough.


12. Interpret the result
Pareeshay Jahanxeb Khan posted below.


























David Mendy commented> The error correction coefficient, estimated at -0.2060 is highly
significant, has the correct negative sign, and imply a low speed of adjustment to
equilibrium. According to Bannerjee et al. (2003) as cited in Kidanemarim (2014), the highly
significant error correction term further confirms the existence of a stable long-run
relationship. moreover, the coefficient of the error term (ECM-1) implies that the deviation
from long run equilibrium level of ( dependent variable ) of the current period is corrected by
20.60% in the next period to bring back equilibrium.

Pareeshay Jahanxeb Khan commented> Is it convergent or divergent to the equilibrium??

Imran Rjn commented> i am sure, it is convergent...


13. What are the assumptions of ARDL Model

Saeed Aas Khan Meo posted below>
POPOLAR BLOGS
Dave
Meo School of Research
Shishir Shakya
Noman Arshed
ARDL Model
Hossain Academy Note
Univariate Models
Multivariate Models
Panel Data Model
14, What should be the right value of error correction term in ARDL model?
Professor Tella Oluwatoba Ibrahim commented> I see nothing wrong in the original post...
basically, the are two school of thoughts. the rigid proponents of 0 to -1 and others which see
nothing wrong from -1 to -2 like Narayan Kumar(2006).