[Sebastian Kripfganz]

You shouldn't choose the standard errors based on whether this delivers "improved" statistical significance. In general, I would not expect the standard errors to become smaller - i.e., coefficient estimates to become more significant - when using Newey-West standard errors.

You are right that a p-value of 0.066 is not very comfortable. This could be used as a justification to use Newey-West standard errors. Alternatively, you might want to address the serial correlation in the first place by allowing for higher-order lags in the ARDL specification. If your sample size allows, you could increase the maximum lag order with the ardl option maxlag(), and/or use the AIC instead of the BIC model selection criterion.

[joseph Mgaya]

Greetings, I have these results from the test of Durbin Watson d-statistic( 9, 34) = 2.459839 and Breusch-Godfrey P value of 0.066, i don't feel comfortable with the P value, can i use Newey-West just to be safe? After applying Newey West, the significance of coefficients seems to have improved

[joseph Mgaya]

Greetings, I have these results from the test of Durbin“Watson d-statistic( 9, 34) = 2.459839 and Breusch“Godfrey P value of 0.066, i don't feel comfortable with the P value, can i use Newey-West just to be safe?

[Sebastian Kripfganz]

We explain in our 2018 UK Stata Conference how to use the sbcusum command. There is also the community-contributed cusum6 command, which can be installed from SSC. It can be used after ardl like any other postestimation command for regress; see the "Postestimation" section of our presentation for general instructions.

[Kong Chantha]

Dear Sir/Madam
I know the command estat sbcusum for testing Parameter stability in model.

How Can STATA runs CUSUMQ ? how about Code/ command ?

thank you

[Sebastian Kripfganz]

The dynardl package might be useful for that purpose.

[Olav Hose]

Hello again,

I do have another question. Everything regarding the ARDL has worked out fine for me, but I do wonder if it possible to illustrade the results with a graph? I am meaning to include how the independent variable of interest affect the dependent variabe, and a graph illustrating the effect first with the initial lags of the short run into the long run? I have not find how to illustrate an ARDL with a graph, so would be very helpfull if anyone had any solution.

Thank you.

[Sebastian Kripfganz]

You would not normally specify the variables in first differences. When called with the ec option, the command itself parameterizes the model in first-differenced form (with additional level error correction term).

[Alex Grisdale]

Hello once again,

When configuring an ardl in stata and all the variable are stationary at I(1) would you input the command "ardl d.lngdp d.lncpi d.hc, ec btest" for example. So would you have to difference all the variables before putting them in the command?

[Olav Hose]

The varsoc command is not the most appropriate one for the single-equation ARDL model; it is more appropriate for VAR models. The ardl command does its own lag selection if you just use the aic or bic option, possibly varying the maximum lag order with the maxlags() option. For the bounds test, it is advisable to use a less parsimonious specification to ensure there is no remaining serial correlation; the AIC is therefore generally preferred over the BIC for this purpose.

Perfect, thank you very much. I really appreciate it.

[Sebastian Kripfganz]

The varsoc command is not the most appropriate one for the single-equation ARDL model; it is more appropriate for VAR models. The ardl command does its own lag selection if you just use the aic or bic option, possibly varying the maximum lag order with the maxlags() option. For the bounds test, it is advisable to use a less parsimonious specification to ensure there is no remaining serial correlation; the AIC is therefore generally preferred over the BIC for this purpose.

[Olav Hose]

Olav Hose
I cannot recommend any p-hacking strategies. You could of course ask whether the model is correctly specified. There might be important variables missing, the maximum lag order may have to be increased to capture all the dynamics, variable transformations (log) might be needed (if not already done), etc. Once you are confident that the model specification is accurate, you then just have to accept the test result. Often, non-significance can be a meaningful result by itself.

Perfect, thank you very much. One final question, I tried out some of the proposals you gave, and when I add extra lags on some of the model, it become statistically significant. However, the lag order of that model is higher as proposed by the BIC criteria which I obtained from the varsoc command. I know it is important not to adjust my model until I get the results which I want, however, would having more or less lags as proposed by the criterium make the model biased?

[Alex Grisdale]

Sebastian Kripfganz

Thank you very much for the help, I appreciate it.

[Ronak Parikh]

Dear Sebastian, that's really great - I have been able to obtain estimates. Thank you!

[Sebastian Kripfganz]

Ronak Parikh
You need to use the correct inverted commas. Copy the code from my previous post 423 instead of from the presentation PDF.