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Suppose you have an outcome variable y and two dummy variables, treated and after. (So some observations of y are treated after a certain date and others are never treated--the control group.) You could do
The last coefficient is the DiD estimate.

Test whether coef_A - coef_b =0 using a Wald test.

I think you don't want equal signs inside @recode.

Makes sense

Okay. So it is nice if there is little multicollinearity. It is also nice if we have many observations and other things. For a given dataset and a correctly specified number of lags, ols is the best we can do…multicollinearity or not.

Specifying lags is part of specifying a model.

You still haven’t said why you think an estimate with multicollinearity is bad.

Correct. But this is a consequence of the data and the model. Basically, ols is optimal in the presence of multicollinearity.

Yes. But these problems have very different consequences. What problem do you think multicollinearity causes?

You are right that there is a distinction. Of course, once you've run the ARDL you get estimates and standard errors for trhe case at hand.

In principle 20 or 30 observations might be okay. In practice I would say it likely isn't enough.

A first question is why you care about multicollinearity??? For many macro time series determining exact timing of effects is quite hard. So ARDL models do have a lot of multicollinearity. That means individual coefficients are not well identified. But functions of the coefficients, such as long-run...

Have you looked at https://eviews.com/download/whitepapers/pyeviews.pdf?

Are you missing the multiplication sign after c(3)?

Gareth's suggestion does what you ask. In your file you have the dummy stay zero if the return stays constant after it first falls. Is that what you want?

Run a unit root test on lowFreq in the attached work file. You get an error message. You can make the error message go away by reducing the maximum number of lags. Nonetheless, I think this is a bug.

You might want to take a look at https://cran.r-project.org/web/packages ... iewsR.html, which may give you a different, but easier, approach.