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You have given two warnings not to use if sample size is less than 100 and not suitable for more than two breaks .references of any such article sir please????
Hi, Yes adding dummies is a good way of removing the effects of a structural break. My advice is that before you do a VAR, do a Johansen test to make sure there is no cointegration between your variables. If there is cointegration, do a VECM model. If there's no cointegration, do a VAR model. Hope that helps.
Hey, if you liked the video, please subscribe, share and thumbs up. It would be great to be able to monetise my videos to the point where I could purchase some proper screen recording software.
Also, if you have any questions about the video or if anything is unclear, don't hesitate to comment and ask me questions - I'll try to reply as soon as possible.
Thanks.
You have given two warnings not to use if sample size is less than 100 and not suitable for more than two breaks .references of any such article sir please????
I have 50 observations 2005Q1-2022Q4. What would you suggest for the trimming parameter?
Shouldn't we use seasonally adjusted unemployment data for Bai-Perron multiple breakpoint test calculations?
Didn't found part 2
Part 2? Thanks,.
should this work with 20 years of quarterly data (81 observations)?
thanks for your video, how to deal with structural break in VAR ? do i have to add dummies? any idea please share with me i'm struggling
Hi,
Yes adding dummies is a good way of removing the effects of a structural break. My advice is that before you do a VAR, do a Johansen test to make sure there is no cointegration between your variables. If there is cointegration, do a VECM model. If there's no cointegration, do a VAR model.
Hope that helps.
@@ImperiumLearning thanks
Why did you say that using more than 3 st. breaks is this ok for dissertation purposes but not for publication