Econometrics: Control Variables

Amazing Video on Control Variables. Why to use

Great explanation of the control variables! Thank you, Professor!

Superb video, helped me a lot to refresh my understanding in under 10 minutes. Comes in really helpful as I am working on my Bachelors Thesis! Thank you for your work!

It's a very good visualization. Would be perfect to see a numerical illustration of this control element.

Thank you. The concepts are simply enough but my ADHD makes it incredibly difficult to focus. Your video helped.

Thank you this was very well explained

PLEASE REPLY ASAP!!

GDP = shadow economy + inflation + government debt + Unemployment

I am looking to investigate the impact of Shadow economy on GDP, and what I just listed is my econometric model.
Would inflation, gov debt and unemployment thus be my control variable?

thank you

Thanks a lot, you save my day, i couldn´t find a channel explaining this in my native language

thank you for the clear explanation and visual illustration!. I've been confused by "what is controlling for a long time ". thank you! so the 2 subtracting process is automatically done when we are doing OLS?

This is the best explanation of control variables I've ever seen. Thank you, HK.

Thank you so much, I finally understand what is control variable..

Thank you for explaining this in a simple way.

Hello Nick, great video!

I would like to ask two questions regarding the use of control variables:
1. Shouldn't we worry about multicollinearity since we know in fact that shortswearing and temperature are correlated?

2. Can we have a meaningful interpretation of the control variable coefficient as well (temperature) when we know it is correlated with shortswearing or its use is purely to fight the endogeneity problem?

Thank you in advance.

At the end slide as you add to the scatterplot variable W, you write as Z, also I think it is a little confusing because you start showing the relationship already controlled by Z (or W) instead of showing it in a scatterplot first without control.

I'm taking a multiple regression course for a data analysis masters, and this video really helped piece things together! Thinking about control variables as variables that cut out the parts of the relationship we don't want to consider in our model is a really useful way of thinking about controls... hopefully I got that right. Thanks!

ah ha pandemic haircut , I caught you!

Great video! had to like and subscribe

I wonder tho, if i pick a control variable like fx. gender on a topic like wages... does that mean that I believe that gender has an impact on wages?..

Very clear explanations. Thanks

Remarkably good explanation.

you're cool

Super!!! i finally learned while clustering can explain positive relationship when in fact there's a negative relationship! Thank you!

Man, you’re fucking good explaining this! Thanks a lot

Very helpful, thanks!

Hello, Nick, could you explain what it means by "conditioning on a set of covariates?" Does it mean the same as controlling for these variables?

Absolutely Amazing!

Thank you so much, you explained very well.

So helpful! Thank you very much!

Excellent video sir. Quick question. When using control variables lets say.. exchange rates from the world bank data base (time series data). Do you make the values constant by using one specific value throughout the years or you use the timeseries data as is for the different years?

Seriously, with this enthusiasm of yours, you could easily explain any subject in the whole world to me and I would never get bored.

I wish tons of likes and subscriptions to you!

well-explained and easy to capture the intuition. Thanks a lot. :D

But sir in the example used temperature can also partly explain shorts wearing....so does the problem of multicolinearity arises when we add temperature to the model ???

just the explanation I was looking for, thank you!

A bit late to the video, but this was extremely useful! Million thanks :)

What is the difference between a moderator and a control variable? Are they the same?

Thank you for the video. I have a few questions. How do we know what covariates to include/ exclude in/from our model? Also, how do we determine how many covariates to include in our model? Do we simply use theoretical knowledge or do we have tests that we can do?

You explain things so well. Thank you for posting this!

Very clear explanations, thank you very much!

Excellent contents in the subject matter. It is valuable to build knowledge and skills. I am really thankful for such efforts.

Hey Nick! Could you answer me a question?
I have a model (OLS) with a key explanatory variable and its effects on my dependent variable, and some (5) control variables. My main explanatory variable is significant, but only two of the control variables are significant; although, the model is itself statistically significant. My objective for the paper is just to tell if some effects caused by my explanatory variable are found, and its direction (positive or negative). Do you recommend keeping all the variables in the regression output table, telling which are not significant, and making clear that it doesn't fully matter for the objective of the paper?

Sorry for this long and broad question. Thanks!

Very helpful!

Excelent video
Your content is awesome
This animation that explain what a control variable do is very helpful!