Econometrics - Interaction Terms

could you ever do an interaction term between just 1 level of categorical variable and another variable?

Hello Nick, thank you for the detailed explanation. How would you do this (code in python) when you have 20 independent variables of which is a treatment variable which is binary?

Thank you ☺☺

Hello! This is awesome. Two questions, if I may: could I interpret just the way you did it, but with Odds Ratios? And, if I find non-statistically significant interactions, can I still calculate predicted probabilities and present them in my paper?
Many thanks for this!

Hi Nicky. I have been looking for a video explaining interaction of two dummies for a long long time. Thanks for saving my thesis. I was wondering, in the case of your example, if we can make margin and interaction plots in stata, and how we can explain them. thanks.

This is the best explanation for interaction terms I've come across. Thank you again for your consistent clarity!

one question about three-way interaction terms. Let's label each variable A(main variable), B(1st moderator), C (2nd moderator). I'm interested in (hypothesize) the relationships A-B and A-B-C. Should all two-way (AB, AC, BC) and three-way interaction terms (A * B * C) be included in a regression model and result or would be it fine to include some of interest (AB, ABC) only?

hello thank you very much for this video it was so clear and you have explained in very great way and easy to understand, thank you for your effort
🌸

Hey Nick. Thank you for your videos they do really help. I am writing my thesis and I just want to make sure whether I can have the regression analysis done this way: my dependent variable is measured with a likert scale. And I wanted to make sure if I can have my independent variable and my moderator done with a binary variable (with yes and no). Thank you so much!

hey! just a clarifying question. for a married person that didn't go to college, the effect on log earnings is 0.24. However, if a marrier person went to college, the effect would be 0.24 + (-0.25) = 0.01? So in this case going to college for the married person would actually be worse off?

Thanks a lot for the video! It is amazing!! I have one question tough: How the interpretation changes if we add in the same model another variable and we interact with MarriedTRUE? Let's say for example, that in the model we have: x1=MarriedTRUE; x2=CollegeTRUE; x3= MArriedTRUE x College TRUE, x4 = White; x5= MarriedTRUE x White. Do you have any video for that? Or any esy explanation? Thanks a lot in advance!!!

You have a gift for teaching econometrics! When I am learning a new concept, or need a refresher, your channel is one of the first supplementary sources I turn to. Thank you so much for providing these lessons free of charge to the public.

Thanks for the video. Let's assume the interaction term has a significant p-value and whereas both predictors have an insignificant one. Would this mean the interaction term is useless for interpretation regarding the dependent variable, because the effect gets lost in the insignificant predictors?

Great video!

This channel is very soon gonna become the Lady Gaga of Econometrics

Does the interpretation of the married main effect "marriedTRUE" change when including the interaction term? Please help

Thank you!

Hey Nick! Do you have a video like this one but interpreting interaction terms in probit models? I'm stuck with my bachelor thesis and would really appreciate the help :) Thanks!

Super comprehensive, thank you very much!

You are a legend!

thank you! great video.

Great video. Helped me a lot! :D

Hi, Nick, great explanation! May I ask a question? Is the interaction effect always smaller than the main effects? Can you explain a little why that is?

Hi Nick, this is very helpful. May I ask a question? How would you interpret the interaction effect if it is so strong that it changes the sign, e.g. 0.85 + (-1.05)*1= -0.2? Is there a substitution effect behind? How do I interpret it? Thank you very much

Hi Nick, This is very helpful. May I ask a question? In the example, the coefficient on the interaction term (marriage * collage) is actually insignificant. Do we still need to add that coefficient when we interpreting the regression?

thank you, very insightful

Hey Nick, it's me again. (Pandemic has made it difficult to discuss with people, and these videos have been a god-sent)

I am running a fixed-effects model which controls for individual fixed effects and time fixed effects (years). The way my data was generated, age is kept as an individual fixed effect. This is, if a person was 17 in 2015, they will show as the nearest multiple of 10, so 20 years old in this case, in the entire panel. However, I want to control for age. So I plan on interacting it with year. At first, it made sense to just scale the age by adding increments of 1 depending on how far it was from 2015. In plm, the model ran fine. In lfe, the effect of Age was absorbed by the fixed effects.

Now I am running the model by multiplying the age of an individual by the current year and the model is running fine. My question is: do you know why addition as an interaction was absorbed by the fixed-effects model? And if there is any specific side effect of interacting variables with the fixed effects. I went all over the internet looking for an answer, and all I got was an article saying I should use a “double-demeaned” estimator. That sounds too complex to me though.

Thank you so much for all the help you provide with your videos! Even after going through Pischke and Woolridge, it's your videos that end up answering my questions.

Hi! I am attempting to plot the marginal effects/confidence intervals of an interaction in a panel data model (plm) and have had no luck whatsoever finding a package that supports plm objects! Would you happen to have any suggestions on packages or code to use for this? I’m going absolutely crazy! Thanks so much!

**I am interacting two continuous variables.

Hi Nick, Thank you for the wonderful video. I am two continuous variables in my growth model. One important thing with the interaction terms is that we have to calculate substantively meaningful marginal effects and standard errors (Brambor et al. 2005). Could you please show how to do this in STATA?