A simple, non-mathematical and intuitive explanation of the endogeneity bias and the importance of the 2-stage least squares (2SLS) model.
This is one of the fundamental models of econometrics and is able to untangle causality from spurious correlations. It is crucial for anyone using non-experimental data to understand the 2SLS model.
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Keywords: 2SLS, 2-stage least squares, 2 stage least squares, endogeneity bias, exogeneity, econometrics, statistics, OLS regression, regression analysis, GMM, maximum likelihood, two-stage least squares, instrumental variables, instruments, endogenous, exogenous, TSLS, economics, finance, stata, eviews, endogeniety
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Great video but total clickbait thumbnail. Gotta do what you gotta do I guess
https://youtu.be/KDZKjNsdWeE
this is such click bait…. didn't even explain 2sls–just a commercial for your course
Excellent explanation. Much better than my grad profs who made such concepts impenetrable.
How is this the most simple explanation of 2SLS? You didn't explain it at all.
clickbait
So in theory, if you had a variable measuring competitiveness and it would correlate with both, your main explanatory variable (education) and you dependent variable (wages), then you would simply include it in your regression model? What about correlation with education?
Clear, thank you!
what kinda accent is that?
I am in Indonesia and I need 2LS regression model 😭. Help
Very nice:)
Thank you for the explanation 🙂
thank you do much for this
excellent explanation!!!!
Thank you!!!
Hi there I am seeing the effect of derivative usage on firm value, and so regression firm value with my independant variable derivative usage and set of control variables.
I know there is an endogeneity issue in the sense that there a characteristics both unobservable (eg managerial quality) and observable that have a postive effect on firm value and are postively correlated with derivative use.
I understand the enodogenity in this sense mean that these characteristics that are captured by the error term are linked to the the explantoryy variable deriavtive usage. What my main question is is which variables are ones reffered to as endogenous?
a)is it the firm value that is enodogenous or deriavtive usage that is enodogenous
b) or are firm value and derivative usage both "endogenous variables"
c) or is the observed/unobserved characterisitcs that are referred to as endogenous. Thanks so much.
what the fuck is that tumbnail u fuckin piece of shit .,… btw the video is good
thank you, this explanation was so helpful!
can you do a video on heterogeneity?
the best explanation I've watched so far
I really appreciate this vedio .. helpful and useful.
I am not sure, but I think this illustrates "confounding" or "common causation." Endogeneity selection bias would result from a situation in which wages and education are independent (B1 = 0), but both cause something else, such as happiness. If we then regressed wages against BOTH education and happiness, it would result in a spurious negative relationship between education and wages (B1-hat < 0).
Thank you so much bro
Thanks so much for this video!
how to apply it in spss??