Dear Statalist,
I have a fairly simple doubt, forgive me if it's rather basic, but I was wondering if you could clear something for me. When we have reverse causality (as a result of Endogeneity), how does this affect the standard errors? Are they overestimated? Does it depend on the sign of the bias?
More concretely, I have a simple regression where 2 variables influence one another in an upwards bias way, and I was wondering up to what extent can I still use my results (since I'm not really using the coefficient values, only if they are significant or not). Since my coefficients will be overestimated, will the t-stat also be overestimated, and thus my variables be "overly significant", so to speak?
I've tried to search for some references on this matter but I didn't find much to go from except that "endogeneity affects and biases estimates".
Any help you could give me, I would be beyond grateful.
Merci,
Anthoine
Related Posts with Effect of Endogeneity on Significance
Survival analysis with inverse probability weighting after multiple imputationDear Statalist-users, Hopefully, there is someone who can help me with the following: I'm trying to…
Plot of Interaction TermI am trying to use margins and marginsplot to plot the effect of X1 in a regression as follows: Y=a…
How to modify individual graph's title on combined graphDear Stata users, Suppose we have a combined graph that is composed of two individual graphs, let's …
tvgc - time-varying granger causalityHow can I solve this error in Stata? tvgc_cv(): 3499 mm_quantile() not found <istmt>: - funct…
Creating a loop to count the weeks before and after a policyHi, I'm working on understanding the impact of a hospital policy on healthcare utilization. The pol…
Subscribe to:
Post Comments (Atom)
0 Response to Effect of Endogeneity on Significance
Post a Comment