This question already has an answer here:
Say, for instance, I'm estimating a model with about 5 million observations using linear regression or MLE. Given that the estimates are consistent, using the standard rule of rejecting the null on a 5% significance level will pretty much never make me entitled to reject the null (of the parameter being equal to zero), i.e. everything is significant.
I should probably use another significance level, which is smaller than 5%, and my question is if there is any literature on picking the right significance level, or how would you guys handle this problem? Should I simply stick with the 5% significance level?