# standard errors

1. ### Regression on estimated variables

I'm making a two-step analysis for my data. First Step: I've collected inflation and interest rate data for 25 countries in a monthly frequency for the last 20 years. I run a simple linear of inflation (right side, X) on interest rate (left side, y) for each country. At the end of this step...
2. ### Generating standardized standard errors

I am testing a structural equation model using Stata. I need to report standardized direct, indirect and total effects with associated standard errors (effects decomposition). While I can get the standardized effects, Std. Err. are only generated in relation to the unstandardized coefficients...
3. ### weighted correlation

Hi Folks, So I have data that looks like: myData <- structure(list(total = c(0.154, 0.223, 0.252, 0.157, 0.196, 0.252, 0.198, 0.162, 0.222, 0.135, 0.196, 0.193, 0.192, 0.274, 0.177, 0.17, 0.214, 0.214, 0.107, 0.22, 0.177, 0.177, 0.165, 0.226, 0.196, 0.267, 0.174, 0.12, 0.159), totalse...
4. ### When are standard errors reasonable?

Obviously you want your model to be as efficient as possible and thus SE as small as possible. But at what point are standard errors acceptable (as compared to being too large)? I have found suprisingly little on this question.