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Monthly Archives: August 2016
The Derivative of the Natural Logarithm
The derivative of the natural logarithm is defined the following way: The formal proof of the derivative is provided at the bottom of this post. The following example further explains the derivative of the natural logarithm. Remember that Advertisements
Posted in Proof, Statistic
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Robust Standard Errors in STATA
”Robust” standard errors is a technique to obtain unbiased standard errors of OLS coefficients under heteroscedasticity. In contrary to other statistical software, such as R for instance, it is rather simple to calculate robust standard errors in STATA. All you … Continue reading
Posted in Computing and Others
3 Comments
Robust Standard Errors in R
One can calculate robust standard errors in R in various ways. However, one can easily reach its limit when calculating robust standard errors in R, especially when you are new in R. It always bordered me that you can calculate … Continue reading
Posted in Computing and Others, Econometrics
15 Comments
Robust Standard Errors in R – Function
One can calculate robust standard errors easily in STATA. However, one can easily reach its limit when calculating robust standard errors in R. Although there exist several possibilities to calculate heteroscedasticity consistent standard errors most of them are not easy … Continue reading
Posted in Computing and Others, Econometrics
6 Comments
Robust Standard Errors
”Robust” standard errors is a technique to obtain unbiased standard errors of OLS coefficients under heteroscedasticity. Remember,the presence of heteroscedasticity violates the Gauss Markov assumptions that are necessary to render OLS the best linear unbiased estimator (BLUE).
Posted in Econometrics
5 Comments
Violation of CLRM – Assumption 4.2: Consequences of Heteroscedasticity
Violating assumption 4.2, i.e. leads to heteroscedasticity. Recall, under heteroscedasticity the OLS estimator still delivers unbiased and consistent coefficient estimates, but the estimator will be biased for standard errors. Increasing the number of observations will not solve the problem in … Continue reading
Posted in Econometrics
3 Comments