Is OLS blue with Heteroskedasticity?

Heteroskedasticity has serious consequences for the OLS estimator. In addition, the OLS estimator is no longer BLUE. If the form of the heteroskedasticity is known, it can be corrected (via appropriate transformation of the data) and the resulting estimator, generalized least squares (GLS), can be shown to be BLUE.

What assumptions are needed for OLS to be blue?

The Use of OLS Assumptions If the OLS assumptions 1 to 5 hold, then according to Gauss-Markov Theorem, OLS estimator is Best Linear Unbiased Estimator (BLUE). These are desirable properties of OLS estimators and require separate discussion in detail.

Why is OLS called OLS?

1 Answer. Least squares in y is often called ordinary least squares (OLS) because it was the first ever statistical procedure to be developed circa 1800, see history.

What is the idea of OLS?

In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model. This method minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses predicted by the linear approximation.

What is multicollinearity econometrics?

Multicollinearity is the occurrence of high intercorrelations among two or more independent variables in a multiple regression model. In general, multicollinearity can lead to wider confidence intervals that produce less reliable probabilities in terms of the effect of independent variables in a model.

Can I use OLS for time series?

OLS works best, when it works at all, when the errors in the dependent variable are independent, identically, and normally distributed. Some departures from these assumptions will still produce acceptable results. However, time series errors are likely to be non-independent and non-identically distributed.

Is the OLS estimator unbiased?

Under the standard assumptions, the OLS estimator in the linear regression model is thus unbiased and efficient. No other linear and unbiased estimator of the regression coefficients exists which leads to a smaller variance.

Why do economists run regressions?

Regressions are used to quantify the relationship between one variable and the other variables that are thought to explain it; regressions can also identify how close and well determined the relationship is.

What is blue econometrics?

BLUE is an acronym for the following: Best Linear Unbiased Estimator. In this context, the definition of “best” refers to the minimum variance or the narrowest sampling distribution.

What do we minimize in OLS?

The most commonly used procedure used for regression analysis is called ordinary least squares (OLS). The OLS procedure minimizes the sum of squared residuals. We choose the s that minimize the sum of squared residuals.

How does OLS work?

Ordinary least squares (OLS) regression is a statistical method of analysis that estimates the relationship between one or more independent variables and a dependent variable; the method estimates the relationship by minimizing the sum of the squares in the difference between the observed and predicted values of the …