# clasical assumptios

## Econometrics: Classical Assumption 7 – The error term is normally distributed.

According to the Gauss Markov Theorem, an Ordinary Least Squares (OLS) model can be considered as the Best Linear Unbiased Estimator (BLUE) as long as the first six classical assumptions are met. However, if you are conducting an econometric analysis and wish to make statistical inferences about the data, such as performing statistical hypothesis testing …

## Econometrics: Classical Assumption 6 – No explanatory variable is a perfectly linear function of any or all of the other explanatory variables.

Two variables are a perfectly linear function of each other when one variable can be entirely explained by the movement in the other variable and vice versa even though the absolute change in each variable may differ. Examples of positively perfectly collinear variables would include age and experience or sales and taxes paid. Whereas examples …

## Econometrics: Classical Assumption 5 – The error term has a constant variance.

In econometrics, variance can be described as the spread of the data from the average value of the data set in question. When running Ordinary Least Squares (OLS), it is vital that this level of variation in the data stays constant. If the variance of the errors in the data set is not consistent but …

## Econometrics: Classical Assumption 4 – All observations of the error term are entirely uncorrelated with each other.

In econometrics, a fantastic way of observing the relationship between the respective error observations within a given data set  is through a visual relationship. It makes any relationship immediately obvious when you draw a representation of the residual level present within the data set. What we see here is what can be described as …

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