# 4.) The Classical Model Flashcards

The term classical refers to a set of fairly basic assumptions required to hold in order for…

OLS to be considered the “best” estimator for regression models

The CLASSICAL ASSUMPTIONS must be…

met in order for OLS estimators to be the best available

The Classical Assumptions are…

- ) The regression model is linear, is correctly specified, and has an additive error term.
- ) The error term has zero population mean.
- ) All explanatory variables are uncorrelated with the error term.
- ) Observations of the error term are uncorrelated with each other (no serial correlation).
- ) The error term has a constant variance (no heteroskadasticity).
- ) No explanatory variable is a perfect linear function of any other explanatory variable(s) (no perfect multicollinearity)
- ) The error term is normally distributed (this assumption is optional but usually is invoked).

Assumption I

The regression model is linear, is correctly specified, and has an additive error term

Assumption II

the error term has a zero population mean

Econometricians add a stochastic (random) error term…

to regression equations to account variation in the dependent variable that is not explained by the model

The properties of the OLS estimator of the betas still hold because the equation is linear. Two additional properties also must hold.

- ) We assume that the equation is correctly specified. If an equation has omitted variable or an incorrect functional form, the odds are against that equation work ing well.
- ) We assume that a stochastic error term has been added to the equation. This error term must be an additive one and cannot be multiplied by or divided into any of the variables in the equation.

In essence, the constant term equals…

the fixed portion of Y that cannot be explained by independent variables whereas the error term equals the stochastic portion of the unexplained value of Y.

Assumption III

All explanatory variables are uncorrelated with the error term. It is assumed that the observed values of the explanatory variables are independent of the values of the error term.

Assumption IV

Observation of the error term are uncorrelated with each other. The observations of the error term are drawn independently from each other

If an explanatory variable and the error term were instead correlated with each other, the OLS estimates would be likely to attribute…

to the X some of the variation in Y that actually came from the error term

If the error term and X were positively correlated then…

the estimated coefficient would probably be higher than it would otherwise have been (biased upward). because the OLS program would mistakenly attribute the variation in Y caused by error term to X instead

Classical Assumption III is violated most frequently when…

a researcher omits an important independent variable from an equation.

Classical Assumption V

The error term has a constant variance

To meet classical assumption V, the variance of the distribution from which the observations of the error term are drawn is…

constant