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17 Cards in this Set

  • Front
  • Back

Best Linear Unbiased Estimator (BLUE)

Among all the linear unbiased estimators, the one with the smallest variance.

Biased Toward Zero

A description of an estimator whose expectation in absolute value is less than the absolute value of the population parameter.

Ceteris Paribus

All other relevant factors held fixed.

Downward Bias

The expected value of an estimator is below the population value of the parameter.

Endogenous Explanatory Variable

An explanatory variable that is correlated with the error term, either because of an omitted variable, measurement error or simultaneity.

Exogenous Explanatory Variable

An explanatory variable that is uncorrelated with the error term.

Gauss-Markov Theorem

A theorem that states under the five Gauss Markov assumptions, the OLS estimator is blue.

Inclusion of an Irrelevant Variable/Overspecifying the Model

An explanatory variable that has a zero population parameter estimate (so no effect on y).

Micronumerosity

A term to used to describe the properties of econometric estimators with small sample sizes.

Misspecification Analysis

The process of determining likely biases that can arise from omitted variables, measurement error, simultaneity.

Multicollinearity

Correlation between the indenpedent variables that is large.

Omitted Variable Bias

Bias that arises in the OLS estimators when a relevant variable is omitted from the regression.

Partial Effect

The effect of the an explanatory variable on the dependent variable, holding other factors constant.

Perfect Collinearity

One independent variable is an exact linear function of one or more other independent variables.

Upward Bias

The expected value of an estimator is greater than the population parameter value.

Variance Inflation Factor

The term in the sampling variance affected by correlation between the explanatory variables.

Underspecifying the Model

Leaving out a variable that has a nonzero partial effect on the dependent variable.