The Moderate Anomalies Flashcards
Suppressor Variables
Severity Ranking: (5/18 Total) (1/7 Moderates)
Description: Two independent variables are uncorrelated with the dependent variable, but are negatively
correlated with each other.
Implication: Significances of suppressor variable parameter estimates are spurious.
Identification: Coefficient for each suppressor variable is insignificant when the other suppressor variable is
dropped from the model.
Correction: Drop both suppressor variables from the model.
Heteroskedasticity
Severity Ranking: (6/18 Total) (2/7 Moderate)
Description: Variance of the error term is not constant.
Implication: Standard errors of the OLS parameter estimates are biased and inconsistent. The degree of
bias in the standard errors is typically small enough to have little effect on significance tests
except in cases of extreme heteroskedasticity.
Identification: White test. Breusch-Pagan test.
Correction: WLS, GLS, GMM, or OLS with robust standard error estimation.
Omitted Regressor / Model Misspecification
Severity Ranking: (7/18 Total) (3/7 Moderates)
Description: A regressor that belongs in the regression has been excluded.
Implication: OLS parameter estimates are biased and inconsistent.
Identification: Theory. Coefficient on omitted regressor is significant when regressor is included. Anomaly
might exhibit itself as serial correlation, or as stochastic regressor (if the omitted regressor is
correlated with an included regressor).
Correction: Include the omitted regressor.
Regime Shift
Severity Ranking: (8/18 Total) (4/7 Moderates)
Description: Parameters change values at some point in the data set.
Implication: OLS parameter estimates are biased and (possibly) inconsistent.
Identification: Chow breakpoint or Chow forecast test.
Correction: Include dummy variable(s) to account for the regime shift.
Non-Linearity in Regressors
Severity Ranking: (9/18 Total) (5/7 Moderates)
Description: Dependent variable is a non-linear function of regressors.
Implication: OLS parameter estimates are biased and inconsistent.
Identification: Theory. Significant coefficient for the non-linear form of the regressor when both the linear
and non-linear forms are included in the regression. Box-Cox transformation.
Correction: Include non-linear form of the regressor. Box-Cox transformation.
Non-Linearity in Parameters
Severity Ranking: (10/18 Total) (6/7 Moderates)
Description: Dependent variable is a non-linear function of parameters.
Implication: OLS parameter estimates are biased and inconsistent.
Identification: Theory. Improved R2 when using non-linear least squares.
Correction: NLS
Stochastic Regressors / Measurement Error
Severity Ranking: (11/18 Total) (7/7 Moderates)
Description: One or more regressors are measured with error.
Implication: OLS parameter estimate of the stochastic regressor is biased toward zero. Estimates of the
other parameters may be biased up or down.
Identification: Theory. Hausman test. May be the result of an omitted regressor that is correlated with an
included regressor.
Correction: GMM, 2SLS. (Use two-stage residual inclusion method if stage two, but not stage one, is
non-linear.)
