Omitted-variable bias

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Omitted-variable bias (OVB) is the bias that appears in estimates of parameters in a regression when the assumed functional form is incorrect, in that it omits an independent variable that belongs in the true model.

[edit] Omitted-variable bias in linear regression

Two conditions must hold true for omitted variable bias to exist in linear regression:

• the omitted variable must be a determinant of the dependent variable (i.e. its true regression coefficient is not zero); and
• the omitted variable must be correlated with one or more of the included independent variables.

When omitted variable bias occurs, least squares estimators (at least the ones for the variables that were correlated with the omitted variable) become biased and inconsistent.