AlibomicsMoney and Economics
CONCEPT LESSON

Omitted variable bias

Bias in a regression coefficient when an omitted relevant factor is correlated with an included explanatory variable.

Why it matters

An apparent relationship can partly reflect an unmeasured factor. Identifying which relevant factors also relate to the explanatory variable is crucial for interpretation.

A worked example

A wage–education regression that omits a relevant ability measure can attribute some associated differences to education if ability also relates to education.

Illustrative example · simplified assumptions

A common mistake

Adding any available variable and assuming the causal problem is solved.

Where the idea needs care

An omitted variable does not always create bias in every coefficient; the relationship to included variables matters.

Apply the idea

Explain this concept using a different example from your spending, work, business or a policy debate. State what stays fixed and what could change the result.

CHECK YOUR UNDERSTANDING
Which missing factor can bias the education coefficient?

Read the answer and explanation

One related to wages and correlated with education. An omitted variable does not always create bias in every coefficient; the relationship to included variables matters.

Sources and further study

Examples and explanations by Alibomics. Numeric illustrations are not current market quotations.