Omitted variables bias (or sometimes omitted variable bias) is a standard expression for the bias that appears in an estimate of a parameter if the regression run does not have the appropriate form and data for other parameters. For example, many regressions that have wage or income as the dependent variable suffer from omitted variables bias because there is often no practical way to add in a worker's innate ability or motivation as an explanatory variable. As a result, the estimated coefficients on variables such as education as likely to be biased because of the correlation between educational attainment and unobserved ability. If the correlation between education and unobserved ability is positive, omitted variables bias will occur in an upward direction. Conversely, if the correlation between an explanatory variable and an unobserved relevant variable is negative, omitted variables bias will occur in a downward direction.

Treatment Effects in Economics

Linear Regression and Multiple Linear Regression Analysis

Definition and Use of Instrumental Variables in Econometrics

What Is Ecological Correlation?

The Differences Between Explanatory and Response Variables

Correlation Analysis: Comparing Variables

What You Should Know About Econometrics

In Pictures: Understanding Stratification by Class, Education, Gender, and Race

The Importance of Exclusion Restrictions in Instrumental Variables

What Is a Scatterplot and How Is It Used in Statistics?

Spurious  Why You Need to Know What It Means

What a Controlled Variable Is and Why It's Important

What Are Residuals?

What Does Implicit Bias Really Mean?

The Slope of the Regression Line and the Correlation Coefficient

How Intervening Variables Work in Sociology