Glossary
Econometrics terms
Short definitions for the core vocabulary used across the first two modules.
- Causality
- A cause-and-effect relationship where changing one factor changes another.
- Ceteris paribus
- All else equal; comparing one factor while holding other relevant factors fixed.
- Coefficient
- An estimated number multiplying a variable in a regression equation.
- Cross-sectional data
- Data on many units observed at one point in time.
- Dependent variable
- The outcome variable the model is trying to explain.
- Econometrics
- The use of data and statistical methods to study economic relationships.
- Error term
- The part of the outcome not explained by the variables included in the model.
- Explanatory variable
- The variable used to describe or predict the dependent variable.
- Fitted value
- The predicted value from an estimated regression equation.
- Heteroskedasticity
- A condition where the error variance changes across values of the explanatory variable.
- Homoskedasticity
- A condition where the error variance is constant across values of the explanatory variable.
- Independent variable
- A variable used to explain or predict the dependent variable.
- Intercept
- The predicted value of the dependent variable when the explanatory variable equals zero.
- OLS
- Ordinary Least Squares, the method that minimizes the sum of squared residuals.
- p-value
- A measure used to judge evidence against a null hypothesis.
- Panel data
- Data that follow the same units across multiple time periods.
- Pooled cross section
- Separate cross-sectional samples combined across multiple time periods.
- PRF
- Population regression function, the average relationship in the full population.
- R-squared
- The share of total variation in the dependent variable explained by the regression.
- Regression
- A statistical method for estimating relationships between a dependent variable and one or more independent variables.
- Residual
- The difference between the observed value and the fitted value.
- Simple regression
- A regression model with one dependent variable and one explanatory variable.
- Slope
- The predicted change in the dependent variable for a one-unit increase in the explanatory variable.
- SRF
- Sample regression function, the fitted relationship estimated from sample data.
- SSR
- Residual sum of squares, the sum of squared residuals left unexplained by the model.
- Standard error
- A measure of sampling uncertainty around an estimated coefficient.
- t-statistic
- A coefficient estimate divided by its standard error.
- Time-series data
- Data on one unit or variable observed across multiple time periods.