Econometrics

Econometrics applies statistical and mathematical methods to economic data to estimate relationships, test economic theories, and produce forecasts.

Regression analysis: A statistical method for estimating relationships between an outcome and one or more explanatory variables. Regression is a central tool for quantifying economic relationships.
Probability theory: The mathematical study of random events and the distributions governing them. Econometric inference uses probability to describe sampling uncertainty.
Program evaluation: The systematic assessment of a policy or intervention's effects and implementation. Econometric methods estimate whether public programs changed outcomes.
Descriptive statistics: Methods for summarizing and presenting observed data without necessarily generalizing beyond them. Econometric analysis goes beyond summaries to estimate relationships and test claims.
Ragnar Frisch: A Norwegian economist and statistician who helped establish econometrics as a discipline. Frisch helped define the field and introduced the term econometrics.
Causal inference: The study of methods for identifying cause-and-effect relationships from data. Econometric designs seek causal effects, not merely statistical associations.
Statistical inference: Methods for drawing conclusions about populations from observed samples. Econometrics adapts inference methods to questions about economic parameters.
Randomized controlled trial: An experiment that assigns participants randomly to treatment and comparison groups. Random assignment provides a benchmark for measuring causal economic effects.
Experimental economics: The use of controlled experiments to study economic behavior and institutions. Experiments generate evidence through designed interventions, unlike much observational econometrics.
Jan Tinbergen: A Dutch economist who built quantitative models of economic dynamics and policy. Tinbergen's empirical models helped make econometrics a tool for analyzing economic policy.

Linked from 17 pages