Foundations of Econometric Theory

Do you need to move beyond simple correlation to understand true causal relationships in data? Econometric theory provides the rigorous statistical framework necessary to model complex economic phenomena accurately. Upon completing this course, you will understand the theoretical basis of classical linear regression, how to interpret model outputs, and how to test for common violations of assumptions. You will be equipped to select appropriate models and apply foundational econometric principles to real-world datasets. What you'll learn: * Understand the foundational assumptions and properties of the Ordinary Least Squares (OLS) estimator. * Learn to interpret regression coefficients, statistical significance, and model fit (R-squared) in economic contexts. * Practice identifying, testing for, and resolving common violations like heteroskedasticity and autocorrelation. * Apply the principles of specification testing to ensure your chosen econometric models are robust and unbiased. * Master the essential concepts of causal inference, distinguishing between correlation and true cause-and-effect relationships. This course begins with key definitions and the mathematical foundations of probability and statistics necessary for econometrics. We then systematically explore the linear regression model, moving from theoretical properties to practical diagnostic testing and model refinement. This course is designed for absolute beginners: students, analysts, and researchers starting their journey in econometrics or quantitative data analysis. No prior advanced econometric knowledge is required, only basic familiarity with algebra and statistics. Start building your rigorous foundation in economic modeling today.