This book unifies econometric theory, estimation, and interpretation into a coherent workflow for turning economic questions into testable, evidence-based claims. It develops linear regression from simple to multiple models, establishing OLS, Gauss–Markov conditions, finite-sample t/F tests, and asymptotic reasoning. Readers learn to detect and correct violations—heteroskedasticity, serial correlation, multicollinearity, functional misspecification—using robust, clustered, and HAC variance estimators with specification diagnostics. Worked examples, data-driven case studies. Aimed at advanced undergraduates, master’s and PhD students, and policy/industry practitioners, it equips readers to deliver credible, policy-relevant empirical analyses
Chapter 1: Concepts and Data in Econometrics
Chapter 2: The Simple Linear Regression Model
Chapter 3: The Multiple Regression Model
Chapter 4: Violations of the Classical Assumptions
Chapter 5: Time‑Series Econometrics
Chapter 6: Interpreting Econometric Results
Chapter 7: Review and Extensions in Econometrics