Econometrics and Empirical Analysis
Read each chapter, then work through auto-marked multiple-choice and numerical questions — plus written answers with instant feedback against the author's model solutions.
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Regression is the workhorse of empirical research — and the easiest tool in the kit to use badly. Econometrics and Empirical Analysis is a practical course in doing regression analysis properly: what the models assume, how to tell when those assumptions fail, and how to move, carefully, from correlation to causation.
The book opens with OLS regression from first principles — the assumptions, the derivation of the estimator, hypothesis testing, and how to read real regression output — before turning to the things that go wrong in practice: heteroscedasticity, multicollinearity, omitted variables, outliers, and how to detect and fix each one. From there it covers binary and discrete choice models (logit, probit, multinomial and ordered outcomes), panel data (fixed effects, random effects, and Fama-MacBeth), and the modern causal-inference toolkit: instrumental variables and 2SLS, difference-in-difference, and regression discontinuity designs. Two applied chapters put the methods to work where empirical finance actually uses them — estimating CAPM betas and factor models, and running event studies. Every technique is developed through worked examples with real regression output, not abstraction.
What the online companion includes
- The complete text, readable online on any device — with every equation properly typeset. Chapter 1 is free, no account required.
- A practice bank of nearly 400 questions written and verified from the book itself: multiple choice, true/false, and numerical problems that mark themselves instantly, with the full worked solution shown on every correct answer.
- Written-answer practice with instant feedback — write your response and get point-by-point marking against the author's model solutions.
- Progress tracking across every chapter, so you always know what's mastered and what needs another pass.
Written for university courses in econometrics and empirical methods, for research students facing their first serious regressions, and for practitioners in finance and economics who need to read — and challenge — empirical results. Also available in print and Kindle editions.