Part I: Probability and Distribution
Chapter 1 - Probability Theory,
Chapter 2 - Conditional Probability and Independence,
Chapter 3 - Random Variables, Distribution Functions, and Densities,
Chapter 4 - Transformations of Random Variables,
Chapter 5 - The Expectation,
Chapter 6 - Examples of Univariate Distributions,
Chapter 7 - Multivariate Random Variables,
Chapter 8 - Asymptotic Theory,
Chapter 9 - Exercises and Complements,
Part II: Statistics
Chapter 10 - Introduction,
Chapter 11 - Estimation Theory,
Chapter 12 - Hypothesis Testing,
Chapter 13 - Confidence Intervals and Sets,
Chapter 14 - Asymptotic Tests and the Bootstrap,
Chapter 15 - Exercises and Complements,
Part III: Econometrics
Chapter 16 - Linear Algebra,
Chapter 17 - The Least Squares Procedure,
Chapter 18 - Linear Model,
Chapter 19 - Statistical Properties of the OLS Estimator,
Chapter 20 - Hypothesis Testing for Linear Regression,
Chapter 21 - Omission of Relevant Variables, Inclusion of Irrelevant Variables, and Model Selection,
Chapter 22 - Asymptotic Properties of OLS Estimator and Test Statistics,
Chapter 23 - Generalized Method of Moments and Extremum Estimators,
Chapter 24 - A Nonparametric Postscript,
Chapter 25 - A Case Study,
Chapter 26 - Exercises and Complements,
Appendix,
Bibliography,
Index.

Probability, Statistics and Econometrics provides a concise, yet rigorous, treatment of the field that is suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of the trinity of fields that use quantitative data in economic decision-making. The book covers much of the groundwork for probability and inference before proceeding to core topics in econometrics. Authored by one of the leading econometricians in the field, it is a unique and valuable addition to the current repertoire of econometrics textbooks and reference books. -- Provided by publisher.