
- 388 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Probability, Statistics and Econometrics
About this book
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.- Synthesizes three substantial areas of research, ensuring success in a subject matter than can be challenging to newcomers- Focused and modern coverage that provides relevant examples from economics and finance- Contains some modern frontier material, including bootstrap and lasso methods not treated in similar-level books- Collects the necessary material for first semester Economics PhD students into a single text
Frequently asked questions
- Essential is ideal for learners and professionals who enjoy exploring a wide range of subjects. Access the Essential Library with 800,000+ trusted titles and best-sellers across business, personal growth, and the humanities. Includes unlimited reading time and Standard Read Aloud voice.
- Complete: Perfect for advanced learners and researchers needing full, unrestricted access. Unlock 1.4M+ books across hundreds of subjects, including academic and specialized titles. The Complete Plan also includes advanced features like Premium Read Aloud and Research Assistant.
Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Information
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of Figures
- About the Author
- Preface
- Acknowledgment
- 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