Probability, Statistics and Econometrics

ISBN-13: 9780128104958 / Angielski / Miękka / 2017 / 388 str.

Oliver Linton

Opis

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

Recenzje

"This book provides a concise treatment of the three fields mentioned in the title, containing the essential notions and results in these areas. Almost all definitions and important theorems in the book are followed by relevant examples and valuable comments. Although most of the theorems and propositions in the book are presented without a proof, in some of the cases a proof is provided. The book is suitable for advanced under- graduate students or graduate students studying econometrics, as well as for researchers in finance and economics seeking to extend their knowledge in these three fields." --Mathematical Reviews Clippings

Spis treści

Part I: Probability and Distribution1. Probability Theory2. Conditional Probability and Independence3. Random Variables, Distribution Functions, and Densities4. Transformations of Random Variables5. The Expectation6. Examples of Univariate Distributions7. Multivariate Random Variables8. Asymptotic Theory9. Exercises and Complements

Part II: Statistics10. Introduction11. Estimation Theory12. Hypothesis Testing13. Confidence Intervals and Sets14. Asymptotic Tests and the Bootstrap15. Exercises and Complements

Part III: Econometrics 16. Linear Algebra17. The Least Squares Procedure18. Linear Model19. Statistical Properties of the OLS Estimator20. Hypothesis Testing for Linear Regression21. Omission of Relevant Variables, Inclusion of Irrelevant Variables, and Model Selection 22. Asymptotic Properties of OLS Estimator and Test Statistics23. Generalized Method of Moments and Extremum Estimators24. A Nonparametric Postscript25. A Case Study26. Exercises and Complements

Appendix A. Some Results from Calculus Appendix B. Some Matrix Facts

O autorze

Professor Oliver Linton (Professor of Political Economy, Trinity College, Cambridge University) has been a Co-editor of Econometric Theory since 2000, the Journal of Econometrics since 2014, was Co-Editor of Econometrics Journal from 2007-14. He is an Elected Fellow of the Econometric Society, the Institute of Mathematical Statistics, and the British Academy. He has published over 130 articles in statistics, econometrics, and in empirical finance. He is particularly interested in nonparametric and semiparametric methods and financial econometrics.