Probability, Statistics and Econometrics

Probability, Statistics and Econometrics

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 "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 Compact work that provides an accessible and rigorous econometrics content that is suitable for graduate courses or first semester PhD students Probability, Statistics and Econometrics provides a concise yet rigorous treatment of the field suitable for graduate students studying econometrics, very advanced undergraduate students, and researchers seeking to extend their knowledge of the trinity of fields underpinning any use of quantitative data in economic decision-making. It 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. Functions as an accessible and compact guide to the field, limiting time investment for busy researchers in a subject often considered challenging to newcomers Focused and modern coverage providing good relevant examples from economics and finance – aiding student motivation and understanding Contains some modern frontier material like bootstrap and lasso methods not treated elsewhere in similar-level books Collects the necessary material for first semester Economics PhD students into a single text About the Author 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. 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.