An Introduction to Econometric Theory
Measure-Theoretic Probability and Statistics with Applications to Economics
Seiten
1997
Princeton University Press (Verlag)
978-0-691-01645-0 (ISBN)
Princeton University Press (Verlag)
978-0-691-01645-0 (ISBN)
Intended primarily to prepare first-year graduate students for their ongoing work in econometrics, economic theory, and finance, this book presents the fundamental concepts of theoretical econometrics, from measure-theoretic probability to statistics. It also features ideas and presents them as solutions to practical problems.
Intended primarily to prepare first-year graduate students for their ongoing work in econometrics, economic theory, and finance, this innovative book presents the fundamental concepts of theoretical econometrics, from measure-theoretic probability to statistics. A. Ronald Gallant covers these topics at an introductory level and develops the ideas to the point where they can be applied. He thereby provides the reader not only with a basic grasp of the key empirical tools but with sound intuition as well. In addition to covering the basic tools of empirical work in economics and finance, Gallant devotes particular attention to motivating ideas and presenting them as the solution to practical problems. For example, he presents correlation, regression, and conditional expectation as a means of obtaining the best approximation of one random variable by some function of another. He considers linear, polynomial, and unrestricted functions, and leads the reader to the notion of conditioning on a sigma-algebra as a means for finding the unrestricted solution. The reader thus gains an understanding of the relationships among linear, polynomial, and unrestricted solutions.
Proofs of results are presented when the proof itself aids understanding or when the proof technique has practical value. A major text-treatise by one of the leading scholars in this field, An Introduction to Econometric Theory will prove valuable not only to graduate students but also to all economists, statisticians, and finance professionals interested in the ideas and implications of theoretical econometrics.
Intended primarily to prepare first-year graduate students for their ongoing work in econometrics, economic theory, and finance, this innovative book presents the fundamental concepts of theoretical econometrics, from measure-theoretic probability to statistics. A. Ronald Gallant covers these topics at an introductory level and develops the ideas to the point where they can be applied. He thereby provides the reader not only with a basic grasp of the key empirical tools but with sound intuition as well. In addition to covering the basic tools of empirical work in economics and finance, Gallant devotes particular attention to motivating ideas and presenting them as the solution to practical problems. For example, he presents correlation, regression, and conditional expectation as a means of obtaining the best approximation of one random variable by some function of another. He considers linear, polynomial, and unrestricted functions, and leads the reader to the notion of conditioning on a sigma-algebra as a means for finding the unrestricted solution. The reader thus gains an understanding of the relationships among linear, polynomial, and unrestricted solutions.
Proofs of results are presented when the proof itself aids understanding or when the proof technique has practical value. A major text-treatise by one of the leading scholars in this field, An Introduction to Econometric Theory will prove valuable not only to graduate students but also to all economists, statisticians, and finance professionals interested in the ideas and implications of theoretical econometrics.
A. Ronald Gallant is Henry A. Latané Distinguished Professor of Economics at the University of North Carolina at Chapel Hill. He is a Fellow of the Econometric Society and the American Statistical Association, and a member of the Board of Directors of the National Bureau of Economic Research and the National Institute of Statistical Science. His books include Nonlinear Statistical Models. He is coeditor of the Journal of Econometrics.
PrefaceCh. 1Probability3Ch. 2Random Variables and Expectation45Ch. 3Distributions, Transformations, and Moments79Ch. 4Convergence Concepts127Ch. 5Statistical Inference147Appendix: Distributions189References197Index199
Erscheint lt. Verlag | 27.7.1997 |
---|---|
Zusatzinfo | 21 line illus. 6 tables |
Verlagsort | New Jersey |
Sprache | englisch |
Maße | 197 x 254 mm |
Gewicht | 454 g |
Themenwelt | Wirtschaft ► Allgemeines / Lexika |
Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie | |
ISBN-10 | 0-691-01645-3 / 0691016453 |
ISBN-13 | 978-0-691-01645-0 / 9780691016450 |
Zustand | Neuware |
Haben Sie eine Frage zum Produkt? |
Mehr entdecken
aus dem Bereich
aus dem Bereich
Übungsaufgaben – Fallstudien – Lösungen
Buch | Softcover (2022)
De Gruyter Oldenbourg (Verlag)
CHF 34,90
mit Aufgaben, Klausuren und Lösungen
Buch | Softcover (2023)
UTB (Verlag)
CHF 34,85
Set aus Lehr- und Arbeitsbuch
Buch | Softcover (2022)
De Gruyter Oldenbourg (Verlag)
CHF 49,95