Stochastic Limit Theory: An Introduction for Econometricians

Davidson, James

ISBN 10: 0198774036 / ISBN 13: 9780198774037

Edité par Oxford University Press, Usa, 2002

A propos de cet article

This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780198774037.

N° de réf. du vendeur 9795209

Détails bibliographiques

• Titre: Stochastic Limit Theory: An Introduction for Econometricians
• Éditeur: Oxford University Press, Usa
• Date de parution: 2002
• Langue: anglais
• ISBN à 10 chiffres: 0198774036
• ISBN à 13 chiffres: 9780198774037
• Reliure: Couverture souple
• État de l'article: Good
• Poids: 900 grammes
• Catalogues du vendeur:
  • Economics

A propos de ce titre

Synopsis

This major new econometrics text surveys recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. Designed for econometricians and advanced students with limited mathematical training, the book clearly lays out the necessary math and probability theory and uses numerous examples to make its data useful and comprehensible. It also includes original new material from Davidson's own research on central limit theorems.

Présentation de l'éditeur

This is a survey of the recent developments in the rapidly expanding field of asymptotic distribution theory, with a special emphasis on the problems of time dependence and heterogeneity. The book is designed to be useful on two levels. First as a textbook and reference work, giving definitions of the relevant mathematical concepts, statements, and proofs of the important results from the probability literature, and numerous examples; and second, as an account of recent work in the field of particular interest to econometricians, including a number of important new results. It is virtually self-contained, with all but the most basic technical prerequisites being explained in their context; mathematical topics include measure theory, integration, metric spaces, and topology, with applications to random variables, and an extended treatment of conditional probability. Other subjects treated include: stochastic processes, mixing processes, martingales, mixingales, and near-epoch dependence; the weak and strong laws of large numbers; weak convergence; and central limit theorems for nonstationary and dependent processes. The functional central limit theorem and its ramifications are covered in detail, including an account of the theoretical underpinnings (the weak convergence of measures on metric spaces), Brownian motion, the multivariate invariance principle, and convergence to stochastic integrals. This material is of special relevance to the theory of cointegration.