An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R

ISBN-13: 9781108483407 / Angielski / Twarda / 2019 / 434 str.

Ontario) Racine Jeffrey S. (McMaster University

Opis

This book provides theory, open source R implementations, and the latest tools for reproducible nonparametric econometric research. Advanced undergraduate students, graduate students, and faculty wishing to keep abreast of this field will find this resource more accessible than similar books.

Recenzje

'This book manages to be comprehensive, careful, and accessible all at once - an impressive achievement for such a challenging subject. It covers topics not found elsewhere and incorporates them in a systematic, unified approach. Illustrations using the R programming language will have broad appeal for both teachers and users of nonparametric methods.' Jeffrey M. Woolridge, Michigan State University

Spis treści

Part I. Probability Functions, Probability Density Functions, and their Cumulative Counterparts: 1. Discrete probability and cumulative probability functions; 2. Continuous density and cumulative distribution functions; 3. Mixed-data probability density and cumulative distribution functions; 4. Conditional probability density and cumulative distribution functions; Part II. Conditional Moment Functions and Related Statistical Objects: 5. Conditional moment functions; 6. Conditional mean function estimation; 7. Conditional mean function estimation with endogenous predictors; 8. Semiparametric conditional mean function estimation; 9. Conditional variance function estimation; Part III. Appendices: A. Large and small orders of magnitude and probability; B. R, RStudio, TeX and Git; C. Computational considerations; D. R Markdown for assignments; E. Practicum.