Bridging the gap between applied economists and theoretical nonparametric econometricians, this book explains basic to advanced nonparametric methods with applications.
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Daniel J. Henderson is the J. Weldon and Delores Cole Faculty Fellow at the University of Alabama, as well as a research fellow at the Institute for the Study of Labor (IZA) in Bonn, Germany, and at the Wang Yanan Institute for Studies in Economics, Xiamen University, in Xiamen, China. He was formerly an associate and Assistant Professor of Economics at the State University of New York at Binghamton. He has held visiting appointments at the Institute of Statistics, Université catholique de Louvain, in Louvain-la-Neuve, Belgium, and in the Department of Economics at Southern Methodist University in Dallas, Texas. He received his PhD in economics from the University of California, Riverside. His work has been published in journals such as the Economic Journal, the European Economic Review, the International Economic Review, the Journal of Applied Econometrics, the Journal of Econometrics, the Journal of Human Resources, the Journal of the Royal Statistical Society, and the Review of Economics and Statistics.
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Zustand: New. Bridging the gap between applied economists and theoretical nonparametric econometricians, this book explains basic to advanced nonparametric methods with applications. Num Pages: 378 pages, 81 b/w illus. 34 tables. BIC Classification: KCG; KCHS. Category: (U) Tertiary Education (US: College). Dimension: 256 x 180 x 21. Weight in Grams: 682. . 2015. 1st. Paperback. . . . . Books ship from the US and Ireland. Artikel-Nr. V9780521279680
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls. Artikel-Nr. 9780521279680
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