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Econometric Analysis of Stochastic Dominance: Concepts, Methods, Tools, and Applications: Themes in Modern Econometrics

Autor Yoon-Jae Whang
en Limba Engleză Hardback – 30 ian 2019
This book offers an up-to-date, comprehensive coverage of stochastic dominance and its related concepts in a unified framework. A method for ordering probability distributions, stochastic dominance has grown in importance recently as a way to measure comparisons in welfare economics, inequality studies, health economics, insurance wages, and trade patterns. Whang pays particular attention to inferential methods and applications, citing and summarizing various empirical studies in order to relate the econometric methods with real applications and using computer codes to enable the practical implementation of these methods. Intuitive explanations throughout the book ensure that readers understand the basic technical tools of stochastic dominance.
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Specificații

ISBN-13: 9781108472791
ISBN-10: 1108472796
Pagini: 278
Ilustrații: 11 b/w illus. 5 tables
Dimensiuni: 157 x 235 x 20 mm
Greutate: 0.5 kg
Editura: Cambridge University Press
Colecția Cambridge University Press
Seria Themes in Modern Econometrics

Locul publicării:New York, United States

Cuprins

1. Introduction; 1.1. Concepts of stochastic dominance; 1.2. Applications of stochastic dominance; 1.3. Outline of subsequent chapters; 2. Tests of stochastic dominance: basic results; 2.1. Introduction; 2.2. Null of dominance against non-dominance; 2.3. Null of non-dominance against dominance; 2.4. Null of equality against dominance; 2.5. Empirical examples; 3. Tests of stochastic dominance: further results; 3.1. SD tests with improved power; 3.2. Program evaluation and stochastic dominance; 3.3. Some issues of SD tests; 3.4. Empirical examples; 4. Stochastic dominance with covariates; 4.1. Introduction; 4.2. Conditional stochastic dominance at fixed values of covariates; 4.3. Conditional stochastic dominance at all values of covariates; 4.4. Stochastic monotonicity; 4.5. Empirical examples; 5. Extensions of stochastic dominance; 5.1. Multivariate stochastic dominance; 5.2. Analysis of economic inequality and poverty; 5.3. Analysis of portfolio choice problems; 5.4. Weaker notions of stochastic dominance; 5.5. Related concepts of stochastic dominance; 6. Some further topics; 6.1. Distributional overlap measure; 6.2. Generalized functional inequalities; 6.3. Distributions with measurement errors; 6.4. SD tests with many covariates; 6.5. Robust forecasting comparisons; 7. Conclusions.

Notă biografică


Descriere

Provides a comprehensive analysis of stochastic dominance through coverage of concepts, methods of estimation, inferential tools, and applications.