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An information theoretic approach to econometrics /
"This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic models and methods. Because most data are observational, practitioners work with indirect noisy observation and ill-posed econometric in the form of stochastic inverse...
| Clasificación: | Libro Electrónico |
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| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge ; New York :
Cambridge University Press,
2012.
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| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | "This book is intended to provide the reader with a firm conceptual and empirical understanding of basic information-theoretic models and methods. Because most data are observational, practitioners work with indirect noisy observation and ill-posed econometric in the form of stochastic inverse problems. Consequently, traditional econometric methods in many cases are not applicable for answering many of the quantitative questions that analysts wish to ask. After initial chapters deal with parametric and semiparametric linear probability models, the focus turns to solving nonparametric stochastic inverse problems. In succeeding chapters, a family of pwer divergence measure-likelihood functions are introduced for a range of traditional and nontraditional econometric-models problems. Finally, within either an empirical maximum likelihood or loss context, Ron C. Mittelhammer and George G. Judge suggest a basis for choosing a member of the divergence family"-- |
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| Descripción Física: | 1 online resource (xvi, 232 pages) : illustrations |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781139223980 1139223984 9781139033848 1139033840 9781139220552 1139220551 9781280568695 1280568690 1107225825 9781107225824 1139222279 9781139222273 9786613598295 6613598291 1139217461 9781139217460 1139214381 9781139214384 |