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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 |
|---|---|
| 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 |
Tabla de Contenidos:
- Econometric Information Recovery
- TRADITIONAL PARAMETRIC AND SEMIPARAMETRIC ECONOMETRIC MODELS: ESTIMATION AND INFERENCE
- Formulation and Analysis of Parametric and Semiparametric Linear Models
- Method of Moments, Generalized Method of Moments, and Estimating Equations
- FORMULATION AND SOLUTION OF STOCHASTIC INVERSE PROBLEMS
- A Stochastic-Empirical Likelihood Inverse Problem: Formulation and Estimation
- A Stochastic Empirical Likelihood Inverse Problem: Estimation and Inference
- Kullback-Leibler Information and the Maximum Empirical Exponential Likelihood
- A FAMILY OF MINIMUM DISCREPANCY ESTIMATORS
- The Cressie-Read Family of Divergence Measures and Empirical Maximum Likelihood Functions
- Cressie-Read-MPD-Type Estimators in Practice: Monte Carlo Evidence of Estimation and Inference Sampling Performance
- BINARY-DISCRETE CHOICE MINIMUM POWER DIVERGENCE (MPD) MEASURES
- Family of MPD Distribution Functions for the Binary Response-Choice Model
- Estimation and Inference for the Binary Response Model Based on the MPD Family of Distributions
- OPTIMAL CONVEX DIVERGENCE
- Choosing the Optimal Divergence under Quadratic Loss
- Epilogue.