Econometric Foundations Pack with CD-ROM

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Cambridge University Press, 28.07.2000 - 756 Seiten
Econometric Foundations establishes a new paradigm for teaching econometric problems to talented upper-level undergraduates, graduate students, and professionals. The complete package (text, accompanying CD-ROM, and electronic guide) provides relevance, clarity, and organization to those wishing to acquaint themselves with the principles and procedures for information processing and recovery from samples of economic data. In the real world such data are usually limited or incomplete, and the parameters sought are unobserved and not subject to direct observation or measurement. Econometric Foundations fully provides an operational understanding of a rich set of estimation and inference tools to master such data, including traditional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjunction with the computer to address economic problems. The accompanying CD-ROM contains reviews of probability theory, principles of classical estimation and inference, and handling of ill-posed inverse problems in text-searchable electronic documents, an interactive Matrix Review manual with GAUSS LIGHT software, and an electronic Examples Manual. A separate Guide, which may be accessed through the Internet, further enhances the student's mastery of the topics by providing solutions guides to the questions and problems in the text. This text, CD-ROM, and electronic guide package make Econometric Foundations the most up-to-date and comprehensive learning resource available.
 

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Inhalt

The Process of Econometric Information Recovery
4
ProbabilityEconometric Models
14
Regression Model Estimation and Inference
33
9
48
Inference
61
Inference
105
15
115
Extremum Estimators and Nonlinear and Nonnormal
131
Simultaneous Equation Probability Models and General
403
Model Discovery
495
The Problem of Noise Covariance
528
Special Econometric Topics
561
Introduction to Nonparametric Density and Regression Analysis
599
Local Linear Regressions and Histograms
624
Bayesian Estimation and Inference
643
Alternative Bayes Formulations for the Regression Model
675

in an Extremum Estimator Context
139
Nonlinear and Nonnormal Parametric
204
Avoiding the Parametric Likelihood
223
QuasiMaximum Likelihood
245
Empirical Likelihood Estimation and Inference
281
Information TheoreticEntropy Approaches to Estimation
313
Generalized Regression Models
337
Regression Models with an Unknown General Noise
370
Bayesian Inference
698
in the Regression Model
704
Epilogue
711
Monte Carlo Simulation
719
Numerical Tools for Evaluating Posterior Distributions
730
References
736
Subject Index
743
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