- 274 pages
- English
- PDF
- Available on iOS & Android
Foundations of Econometrics
About this book
Advanced Textbooks in Economics, Volume 7: Foundations of Econometrics focuses on the principles, processes, methodologies, and approaches involved in the study of econometrics. The publication examines matrix theory and multivariate statistical analysis. Discussions focus on the maximum likelihood estimation of multivariate normal distribution parameters, point estimation theory, multivariate normal distribution, multivariate probability distributions, Euclidean spaces and linear transformations, orthogonal transformations and symmetric matrices, and determinants. The manuscript then ponders on linear expected value models and simultaneous equation estimation. Topics include random exogenous variables, maximum likelihood estimation of a single equation, identification of a single equation, linear stochastic difference equations, and errors-in-variables models. The book takes a look at a prolegomenon to econometric model building, tests of hypotheses in econometric models, multivariate statistical analysis, and simultaneous equation estimation. Concerns include maximum likelihood estimation of a single equation, tests of linear hypotheses, testing for independence, and causality in economic models. The publication is a valuable source of data for economists and researchers interested in the foundations of econometrics.
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Table of contents
- Front Cover
- Foundations of Econometrics
- Copyright Page
- Table of Contents
- Preface
- Chapter 1. Matrix theory
- Chapter 2. Multivariate statistical analysis: Distribution and point estimation theory
- Chapter 3. Linear expected value models
- Chapter 4. Simultaneous equation estimation
- Chapter 5. Multivariate statistical analysis: Hypothesis testing theory
- Chapter 6. Tests of hypotheses in econometric models
- Chapter 7. A prolegomenon to econometric model building
- Index