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Disponibilidad: En existencia
ISBN: 9781292014005
Precio sin IVA:
$ 132.300,00

Edición: 7
Copyright: 2015
Páginas: 560

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Econometric Analysis: International Edition (ebook)

By William H. Greene


This text has two objectives that are intended to help students bridge the gap between the field of econometrics and the professional literature for graduate students in social sciences:

  1. To introduce students to applied econometrics
  2. To present students with sufficient theoretical background so they will recognise new variants of the models learned about here as natural extensions of common principles.

The arrangement of this text begins with formal presentation of the development of the fundamental pillar of econometrics.  Some highlights include:


  • The classical linear regression model; Chapters 1-7
  • The generalised regression model and non-linear regressions; Chapters 8-11
  • Instrumental variables and its application to the estimation of simultaneous equations models; Chapters 12 and 13
  • Matrix Algebra — This text makes heavy use of this feature. All the matrix algebra needed in the text contains a description of numerical methods that will be useful to practicing econometricians.

Part I: The Linear Regression Model
Chapter 1: Econometrics
Chapter 2: The Linear Regression Model
Chapter 3: Least Squares
Chapter 4: The Least Squares Estimator
Chapter 5: Hypothesis Tests and Model Selection
Chapter 6: Functional Form and Structural Change
Chapter 7: Nonlinear, Semiparametric, and Nonparametric Regression Models
Chapter 8: Endogeneity and Instrumental Variable Estimation

Part II: Generalized Regression Model and Equation Systems
Chapter 9: The Generalized Regression Model and Heteroscedasticity
Chapter 10: Systems of Equations
Chapter 11: Models for Panel Data

Part III: Estimation Methodology
Chapter 12: Estimation Frameworks in Econometrics
Chapter 13: Minimum Distance Estimation and the Generalized Method of Moments
Chapter 14: Maximum Likelihood Estimation
Chapter 15: Simulation-Based Estimation and Inference
Chapter 16: Bayesian Estimation and Inference

Part IV: Cross Sections, Panel Data, and Microeconometrics
Chapter 17: Discrete Choice
Chapter 18: Discrete Choices and Event Counts
Chapter 19: Limited Dependent Variables—Truncation, Censoring, and Sample Selection

Part V: Time Series and Macroeconometrics
Chapter 20: Serial Correlation
Chapter 21: Models with Lagged Variables
Chapter 22: Time-Series Models
Chapter 23: Nonstationary Data