Greene William. Econometric analisys

This book has two objectives. The first is to introduce students to applied econometrics,
including basic techniques in regression analysis and some of the rich variety
of models that are used when the linear model proves inadequate or inappropriate.
The second is to present students with sufficient theoretical background that they will
recognize new variants of the models leaed about here as merely natural extensions
that fit within a common body of principles.

Contents:
Chapter 1 Introduction
Chapter 2 The Classical Multiple Linear Regression Model
Chapter 3 Least Squares
Chapter 4 Finite-Sample Properties of the Least Squares Estimator
Chapter 5 Large-Sample Properties of the Least Squares and Instrumental
Variables Estimators
Chapter 6 Inference and Prediction
Chapter 7 Functional Form and Structural Change
Chapter 8 Specification Analysis and Model Selection
Chapter 9 Nonlinear Regression Models
Chapter 10 Nonspherical Disturbances—The Generalized
Regression Model
Chapter 11 Heteroscedasticity
Chapter 12 Serial Correlation
Chapter 13 Models for Panel Data
Chapter 14 Systems of Regression Equations
Chapter 15 Simultaneous-Equations Models
Chapter 16 Estimation Frameworks in Econometrics
Chapter 17 Maximum Likelihood Estimation
Chapter 18 The Generalized Method of Moments
Chapter 19 Models with Lagged Variables
Chapter 20 Time-Series Models
Chapter 21 Models for Discrete Choice
Chapter 22 Limited Dependent Variable and Duration Models