Gujarati, Damodar N.

Basic econometrics - 6th ed. - New Delhi McGraw Hill 2009 - 910p.

Preface
Acknowledgments

Introduction

PART ONE
Single-Equation Regression Models

1 The Nature of Regression Analysis
2 Two-Variable Regression Analysis: Some Basic Ideas
3 Two-Variable Regression Model: The Problem of Estimation
4 Classical Normal Linear Regression Model (CNLRM)
5 Two-Variable Regression: Interval Estimation and Hypothesis Testing
6 Extensions of the Two-Variable Linear Regression Model
7 Multiple Regression Analysis: The Problem of Estimation
8 Multiple Regression Analysis: The Problem of Inference
9 Dummy Variable Regression Models

PART TWO
Relaxing the Assumptions of the Classical Model

10 Multicollinearity: What Happens If the Regressors Are Correlated?
11 Heteroscedasticity: What Happens If the Error Variance Is Nonconstant?
12 Autocorrelation: What Happens If the Error Terms Are Correlated?
13 Econometric Modeling: Model Specification and Diagnostic Testing

PART THREE
Topics in Econometrics

14 Nonlinear Regression Models
15 Qualitative Response Regression Models
16 Panel Data Regression Models
17 Dynamic Econometric Models: Autoregressive and Distributed-Lag Models

PART FOUR
Simultaneous-Equation Models

18 Simultaneous-Equation Models
19 The Identification Problem
20 Simultaneous-Equation Methods
21 Time Series Econometrics: Some Basic Concepts
22 Time Series Econometrics: Forecasting

APPENDIXES

A A Review of Some Statistical Concepts
B Rudiments of Matrix Algebra
C The Matrix Approach to Linear Regression Model
D Statistical Tables
E Computer Output of EViews, MINITAB, Excel, and STATA
F Economic Data on the World Wide Web

SELECTED BIBLIOGRAPHY

9789390219292


Econometrics

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