9780072478525

Gujarati's Basic Econometrics provides an elementary but comprehensive introduction to econometrics without resorting to matrix algebra, calculus, or statistics beyond the elementary level. Because of the way the book is organized, it may be used at a variety of levels of rigor. For example, if matrix algebra is used, theoretical exercises may be omitted. A CD of data sets is provided with the text.

Introduction
Part I 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 2: Relaxing Assumptions of the Classical Model
10. Multicollinearity: What Happens if the Regressions 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 I: Model Specification and Diagnostic Testing?
Part 3: Topics in Econometrics
14. Nonlinear Regression Models
15. Qualitative Response Regression Models
16. Panel Data Regression Models
17. Dynamic Econometric Model: Autoregressive and Distributed Lag Models
Part 4: Simultaneous Equation Models
18. Simultaneous-Equation Models
19. The Identification Problem
20. Simultaneous-Equation Methods
Part 5: Time Series Econometrics
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 the Linear Regression Model
D. Statistical Tables
Selected Bibliography
Indexes
Name Index
Subject Index

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Basic Econometrics w/Software Disk

Basic Econometrics w/Software Disk

0072478527

Summary

Table of Contents

Part I 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 2: Relaxing Assumptions of the Classical Model

10. Multicollinearity: What Happens if the Regressions 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 I: Model Specification and Diagnostic Testing?

Part 3: Topics in Econometrics

14. Nonlinear Regression Models

15. Qualitative Response Regression Models

16. Panel Data Regression Models

17. Dynamic Econometric Model: Autoregressive and Distributed Lag Models

Part 4: Simultaneous Equation Models

18. Simultaneous-Equation Models

19. The Identification Problem

20. Simultaneous-Equation Methods

Part 5: Time Series Econometrics

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 the Linear Regression Model

D. Statistical Tables

Selected Bibliography

Indexes

Name Index

Subject Index

Supplemental Materials

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