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Introductory Econometrics A Modern Approach

ISBN-10: 0324289782
ISBN-13: 9780324289787
Edition: 3rd 2006
List price: $332.95
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Description: The modern approach of this text recognizes that econometrics has moved from a specialized mathematical description of economics to an applied interpretation based on empirical research techniques. It bridges the gap between the mechanics of  More...

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Book details

List price: $332.95
Edition: 3rd
Copyright year: 2006
Publisher: Cengage South-Western
Publication date: 7/13/2005
Binding: Hardcover
Pages: 912
Size: 7.25" wide x 9.25" long x 1.50" tall
Weight: 3.344
Language: English

The modern approach of this text recognizes that econometrics has moved from a specialized mathematical description of economics to an applied interpretation based on empirical research techniques. It bridges the gap between the mechanics of econometrics and modern applications of econometrics by employing a systematic approach motivated by the major problems facing applied researchers today. Throughout the text, the emphasis on examples gives a concrete reality to economic relationships and allows treatment of interesting policy questions in a realistic and accessible framework.

Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University and a Fellow of the Econometric Society.

The Nature of Econometrics and Economic Data
Regression Analysis with Cross-Sectional Data
The Simple Regression Model
Multiple Regression Analysis: Estimation
Multiple Regression Analysis: Inference
Multiple Regression Analysis: OLS Asymptotics
Multiple Regression Analysis: Further Issues
Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
Heteroskedasticity
More on Specification and Data Problems
Regression Analysis with Time Series Data
Basic Regression Analysis with Time Series Data
Further Issues in Using OLS with Time Series Data
Serial Correlation and Heteroskedasticity in Time Series Regressions
Advanced Topics
Pooling Cross Sections Across Time. Simple Panel Data Methods
Advanced Panel Data Methods
Instrumental Variables Estimation and Two Stage Least Squares
Simultaneous Equations Models
Limited Dependent Variable Models and Sample Selection Corrections
Advanced Time Series Topics
Carrying out an Empirical Project
Appendices
Basic Mathematical Tools
Fundamentals of Probability
Fundamentals of Mathematical Statistics
Summary of Matrix Algebra
The Linear Regression Model in Matrix Form
Answers to Chapter Questions
Statistical Tables
References
Glossary
Index

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