Introductory Econometrics A Modern Approach

ISBN-10: 0324581629

ISBN-13: 9780324581621

Edition: 4th 2009

List price: $374.95
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Practical and professional, Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 4e bridges the gap between how undergraduate econometrics has traditionally been taught and how empirical researchers actually think about and apply econometric methods. The text's unique approach reflects the fact that econometrics has moved from a specialized mathematical description of economics to an applied interpretation based on empirical research techniques. The text combines the mechanics of econometrics with modern applications of econometrics by employing a systematic approach motivated by the major problems facing applied researchers today. Unlike traditional texts, INTRODUCTORY ECONOMETRICS's unique organization separates topics by the kinds of data being analyzed, rather than presenting a strictly linear model. Packed with relevant applications and a wealth of interesting data sets, the text emphasizes examples throughout, which gives a concrete reality to economic relationships, as well as allows treatment of intriguing policy questions in a realistic and accessible framework.
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Book details

List price: $374.95
Edition: 4th
Copyright year: 2009
Publisher: Cengage South-Western
Publication date: 3/27/2008
Binding: Hardcover
Pages: 896
Size: 7.50" wide x 9.50" long x 1.25" tall
Weight: 3.432
Language: English

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
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
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
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