Introductory Econometrics: A Modern Approach
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.
Unique Features Logical Progression: This text focuses first on multiple regression then leads in a straightforward manner to more advanced methods, such as simple panel data analysis and instrumental variables estimation. Time Series/Cross-Section Analysis Flexibility:Time series and cross section analysis are not treated concurrently, but in a way that one can jump to time series analysis after covering the basics of regression with cross-section data. In-Depth Data Coverage: Panel data methods and other new models are covered in greater detail than in other texts. Meaningful Examples: This edition emphasizes examples intended to infer causality Empirical Focus: Recent empirical literature motivates the discussion of topics. A Foundation for Social Science Research: This text provides students with important knowledge used for empirical work and carrying out research projects in a variety of applied social science fields, some outside of economics (e.g. political science, criminology, etc.). Extensive, Up-to-Date Data Sets: More than 60 data sets, many of which come from very recent studies, accompany the text and are used in numerous examples and computer exercises. New Features Chapter 19 provides expanded coverage on guiding the students through empirical projects. The chapter now offers more examples and updated tips on writing a term paper with an expanded list of suggested topics. Added material to the appendix in chapter 3 will include new insights on the omitted variable problems with clearer descriptions. Empirical examples have been updated using the most recent data. End-of-chapter problems include new exercises using data sets.
All the data sets are now available in a variety of formats: ASCII, Eviews, Excel,
Stata, and Minitab. These files are available on the Website.
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- 1. The Nature of Econometrics and Economic Data
PART I:. REGRESSION ANALYSIS WITH CROSS SECTION DATA
- 2. The Simple Regression Model
3. Multiple Regression Analysis: Estimation
4. Multiple Regression Analysis: Inference
5. Multiple Regression Analysis: OLS Asymptotics
6. Multiple Regression Analysis: Further Issues
7. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
8. Heteroskedasticity
9. More on Specification and Data Problems
PART II: REGRESSION ANALYSIS WITH TIME SERIES DATA
- 10. Basic Regression Analysis with Time Series Data
11. Further Issues in Using OLS with Time Series Data
12. Serial Correlation and Heteroskedasticity in Time Series Regressions
PART III: ADVANCED TOPICS
- 13. Polling Cross Sections Across Time: Simple Panel Data Methods
14. Advanced Panel Data Methods
15. Instrumental Variables Estimation and Two State Least Squares
16. Introduction to Simultaneous Equations Models
17. Limited Dependent Variable Models and Sample Selection Corrections
18. Advanced Time Series Topics
19. Carrying Out an Empirical Project
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