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Essentials of applied econometrics / Aaron D. Smith, J. Edward Taylor.

De Gruyter University of California Press Complete eBook-Package 2016 Available online

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EBSCOhost Academic eBook Collection (North America) Available online

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Format:
Book
Author/Creator:
Smith, Aaron D., author.
Taylor, J. Edward, author.
Language:
English
Subjects (All):
Econometrics--Textbooks.
Econometrics.
Physical Description:
1 online resource (239 pages) : illustrations
Edition:
1st ed.
Place of Publication:
Oakland, California : University of California Press, 2017.
Language Note:
English
Summary:
Essentials of Applied Econometrics prepares students for a world in which more data surround us every day and in which econometric tools are put to diverse uses. Written for students in economics and for professionals interested in continuing an education in econometrics, this succinct text not only teaches best practices and state-of-the-art techniques, but uses vivid examples and data obtained from a variety of real world sources. The book's emphasis on application uniquely prepares the reader for today's econometric work, which can include analyzing causal relationships or correlations in big data to obtain useful insights.
Contents:
Frontmatter
Contents
Preface
Acknowledgments
About the Authors
1. Introduction to Econometrics
2. Simple Regression
3. Multiple Regression
4. Generalizing from a Sample
5. Properties of Our Estimators
6. Hypothesis Testing and Confi dence Intervals
7. Predicting in a Nonlinear World
8. Best of BLUE I: Cross-Section Data and Heteroskedasticity (Assumption CR2)
9. Best of Blue II: Correlated Errors (Assumption CR3)
10. Sample Selection Bias (Assumption CR1)
11. Identifying Causation
12. Instrumental Variables: A Solution to the Endogeneity Problem
Appendix: Critical Values for Commonly Used Tests in Econometrics
Notes
Index
Notes:
Includes index.
Description based on online resource; title from PDF title page (publisher's Web site, viewed 24. Apr 2020)
Description based on print version record.
ISBN:
9780520963290
0520963296
OCLC:
960758724

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