Items related to Introductory Econometrics: Intuition, Proof And Practice
Synopsis
Zax's INTRODUCTORY ECONOMETRICS: INTUITION, PROOF, AND PRACTICE uses an innovative approach to teach regression analysis to students with a background in only introductory economics and statistics. Using basic algebra, this text focuses on learning the most important concepts of regression at an in-depth level, rather than providing more shallow coverage of a broad overview of topics. Each chapter begins with a summary of what students will learn by the end of the chapter, and follows with careful proofs and derivations that show step-by-step how the answers are reached. Students learn the intuition behind regression analysis by moving carefully through covariance and correlations, from sample to population, confidence intervals, inference in OLS, and finally violations of the standard assumptions. The benefit to this approach is a clear and complete understanding of regression analysis that will enable the student to continue his or her studies in econometrics, or go on to a career with a solid foundation in running regressions and interpreting results.
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About the Author
Jeffrey Zax is a professor of Economics at the University of Colorado at Boulder. He received his undergraduate and PhD degrees from Harvard University. While at Harvard he studied under Olivier Blanchard, a well-known and accomplished economist, the current Department Chair at MIT, and the author of an Intermediate Macroeconomics text. Jeffrey Zax is well regarded as an excellent teacher and has long used the innovations presented in his text in his econometrics course at the University of Colorado, Boulder.
Review
"I like the emphasis on intuition. Particular strengths of this work include: accessible definitions, unique demonstrations of core ideas, novel examples to illustrate technical concepts, and a strong presentation of asymptotic theory and instrumental variables using simulations in place of formal derivations."
Jeff Desimone, University of Texas at Arlington and NBER
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