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

By: Contributor(s): Material type: TextTextPublication details: Oakland, California : University of California Press, 2017.Description: xi, 225 pages : illustrations, charts ; 24 cmISBN:
  • 9780520288331 (pbk. : alk. paper)
Subject(s): Additional physical formats: Online version:: Essentials of applied econometricsDDC classification:
  • 330.01/5195 23
Summary: "Essentials of Applied Econometrics gives students and professionals the tools they need to do econometric analysis in a world in which more data surround us every day and in which econometrics is put to a diversity of uses. Vivid examples and data from a variety of real-world sources are used to teach best practices and state-of-the-art techniques. This book differs from traditional textbooks that assume the only goal of econometrics is to estimate causal effects and that confound sampling theory with causal analysis. It begins with sampling theory - how to use a sample to make inferences about a whole population. Then, in the last two chapters, it addresses causality as a distinct topic. In between, it covers the gambit of topics essential for doing econometrics, including properties of estimators, hypothesis testing, nonlinear relationships, heteroskedasticity, serial correlation, and sampling bias. This book covers essential theory but with an emphasis on the best practices for estimating econometric models. The text is succinct, written for students and professionals interested in continuing their econometric education"--Provided by publisher.
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Includes index.

"Essentials of Applied Econometrics gives students and professionals the tools they need to do econometric analysis in a world in which more data surround us every day and in which econometrics is put to a diversity of uses. Vivid examples and data from a variety of real-world sources are used to teach best practices and state-of-the-art techniques. This book differs from traditional textbooks that assume the only goal of econometrics is to estimate causal effects and that confound sampling theory with causal analysis. It begins with sampling theory - how to use a sample to make inferences about a whole population. Then, in the last two chapters, it addresses causality as a distinct topic. In between, it covers the gambit of topics essential for doing econometrics, including properties of estimators, hypothesis testing, nonlinear relationships, heteroskedasticity, serial correlation, and sampling bias. This book covers essential theory but with an emphasis on the best practices for estimating econometric models. The text is succinct, written for students and professionals interested in continuing their econometric education"--Provided by publisher.

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