Includes index.

Introduction to econometrics -- Simple regression -- Multiple regression -- Generalizing from a sample -- Properties of our estimators -- Hypothesis testing and confidence intervals -- Predicting in a nonlinear world -- Best of blue I : cross section data and heteroskedasticity (assumption CR2) -- Best of blue II : correlated errors (assumption CR3) -- Sample selection bias (assumption CR1) -- Identifying causation -- Instrumental variables : a solution to the endogeneity problem -- Appendix : critical values for commonly used tests in econometrics.

"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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