Introduction to Econometrics (2nd Edition)
Designed for a first course in introductory econometrics, Introduction to Econometrics reflects modern theory and practice, with interesting applications that motivate and match up with the theory to ensure students grasp the relevance of econometrics. Authors James H. Stock and Mark W. Watson integrate real-world questions and data into the development of the theory, with serious treatment of the substantive findings of the resulting empirical analysis.
- Real-world questions and data: All examples can be understood by students with an introductory economics background, so the instructor can focus on teaching econometrics, not microeconomics or macroeconomics.
- Contemporary choice of topics: Stock and Watson focus on the procedures and tests commonly used in modern practice. For example:
- Instrumental variables regression is presented as a general method for handling correlation between the error term and a regressor, which can arise for many reasons, including simultaneous causality. The two assumptions for a valid instrument-exogeneity and relevance-are given equal billing.
- Program evaluation (covered in Chapter 11)includes a discussion of the strengths and weaknesses of randomized controlled experiments and natural experiments as alternative approaches to the problems of omitted variables, simultaneous causality, and selection.
- Forecasting (Chapter 12)considers univariate (autoregressive) and multivariate forecasts using time series regression, not large simultaneous equation structural models.
- Time series regression coverage makes a clear distinction between two very different applications of time series regression: forecasting and estimation of dynamic causal effects.
- Theory that matches applications: This modern treatment of econometrics fits theory and applications together as tightly as possible. The three key differences that set the theoretical development of this text apart are a large sample approach that saves students time and frustration, treatment of data on all variables as the result of random sampling, and early use of heteroskedasticity rather than treating it as a problem to be solved.
- Intuitive explanations: Praised by reviewers, the text features common-sense explanations that emphasize conceptual approaches to understanding and that facilitate students’ mastery of both basic and technical topics.
- Pedagogical features: Key Concept boxes throughout the text highlight and reinforce essential ideas. General-interest sidebars provide additional interesting real-world examples closely tied to the central ideas.
- Accessible mathematics: Parts I-IV of the textbook, which cover all the core substantive material, are accessible to students with only precalculus mathematics.
- Advanced topics: Part V, on introductory econometric theory, is suitable for those teaching a more rigorous basic course and for those teaching mathematical sections of undergraduate courses or master’s level econometrics courses.
- Companion Website: Web site features include data sets, projects, software tutorials, suggested empirical exercises of differing scopes, and more.
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