Introduction to econometrics - Stock, James H.; Watson, Mark W. (Pearson series in economics, 2020)
"Designed for a first course in undergraduate and introductory econometrics, this text reflects modern theory and practice. With riveting empirical applications as well as real-world examples and data integrated into the development of the theory, the authors ensure that students grasp the relevance of econometrics by providing an effective treatment of the substantive findings of the resulting empirical analysis. New to this edition : Chapter on "Big Data" and machine learning methods ; Parallel treatment of prediction and causal inference using regression ; Brand new general interest boxes, like "The distribution of adulthood earnings in the United Kingdom by Childhood Socioeconomic Circumstances" and "Conditional cash transfers in Rural Mexico to increase school enrollment," that focus on contemporary and global choice of topics ; Coverage of realized volatility as well as autoregressive conditional heteroskedasticity ; Concept exercises in MyLab that focus on core concepts and economic interpretations." -- Back cover