Regression is most useful for data reduction, leading to relatively simple but rich and precise descriptions of patterns in a data set. The emphasis on description provides readers with an insightful rethinking from the ground up of what regression analysis can do, so that readers can better match regression analysis with useful empirical questions and improved policy-related research. "An interesting and lively text, rich in practical wisdom, written for people who do empirical work in the social sciences and their graduate students." --David A. Freedman, Professor of Statistics, University of California, Berkeley
This book treats in a critical way one of the most frequented topics in Econometrics, Regression Analysis. This topic is built over a set of assumptions that are hardly fulfilled when we approach data. Although Richard A. Berk points out the problems with regression analysis from a theoretical point of view, the book is still relevant to address and assess the principal concerns related to the empirical application of regression methods.
Comment from our editors:
In general, econometric textbooks minimize the hard questions referring to the weaknesses of the methods they present. This book is a good treatise of the main concerns about why linear regression is not only a science but also an art.
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