Mastering 'Metrics: The Path from Cause to Effect

Product Information

One of the limitations of finance is that randomized trials cannot be used to answer key questions; nevertheless, focusing on how to conduct randomized trials and formulate tests is critical to doing good econometric work.

After a brief discussion of curve fitting, Pindyck and Rubinfeld’s (1976) first edition book began with subsections titled ‘The Model’, ‘Statistical Properties of Estimators’, and ‘Best Linear Unbiased Estimation’.Just like healthcare, Steve suggests there is little indication that the more you spend on education the greater the eventual benefit - however that benefit may be measured. Wooldridge, JM (2012), Introductory Econometrics: A Modern Approach, South-Western Cengage Learning. Um dos autores, Joshua (Nobel) possui um canal no youtube com o mesmo assunto e explica bem as ferramentas de inferência causal de uma forma bem lúdica.

Reading it is like overhearing a conversation between two grumpy old men who happen to be economists--and I mean this in the best way possible. apos;Metrics encompasses the statistical methods economists use to untangle cause and effect in human affairs. The ascendance of the five core econometric tools – experiments, matching and regression methods, instrumental variables, differences-in-differences and regression discontinuity designs – marks a paradigm shift in empirical economics.For decades, economics undergraduates have found jobs in sectors that make heavy use of quantitative skills. But to those who want to understand what most economists do these days and what are their methods - I think this book is a neat introduction.

Mastering 'Metrics is an engaging, fun, and highly accessible guide to the paradigm of causal inference. Take for instance - Chapters on Regression, RDD are flowing smoothly, but the chapter on IV is tighter than the others.Jorn-Steffen Pischke is professor of economics at the London School of Economics and Political Science. This valuable book connects the dots between mathematical formulas, statistical methods, and real-world policy analysis. This book should be on the shelf of anyone interested in doing applied policy work who aren't math geniuses. Even where random assignment is impractical, the notion of the experiment we’d like to run guides our choice of empirical questions and disciplines our use of non-experimental tools and data.