Practical Regression: Discrete Dependent Variables Harvard Case Solution & Analysis

This is the ninth in a series of lecture notes which, if tied together into a textbook, might be entitled "Practical Regression." The purpose of the notes would be to supplement the theoretical content of most statistics texts with practical advice based on almost three decades of experience of the writer, combined with over one hundred years of experience of colleagues who have offered guidance. As the name "Practical Regression" implies, these notes are a guide to performing regression in practice.

This note returns to the topic of endogeneity, explaining how a predictor variable may be endogenous (and so its coefficient could be biased) if causality is in uncertainty. Through an extended instance of the learning curve in medicine, the note introduces the concept of instrumental variables (IV), provides an intuitive explanation for why instruments solve the causality problem, and clarifies the best way to estimate two and IV - stage least squares regressions. The note describes statistical tests for the validity of instruments.

Practical Regression Discrete Dependent Variables Case Study Solution


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