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The goal of this course is to provide students with an introduction to key methods of quantitative policy analysis and impact evaluation used to analyze policy relevant questions in developing countries. We develop the statistical toolkit of regression analysis, reviewing the bivariate regression model and then continuing with multiple regression, and explore how these methods are applied to policy analysis in five benchmark techniques: randomized trials, direct regression analysis, instrumental variables, regression discontinuity, and difference in differences. We emphasize the distinction between regression as a statistical tool and the additional context knowledge (and occasionally assumptions) that are required to address causal policy questions. We will rely on empirical microeconomic studies (mostly in developing countries) to analyze behavior under different types of market failures and to evaluate the impacts of policy interventions. Pre-requisites: Statistics, econometrics, and microeconomics. Previous knowledge of STATA will be helpful. This course is open to enrollment by MIEF students only.