Applied Microeconometrics

This is an introductory course in applied econometrics, with a strong focus on practical application rather than formal derivation. The course begins with the fundamentals of simple and multiple linear regression and then introduces key topics such as omitted variable bias, multicollinearity, and endogeneity. Emphasis is placed on developing an intuitive understanding of these concepts and on learning how to apply them in practice using real-world data. Students will learn to think critically about empirical results, assess their reliability, and understand how econometric evidence is used in economic research and policy. The course uses Stata software for data analysis, and no prior programming experience is required.

This course aims to introduce students to the basic tools of applied econometrics and to build a strong foundation in empirical economic analysis. By the end of the course, students will understand how to interpret regression results, recognize the conditions under which econometric methods are valid, and use data to answer simple economic questions. The goal is to equip students with both the intuition and technical skills necessary to critically evaluate basic empirical research and to begin conducting their own analyses.

In presence

Teaching combines lectures with applied lab sessions to develop both theoretical knowledge and hands-on skills. Lectures provide a structured and accessible introduction to econometric models, focusing on interpretation and application. These are complemented by weekly computer lab sessions, where students use Stata to work with data and apply the methods introduced in class. The labs are led by research assistants who provide support and guidance as students complete structured assignments. 

Assessment is based on a written exam, which counts for 70% of the final grade, and participation in lab sessions and the completion of Stata-based assignments, which account for the remaining 30%.