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KOUT 2055 - Applied Econometrics with Stata - Advanced

Type d'enseignement : Seminar

Semester : Autumn 2018-2019

Number of hours : 24

Language of tuition : English


An introductory undergraduate module in calculus and in probability and statistics.

Course Description

The course covers the basics aspects of econometric analysis of real data with a focus on policy implications. There are two modules available: a beginners module for students new to econometrics and an advanced module for students with a more quantitative. The topics covered are mainly the same in each module but covered with a different level of complexity. Throughout the course some real data examples are studied and a comparison of the different econometric techniques presented is made. These are examples relevant for education and health public sectors, for social policies, and for monetary policies. As potential consequences of these analysis there are effects on fiscal policies, on citizens security and welfare, and on consumers', investors' and government's behavior. We consider different type of data that an econometrician has to be able to handle: cross-sectional, longitudinal and, only for the advanced course, time series. For each type the appropriate models are presented and discussed with a focus on interpretation of results and on estimation. For the advanced module derivation of some asymptotic results is also covered. The regression models considered are: linear, non-linear, panel data, limited dependent variable, instrumental variable, and auto-regressions (only for the advanced course). Basic concepts of probability and statistics will be covered during the first weeks of the course. Each lecture is followed by an applied computer session based on Stata where students learn to implement the techniques presented. This course description is thus valid for both the Econometrics Lectures (OAEA2080) and the Applied Econometrics with Stata classes (KOUT2050/KOUT2055). The main objectives of the course are to teach students to be able to: to conduct empirical research, i.e. to interpret the information extracted from the data in a critical way ; to identify economic policy problems that can benefit of quantitative analysis ; to identify the appropriate method of analysis depending on the data at hand ; to run statistical tests of hypothesis on real world data and to interpret the results.


BULL, Hannah (Data Scientist)