Econometric Theory (master)

Lecture: 16007, Wed, 8:15 - 10am
Exercise: 16006, Fr, 8:15 - 10am
LSF link

Tutor: Mauricio Olivares (m.olivares@lmu.de)

Teaching content: The generalized method of moments (GMM) is the organizing principle of this course. The notion of a moment is essential for describing features of a population. Indeed, as we will see throughout the course, moment equations typically characterize econometric models and link naturally to economic theory. Such a connection makes GMM a unifying framework for studying modern econometrics. We begin this course with the popular ordinary least squares (OLS) method as a particular case of GMM. OLS conveys many of the core ideas behind GMM. Thus, we spend the first part of this course carefully studying it while keeping in mind this is only a stepping stone to the richer and more flexible GMM framework.
Once we are familiar with the OLS machinery, the second part of this course will focus on GMM. We will spend quite some time developing the large sample properties of GMM and associated test statistics. We enrich this section by introducing a series of topics specific to GMM, like over-identifying restrictions or conditional moment equations.
GMM is considerably general. Besides OLS, it encompasses instrumental variables (IV), multivariate regression, two-stage least squares (2SLS), quasi-maximum likelihood, random effects, fixed effects, linear and nonlinear models defined by moment equations, and the list goes on. In the third part, we highlight GMM’s potential by looking at some special cases. However, since they are special cases of GMM, we develop their large-sample properties almost off the shelf by leveraging the lessons learned from Part III.

Requisites: There are no formal prerequisites for this course. However, students are expected to be familiar with matrix algebra (at the level of Bruce Hansen's Econometrics, Appendix A) and have a good command of probability and statistics at an advanced undergraduate level.

Audience: PhD and Master students in statistics and economics

Evaluation: The final grade is entirely determined by a final exam at the end of the semester (approximately one week after the last day of classes). The exam is theoretical, comprehensive, and goes for about 150 min (2,5 hrs).

ECTS Credits: 6 ECTS