The course aims at providing the Ph.D students the basic math skills needed in order to follow proficiently the Econometric, Micro and Macro courses of the Ph.D program. The course is divided in two parts. In the first part, after a brief review of calculus, will be explained the basics of linear algebra, static optimization and discrete dynamic optimization. In the second part, the topics will be ordinary differential equations, calculus of variations and optimal control theory.
The econometrics course aims at giving the students all the necessary tools for a thorough comprehension of contemporary applied econometrics literature, plus a solid understanding of the main topics in contemporary econometrics. The course is divided into 3 main modules:
General Principles of Estimation and Inference
Time series Econometrics
Module (a) will not go into the specifics of applied econometric techniques, but rather aims at making the students familiar with the main statistical and computational techniques used in contemporary applied econometrics. Modules (b) and (c) are more applied in nature than module (a) and will focus on applications as well as the theoretical aspects.
This course aims at giving PhD students a solid intermediate and upper intermediate treatment of the foundations of microeconomic theory, and to present selected extensions, as a basis for enabling the comprehension of the contemporary developments of the literature. Main topics are consumer and firm's behavior, market structures and regulation, and partial and general equilibrium analysis. In detail, the course is divided into the following main modules:
Production theory and functional forms
Theory of choice
Game Theory and Industrial Organization
While the main emphasis is put on theoretical aspects, some modules also feature empirical applications.