Economics, Topics on Economic Growth (Fall 2023). The course aims to provide students with advanced theoretical tools in macroeconomics, focusing on consumer theory, firm theory, general equilibrium, micro-foundations of economic growth, business cycles, and welfare economics.
David Romer (2019) Advanced Macroeconomics 5th Edition. Chapters 2, 3, 5.
Applied Statistics (Spring 2020). This is a first course in applied statistics and probability theory for graduate students in social sciences. The course aims to gradually introduce students to formalism, terminology and tools for the knowledge of statistical analysis of the main phenomena of our socioeconomic system. The program is ideally divided into parts ranging from the indication and explanation of the statistical tools (descriptive statistics), to the implementation and measurement of socioeconomic theories that influence our dynamic system (statistical inference). At the end of the course, the student will be able to quantify (hypothesis testing) the main economic phenomena and compare the measurement (inference) methods most widely used.
Agresti, Alan. and B. Finlay. Statistical Methods for the Social Sciences (5th edition), Pearson Education Limited.
Casella, G. and R. Berger. Statistical Inference (2nd edition), Duxbury Advanced Series.
Microeconomic Topics on: Monopoly, Oligopoly, Externalities, Information (Fall 2019). Lessons will cover the topics of Chapters 14 (15), 16, 24, 25 from Varian, Hal R. Microeconomic Analysis. But there can be so useful the Nicholson’s book on Microeconomic Theory (ch. 14, 15, 18, 19), the Varian’s book on Intermediate Microeconomic (ch. 24, 25, 27, 29, 34, 35, 37).
Introduction to Applied Econometrics (2018). This course is intended to provide an explicit list of the introductory mathematical formulae and proofs that you are expected to know for the examination in an introductory course of econometrics. The aim is to cover the basic ideas of linear regression, first with the two-variable regression model and then with the multivariate model, using both quantitative and qualitative variables. Then we deal with the practical consequences of relaxing various assumptions of the classical linear regression model. We close lessons with an introductory analysis of time series. The purpose is that students will be able to set up an econometric model, estimate the model, perform appropriate diagnostic and hypothesis tests, and interpret the results.
Dougherty, C. Introduction to Econometrics, 5th edition.
Brooks, C. Introductory Econometrics for Finance, 2nd or 3th edition.
Wooldridge, J. M. Introductory Econometrics: A Modern Approach, 6th Edition.