A.A. di erogazione 2020/2021
Insegnamento obbligatorio

 (A.A. 2020/2021)


Anno di corso: 
Tipologia di insegnamento: 
Settore disciplinare: 
Primo Semestre
Ore di attivita' frontale: 
Dettaglio ore: 
Lezione (80 ore)

In the last one or two decades, the classical way of teaching economics, through theoretical models and without empirical evidence, has been questioned. The prominence of this framework is caused by the fact that introductory courses are generally taught when students do not have yet the statistical skills that would allow them to appraise critically the data. The solution that has been advocated very recently is to teach theory together with data analysis.
This course is structured exactly as an interplay between economic theory and econometric data analysis. Each economic topic is presented together with the econometric tool that can be used to obtain estimates connected with it. When topics accumulate, more and more applications of the same econometrics tools will be introduced.
An additional feature of the course is that the presentation of the econometric methods follows roughly their historical development. First of all, the linear regression that was introduced around 1885 by Francis Galton will be presented. The consumer and producer problems were formalized around the same time by the marginalist school. The general equilibrium theory in economics and simultaneous equations estimation in econometrics are the main contributions of the Cowles Commission, founded in 1932. Both these topics converge in the estimation of demand-supply equilibria.
Then we tackle some topics that have been developed between the 30’s and the 90’s, and that account for some deviations from the classical description of producers, consumers and market equilibria. Then we turn to discrete choice models and their applications, a topic developed in the 70’s and 80’s, and that has led to a better comprehension of individual behavior. This establishes a link with behavioral and experimental economics.
At last, we consider the models and methods developed in in the so-called "empirical revolution”, a movement in economics that has allowed researchers to study economic phenomena from the empirical point of view with much greater efficiency and effectiveness than in the past.

The most trivial competence that the student should obtain from the course is to master the interpretation of the results of OLS, IV, 2SLS and ML estimation. More ambitiously, the course aims to:
- fill the gaps that students coming from heterogeneous backgrounds may have in their basic micro-economic knowledge, and
- teach something about the scientific method, namely how statistical inference can help in testing hypotheses and which arrangements have to be done to this procedure in a complex context such as the economic environment.


Lecture 00 - R (1 hour)
Econometrics of Competitive Markets (40 hours)
Lecture 01 - Linear Regression
Lecture 02 - Consumption Theory
Lecture 03 - Production Theory
Lecture 04 - Economic Aspects of the Demand-Supply Equilibrium
Lecture 05 - The Instrumental Variables Estimator
Lecture 06 - Simultaneous Equations Systems and the Demand-Supply Equilibrium
Econometrics of Imperfect Markets (15 hours)
Lecture 07 - Oligopolistic Models
Lecture 08 - Production Theory Reloaded
Lecture 09 - Dynamics in Demand-Supply Equilibria
Lecture 10 - Hedonic Price Models, Parametric Cost Analysis and Conjoint Analysis
Lecture 11 - Product Diffusion Models
Econometrics of Non-Existent Markets (10 hours)
Lecture 12 - Discrete Choice Models
Lecture 13 - Contingent Valuation Studies
Lecture 14 - Models of Firm Decisions
Econometrics of Policy Interventions (14 hours)
Lecture 15 - Causal Relationships and Controlled Experiments
Lecture 16 - The Neyman-Rubin Causal Model
Lecture 17 - Estimation under Conditional Independence
Lecture 18 - Estimation without Conditional Independence

The course will be composed of 80 hours of lectures, and will be based on a set of slides written by the instructor, covering both theory and specialized paper-length examples.

Students will be evaluated on the basis of an essay discussing a topic relevant to the course. The student can choose whether to write an applied or theoretical essay:
- an applied essay is based on the statistical analysis of real data;
- a theoretical essay is based on the reading and critical analysis of some papers.
The final topic of the essay will be chosen together by the instructor and the student. The grade will take into account both the technical skills learned by the student during the course, and the structure and organization of the text.

The course will be based on a set of slides written by the instructor, covering both theory and specialized paper-length examples. A list of academic papers or blog posts addressing more advanced topics will be provided to the students as additional readings. Mathematical derivations will be dealt with in handouts written by the lecturer. Solved exercises exploring more advanced topics will also be provided.

Office hours by appointment arranged by email.

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