The goal of this course is to link econometric methods for estimation of causal effects to data. We will cover a number of theoretical topics that are important in applied research in labor economics, health economics, industrial organization and related fields.
The course will be organized in lectures to provide the economic framework and the econometric issues for each topic. The lectures will be complemented with problem sets, that include both theoretical and empirical exercises. Students ought to handle the Stata program on their own and read related papers.
Basic Skills:
To develop knowledge that is the basis for developing new knowledge, often in a research context.
To apply the concepts learn to new problems and to new areas of knowledge that are related to the area of study of the student.
To integrate diverse concepts and confront new realities and be able to judge ethical aspects when applying the concepts learned.
To communicate results and knowledge to the general public and to specialized audiences in a clear and unambiguous fashion.
To acquire the ability for independent learning.
General Skills:
To analyze and summarize a scientific text.
To interpret and elaborate advanced studies in economics.
To apply advanced knowledge in economics, mathematics, and econometrics.
To evaluate scientific articles.
To prepare and present scientific documents.
To identify key conventions in sciences and, in particular, economics.
To identify the value added by a scientific contribution.
Specific Skills:
To apply and interpret the standard model of rational choice in static conditions and without uncertainty.
To apply and interpret the extension of the rational choice model to risk and uncertainty.
To apply and interpret the extension of the rational choice model to the dynamic framework.
To apply and interpret the standard model of strategic interaction (game theory) in static and dynamic situations, with or without asymmetric information.
To describe and analyze consumption decisions under uncertainty
To apply and interpret the mechanism design model both under symmetric and asymmetric information.
To understand and evaluate alternative public polices and their macroeconomic consequences.
To apply and interpret macroeconometric models
To apply and interpret the concept of random variables at an advanced level, distinguishing (a) between potential and actual outcomes, and (b) between population and sample.
To apply the description of a random variable to advanced problems using the probability distribution function and the cumulative distribution function.
To analyze a random sample to provide moment estimators or characteristics of a random variable, distinguishing between population parameters (unknown) and sample estimators.
To apply advanced statistical estimation and hypothesis testing to make inferences about a parameter or characteristic of a random variable.
To apply and interpret the linear regression model and its assumptions.
To apply and interpret at an advanced level the ordinary least squares estimator in the linear regression model under classical assumptions, and its parametric tests.
To discuss the consequences of deviating from classical assumptions in the linear regression model.
To apply and interpret the variable approach at an advanced level
To apply and interpret at an advanced level the identification and estimation of simultaneous linear equation systems: OLS, GLS, 2SLS, and 3SLS.
To apply and interpret the panel data model, and discuss the problem of unobservable heterogeneity and estimation methods.
Learning outcomes:
1. Understand the distinction between causal and spurious relationships.
2. Apply advanced econometric methods to questions from other fields of economic analysis.
3. Use econometric tools to describe economic relationships and construct stylized facts.
4. Master the basic elements of public policy evaluation.
5. Understand the assumptions necessary to evaluate an intervention or treatment.
6. Distinguish and understand identification assumptions in different data structures.
7. Master empirical analysis with microdata: households, firms, or individuals, in particular, specifications, estimation methods, and inference of various types of models formulated for both panel data and cross-sectional data.
8. Apply public policy evaluation methods to problems in development economics, labor economics, family economics, environmental economics, industrial economics, health economics, and population economics.
9. Familiarization with recent advances in different topics in applied economics.
10. Develop a critical stance on future aspects to be addressed for future advances in the literature.
11. Develop the ability to define both micro-econometric and macro-econometric empirical models for application to different areas of applied knowledge.
12. Define counterfactuals of interest.
13. Establish the relevant parameters in the evaluation of an intervention or treatment.
14. Distinguish the elements that ensure internal and external validity in a causal analysis.
15. Develop the ability to replicate the results of a scientific publication and to convey the details of the replication.
16. Develop critical thinking, synthesis, and creativity in empirical work.
