HOUSEHOLD ECONOMICS

This course is offered to second year PhD students and is aimed at providing advanced tools for the understanding and the development of applied microeconometric analyses. The course will propose quantitative methods for the analysis of cross-sectional data (for instance, samples of households or firms in a given year) or panel data (for instance, samples of households or firms followed over time). The course will discuss microeconomic models and to then propose emprical solutions - placing particular attention on the interpretation of their predictions and the discussion of the policy implications.
The course intends to emphasize the practical application approach rathre than the theoretical approach

1. Knowledge and understanding:
1.1. Knowing microeconometric models for the analysis of cross-section and panel data;
1.2. Knowing how to present and interpret the results produced by these models to answer a research question in economics;
1.3. Knowing the hypotheses at the basis of the models studied during the course and their consequences on the identification and the estimation of causal effects in economic research questions.

2. Applying knowledge and understanding:
2.1. Applying the models studied in the course to answer a research question in economics;
2.2. Comparing the results produced by alternative econometric models based on the different hypotheses on the data generating process and their reliability in the research questions at hand;
2.3. Applying the economic theory to assess the contribution of alternative microeconometric models in terms of identification and estimation of causal effects


3. Evaluation and project skills:
3.1. Designing empirical analyses that exploit cross-sectional or panel data to address an economic research question of interest;
3.2. Evaluating the contribution provided by papers in the scientific literature that exploit microeconometric models to address an economic research question of interest;
3.3. Thinking about the design of microeconometric models aimed at overcoming issues in the identification and estimation of causal effects.

4. Lifelong learning skills
4.1 Master complex quantitatve problems.
4.2 Master assumptions of economic problems to be implemented in applications
4.3 Ability to make use of new tools and adapt competences.

Students must be familiar with the contents of the Probability Theory and Basic Econometrics courses of the PhD course.
In particular, students should be familiar with the following subjects, at least at the introductory level:
- random variables, distribution, expectations, moments;
- joint distributions, marginal distributions, conditional distributions
- hypothesis testing;
- linear regression models and ordinary least squares estimation (OLS);

The life-cycle model of saving as a basic working model
Empirical Implications of the Life Cycle Theory
Empirical applications/testing Life Cycle Theory
Liquidity Constraints and empirical issues related to risks
Applied models of Labour Supply and Human capital
Models and applications of Health, Saving and Retirement
Other relevant models with applications

The course is based on case studies: a presentation of the lectures will be provided on slides at the dedicated moodle platform

Grading is based on the work done during the years (homeworks and study groups) and on a final written exam.

The course is strongly based on practical experience and case studies, flipped classes. Lectures will support the organization of the material

Grading is based on the work done during the years (homeworks and study groups) and on a final written exam

written