2023
Microeconometrics
Name: Microeconometrics
Code: ECN10320D
7.5 ECTS
Duration: 15 weeks/195 hours
Scientific Area:
Economy
Teaching languages: Portuguese
Languages of tutoring support: Portuguese, English
Regime de Frequência: Presencial
Presentation
The econometric methods applicable to the main types of microeconomic data are thoroughly analyzed: the main alternative specifications, the estimation methods and their assumptions.
Sustainable Development Goals
Learning Goals
Main Objectives:
To acquaint students with modern econometric techniques for the analysis of micro data and to prepare them for practical application of econometric techniques. The students should be able to carry out relevant practical analysis using appropriate software. Some of the topics maybe different in some years, according to the students research interests.
Competences to be acquired:
• Data analysis and manipulation.
• Formulation of econometric models and its interpretation
• Critical reasoning; problem solving; analytical skills;
• Team work, written and oral communication ;
• Computing skills and knowledge of econometric software
To acquaint students with modern econometric techniques for the analysis of micro data and to prepare them for practical application of econometric techniques. The students should be able to carry out relevant practical analysis using appropriate software. Some of the topics maybe different in some years, according to the students research interests.
Competences to be acquired:
• Data analysis and manipulation.
• Formulation of econometric models and its interpretation
• Critical reasoning; problem solving; analytical skills;
• Team work, written and oral communication ;
• Computing skills and knowledge of econometric software
Contents
Introduction: Microeconometric data, Data Issues, Specification Analysis
Advanced topics in Models for Limited and discrete dependent variables,: Tobit Models; Two-part models; Selectivity Models.
Advanced topics in Panel Data Models: Dynamic Models, Nonlinear Models.
Duration Analysis: Parametric and semiparametric models. Continous time models and discrete time models.
Spatial Econometrics: Spatial dependence and spatial heterogeneity. Spatial autocorrelation statistics. Spatial regression models.
Policy Evaluation Methods: Natural and Social Experiences, Differences in Differences Methods, Matching.
Advanced topics in Models for Limited and discrete dependent variables,: Tobit Models; Two-part models; Selectivity Models.
Advanced topics in Panel Data Models: Dynamic Models, Nonlinear Models.
Duration Analysis: Parametric and semiparametric models. Continous time models and discrete time models.
Spatial Econometrics: Spatial dependence and spatial heterogeneity. Spatial autocorrelation statistics. Spatial regression models.
Policy Evaluation Methods: Natural and Social Experiences, Differences in Differences Methods, Matching.
Teaching Methods
Small group classes where theoretical contents are supplemented by exercise lectures and computer
exercises, in order to help understanding the theoretical concepts and to give the opportunity to the students to produce econometric work of their own. Real economic data is employed on solving the computer exercises using adequate software.
Evaluation: One individual empirical project.
exercises, in order to help understanding the theoretical concepts and to give the opportunity to the students to produce econometric work of their own. Real economic data is employed on solving the computer exercises using adequate software.
Evaluation: One individual empirical project.
Teaching Staff
- Maria Aurora Murcho Galego [responsible]
