- Organizer: University of Helsinki
- Location: Helsinki, Arkadiankatu 7, Economicum building
- Time schedule
- The course includes 18 hours of lectures and 8 hours of exercises, a final exam and a possibility to retake the exam.
- Instructor: Assistant Professor Mika Meitz (University of Helsinki)
- Teaching assistant: Yin Ming (University of Helsinki)
Topics and learning objectives
- Description: This module covers a number of topics beyond the standard linear regression model, including estimation methods other than least squares, such as generalized method of moments and maximum likelihood estimation. In addition, simulation-based methods as well as basic nonparametric inference widely employed in empirical econometric research are discussed. After the module, the student should know the properties of the estimators introduced and be able to apply them and the related inferential procedures in empirical work. The module should also give a solid foundation for the study of more specialized microeconometric and time series methods. In addition, sufficient level of proficiency in simulation-based and basic nonparametric methods should be reached to enable critical evaluation of empirical results obtained by these methods.
- Topics covered include:
- Generalized method of moments
- Maximum likelihood estimation (basic concepts, asymptotic estimation theory, statistical inference)
- Simulation methods (Monte Carlo simulations, Bootstrap)
- Nonparametric methods (kernel density estimation, semi- and nonparametric regression)
Course Readings and Material
- To be added to Moodle