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This course moves beyond the standard linear regression model and conventional least squares estimation. Important econometric estimation principles, such as generalized method of moments and maximum likelihood estimation, are covered and the related statistical inference procedures discussed. Basic concepts of simulation-based methods are also introduced. Specifically, the topics covered in the course include

  • Generalized method of moments estimation (basic concepts, asymptotic estimation theory, statistical inference)
  • Maximum likelihood estimation (basic concepts, asymptotic estimation theory, statistical inference)
  • Simulation methods (Monte Carlo simulations, Bootstrap)
  • Completion method: remote teaching (a link to Zoom can be found in the course Moodle area)
  • Schedule: can be found in Course Page and Sisu
  • Study materials: can be found in Moodle
    • Tips for enrolling in a Moodle course area can be found here

Please register for the course in the UH Sisu with your UH username, further instructions can be found here.

    • Code: ECON-L4200
    • Target groups: PhD / rMSc / MSc
    • Credit points: 5
    • Credit transfer: apply for substitution in Sisu
    • Code: 26054
    • Target groups: PhD / rMSc / MSc
    • Credit points: 5
    • Credit transfer: apply for substitution in Sisu
    • Code: COM-R315

    • Target groups: PhD / rMSc

    • Credit points: 5

    • Target groups: PhD
    • Credit points: please check your curriculum
    • Credit transfer: please apply for credit transfer according to your home university's procedures

After the course, 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 course should also give a solid foundation for the study of more specialised microeconometric and time series methods.