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This course introduces the basic methods used in the linear regression analysis of economic variables. The classical finite sample theory and asymptotic analysis of the linear regression model as well as the necessary methodological tools required for these topics are covered. Specifically, the topics covered in the course include

  • Classical finite sample theory in the linear regression model 
  • The basics of asymptotic theory 
  • Asymptotic theory in the linear regression model 
  • Autocorrelation, heteroskedasticity and dynamic regressors 
  • Specification tests 
  • Omitted variables, instrumental variables and the two-stage least squares estimator (2SLS)
  • Completion method: remote teaching
  • Schedule: can be found in Courses Page and Sisu
  • Study materials: can be found in Moodle
    • A link and a Moodle course key will be sent by email before the course starts and/or they will be provided on the Courses page: you can view the information on this site without logging in or registering, but some of the content added by teachers to course pages may be available to course participants only, for example Moodle course enrolment key.
    • Log in with your UH username to be able to use all the features of the course workspace
  • Self study material to be studied before the course starts (link to be added here later)

Please register for the course in the UH Sisu with your UH username. Further instructions (link to be added here later).

    • Code: ECON-L4100

    • Target groups: PhD / rMSc / MSc

    • Credit points: 5

    • Credit transfer: apply for substitution in Sisu

    Further instructions (link to be added here later)

    • Code: 26053

    • Target groups: PhD / rMSc / MSc

    • Credit points: 5

    • Credit transfer: apply for substitution in Sisu

    Further instructions (link to be added here later)

    • Code: COM-R314

    • 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

    Further instructions (link to be added here later).

After the course, the student should

  • Know the main properties and limitations of the linear regression model 
  • Be familiar with the basics of asymptotic analysis 
  • Be able to employ the linear regression model and related inferential methods in empirical research