For students:

Solving environmental problems with data (5 cr)

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Code:
AGERE-E11
Field:
Environmental Economics
Targets:
Master’s students Research Master's students PhD students
Organiser:
University of Helsinki - Environmental Economics
Instructor:
Lassi Ahlvik
Period:
Period 4
Format:
Lecture
Method:
Contact teaching
Venue:
Viikki campus
Enrollment:
Sisu How to enroll?

In case of conflicting information consider the Sisu/Courses/Moodle pages the primary source of information.

Content

Most common methods for causal identification, including randomized controlled trials (RCTs), instrument variable analysis, panel data and difference-in-differences and regression discontinuity designs. The course will have both lectures and Stata lab sessions.

Teaching

  • Schedule: can be found in Course Page and Sisu
  • Study materials: can be found in Moodle
    • For some courses, it is enough to register in Sisu and you can access directly the Moodle area, please note, however, that it may take up to two hours after registration to enter the Moodle area.
    • Log in with your UH username to be able to use all the features of the course workspace
    • More tips for enrolling in Moodle can be found here

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

University-specific instructions

Aalto University Students
  • Code: no equivalent code
  • Target groups: MSc / rMSc / PhD
  • Credit points: 5
  • Credit transfer: apply for inclusion in Sisu
Hanken Students
  • Code: no equivalent code
  • Target groups: MSc / rMSc / PhD
  • Credit points: 5
  • Credit transfer: apply for substitution in Sisu
University of Helsinki Students
  • Code: AGERE-E11
  • Target groups: MSc / rMSc / PhD students: please contact your supervisor/program director to be sure that the course credit can be counted towards your degree
  • Credit points: 5
FDPE Students Students
  • Please contact your supervisor/program director to be sure that the course credit can be counted towards your degree
  • Credit transfer: please apply for credit transfer according to your home university’s procedures
    • further instructions can be found here.

Learning outcomes

After finishing this course the students will have a sound knowledge on different methods for causal analysis and understnd how empirical methods can be used for analyzing drivers of and solutions to environmental problems. Students will be equipped with the skills necessary to understand and to apply methods of causal analysis to actual observational and experimental data, formulate research questions and have the skills to write do-flies and run relevant commands to produce tables and figures in R or Stata. After the course students will be able to use causal analysis methods in their master's thesis or in future professional careers.