ECON-C4210 - Econometrics II, Lecture, 24.2.2025-7.4.2025

Inträde för gästanvändare
Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Students are able to

  1. utilize panel data with an understanding of the benefits
  2. employ Difference-in-Difference and Regression Discontinuity methods for causal analysis
  3. model limited dependent variable and describe at a conceptual level how maximum likelihood estimation works
  4. discuss the connection between econometric models and the basic machine learning models
  5. classify and estimate time series econometrics, including forecasting models
  6. describe VAR (Vector AutoRegressive) models and their use
  7. explain what cointegration is
  8. describe (G)ARCH (Generalized AutoRegressive Conditional Heteroskedasticity) models and their use
  9. apply the econometric tools taught in this course and in Econometrics I and use them to perform and present an econometric analysis in the Capstone project

Credits: 5

Schedule: 24.02.2025 - 07.04.2025

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Otto Toivanen

Contact information for the course (applies in this implementation):

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: Finnish, English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Panel data methods, difference in difference analysis, regression discontinuity analysis and time series analysis. Capstone work. 

Assessment Methods and Criteria

  • valid for whole curriculum period:

    Exam, exercises

Workload

  • valid for whole curriculum period:

    Lectures, exercises and preparation

DETAILS

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    8 Decent Work and Economic Growth

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Language: English

    Teaching Period: 2024-2025 Spring IV
    2025-2026 Spring IV

Rules of Conduct - Students´ Rights and Responsibilities (in force from 1 August 2020)

Aalto University Code of Academic Integrity and Handling Violations Thereof