30C00200 - Econometrics, Lecture, 12.1.2022-25.2.2022

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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

The main objective of the course is to obtain a basic understanding of the econometric methodology. The aim is to motivate the students to examine causal relationships between economic phenomena by using a linear regression model. The course focuses on least squares estimation of the model and related statistical inferences. The assumptions of least squares estimation will be critically investigated. We examine the violations of these assumptions and the possible ways to alleviate the assumptions. The emphasis of the course is in the empirical application of the least squares method and its extensions. The economic interpretation of the estimated parameters of regression model and their statistical significance is given a special focus. After the course, students should have the skills to conduct basic empirical econometric analysis.

Credits: 6

Schedule: 12.01.2022 - 25.02.2022

Teacher in charge (valid for whole curriculum period):

Teacher in charge (applies in this implementation): Timo Kuosmanen

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: English

CONTENT, ASSESSMENT AND WORKLOAD

Content

  • valid for whole curriculum period:

    Econometrics is a branch of economics that aims to give empirical content to economic theory by applying statistical methods to real world data. This course focuses on the application of linear regression to economic data, its assumptions, and statistical significance tests of parameters and linear restrictions. We also extend the basic linear regression for modeling endogeneity, heteroskedasticity and autocorrelation. Time series and panel data models are considered towards the end of the course. All topics are examined by means of economic examples with actual empirical data.

Assessment Methods and Criteria

  • valid for whole curriculum period:

    70 % exam
    30 % assignments

Workload

  • valid for whole curriculum period:

    Lectures 36 h
    Exercise sessions 10 h
    Self-study and other independent work 74 h
    Exam preparation 37 h
    Exam 3 h
    Total 160 h (6 ECTS)

DETAILS

Study Material

  • valid for whole curriculum period:

    Lecture notes and additional material are provided on the course website.

    The following textbooks may be used as supplementary study material:
    Wooldridge, J.M. (2015) Introductory econometrics: A modern approach. (or any newer edition)
    Dougherty, Christopher (2016) Introduction to econometrics.  (or any newer edition)

Substitutes for Courses
Prerequisites
SDG: Sustainable Development Goals

    7 Affordable and Clean Energy

    8 Decent Work and Economic Growth

    12 Responsible Production and Consumption

FURTHER INFORMATION

Further Information

  • valid for whole curriculum period:

    Teaching Period:

    2020-2021 Spring III

    2021-2022 Spring III


    Course Homepage: https://mycourses.aalto.fi/course/search.php?search=30C00200


    Registration for Courses: In the academic year 2021-2022, registration for courses will take place on Sisu (sisu.aalto.fi) instead of WebOodi.

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