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Course

ECN201 Econometrics

Credits (ECTS):10

Course responsible:Erlend Dancke Sandorf

Campus / Online:Taught campus Ås

Teaching language:Engelsk

Course frequency:Annually

Nominal workload:250 hours

Teaching and exam period:The course starts in Autumn parallel. The course has teaching/evaluation in Autumn parallel.

About this course

The course covers simple and multiple regression analysis. Topics include: Ordinary Least Squares (OLS), hypothesis testing, violations of the OLS assumptions, Generalized Least Squares (GLS), dummy independent variables. The econometric program R is used in computer exercises.

Learning outcome

Knowledge

  • Have knowledge of fundamental concepts in econometrics and statistics.
  • Be familiar with the assumptions behind the least squares method and the consequences when these assumptions are not met.
  • Be familiar with different types of economic data, such as cross-sectional, time series, and panel data, and understand how data influences model selection.
  • Have knowledge of the theory underpinning statistical and econometric inference.

Skills

  • Be able to conduct simple and multiple regression analyses on cross-sectional and time series data in R.
  • Be able to test whether the assumptions of the model hold in R.
  • Be able to test and correct for misspecification in a regression analysis.
  • Be able to test economic hypotheses using the model.
  • Read, interpret, and critically evaluate reports and articles that use regression analyses.

General Competence

  • Identify issues and formulate researchable questions within applied economics.
  • Learning activities
    Teaching on campus without streaming. The course consists of lectures and independent studies in the form of reading the textbook, solving problem sets, and doing PC exercises.
  • Teaching support
    Lectures and seminars
  • Syllabus

    Jeffrey M. Wooldridge. Introductory Econometrics - A Modern Approach, 7th edition, Cengage. The textbook used in the course may be changed.

    R and R studio is open source and freely accessible for download.

  • Prerequisites
    Introductory mathematics such as MATH100 Introductory Mathematics or ECN102 Introduction to Mathematics for Economists, statistics such as STAT100 Statistics, and microeconomics such as ECN210 Microeconomics: Consumers, Producers, Market and Welfare.
  • Recommended prerequisites
    Basic knowledge about macroeconomics, for example, ECN120 Macroeconomics I - Markets, Economic Development and Welfare
  • Assessment method
    Final written exam (3,5 hours) that accounts for 100% of the grade. Grading A-F.

    School exam Karakterregel: Letter grades Hjelpemiddel: B1 Calculator handed out, no other aids
  • About use of AI

    Mandatory activity: K2 - Specified use of AI in line with the NMBU guidelines. For the mandatory assignments AI may be used as support with R. AI use must be described in the submission, including which AI, how, and for what it was used. You are responsible for all submitted work.

    Exam: K1 - The use of AI is not permitted.

    See guidelines for use of artificial intelligence (AI) at NMBU.

    Descriptions of AI-category codes.

  • Examiner scheme
    The course is graded by an internal examiner. External examiner will control the quality of syllabus, questions for the final examination, and principles for the assessment of the examination answers.
  • Mandatory activity

    3 of 4 mandatory assignments must be approved.

    Approved mandatory activity from the last time the course was given is valid when retaking the course.

  • Notes
    The course is in English. Incoming students can contact student advisors at the School of Economics and Business (studieveileder-hh@nmbu.no) for admission to the course.
  • Teaching hours
    250 hours. About 28 hours of lectures and 20 hours of exercises. The rest is unstructured time allocated to independent studies such as reading and working independently on ten problem sets.
  • Reduction of credits
    The course partly overlaps with ECN202 Introduction to Econometrics and STAT200 Regression Analysis. There is reduction in credits for ECN202 (5 ECTS) and STAT200 (5 ECTS).
  • Admission requirements
    Minimum requirements for entrance to higher education in Norway (generell studiekompetanse).