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ECN301 Econometric Methods

Credits (ECTS):10

Course responsible:Olvar Bergland

Campus / Online:Taught campus Ås

Teaching language:Engelsk

Course frequency:Annually

Nominal workload:250 hours

Teaching and exam period:This course starts in Spring parallel. This course has teaching/evaluation in Spring parallel.

About this course

This course focuses on modern econometric methods for the utilization of and analysis using economic data - both cross-sectional and time-series data. The following topics are covered: estimation and testing of linear regression models with stochastic and possibly endogenous regressors, panel data models, models with limited dependent variables, models of sample selection, and time-series models for stationary or non-stationary processes, co-integration and error correction models, prediction and cross-validation.

Learning outcome

The successful student should be able to

  • conduct independent econometric analysis of economic data,
  • access sources for economic data,
  • combine data from different sources,
  • critically evaluate econometric analysis with respect to choice of model, method and interpretation of results,
  • communicate empirical economic analysis and results including data sources, choice of model and estimator, results and policy implications, and
  • know and understand current professional and ethical standards for analysis, documentation and reporting within economics.
  • Learning activities

    The course consists of lectures and organized computer laboratory time as well as self-study. There are six independent assignments. The assignments involve data, but are not limited to data gathering, data cleaning, estimation of different econometric models, interpretation and presentation of results, and critical assessment of econometric analysis.

    The class time is divided with about 20% as organized class time, 40% as exercises, 40% as self study.

  • Teaching support
    Open office 2 hours/week.
  • Prerequisites
    STAT100 Statistics, ECN201 Econometrics (or regression analysis), Linear algebra at the level of ECN302 Mathematics for Economists. BUS350 Data Analytics in R.
  • Recommended prerequisites
    Courses in micro- and macroeconomics. Experience with computer languages such as Python and/or R.
  • Assessment method

    Combined assessment based on a portfolio (8 assignments for 60% of overall grade) and an oral exam (40% of overall grade) held during the examination period. The oral exam includes a presentation based on one of the written assignments and questions pertaining to the course.

    All parts of a combined assessment must be passed in the same semester to pass the course.

    A retake exam is not organized in this course. Those who do not pass need to retake the whole course.



    Portfolio Grading: Letter grades Oral exam Grading: Letter grades
  • Examiner scheme
    An external examiner is used to evaluate course content, exam questions and grading guidelines.
  • 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
    Class lectures: 44 hours. Laboratory work: 20 hours.
  • Admission requirements
    Minimum requirements for entrance to higher education in Norway (generell studiekompetanse).