About this course

Provide in-depth knowledge and understanding of methods of analysis among survey design, experimental design, and econometric modeling to analyze economic data, with the ability to detect logical flaws in the analysis. Basic introduction to the challenge of identifying causal effects in the analysis of survey data. Provide an overview of impact assessment methods: establishment of causality vs. correlation; Impacts of what on what?; How far can the results be generalized? Introduction and exercises in use of matching methods, selection methods, Instrumental variable methods, control function methods, difference-in-difference methods, panel data methods, experimental and quasi-experimental approaches. The students get exercises in use of the different methods. It is a "learning by doing" course.

Learning outcome

Knowledge

  • Deep knowledge about the challenges of identifying and measuring impacts of policies, projects, shocks (causes of impacts)
  • To use advanced statistical/econometric methods to measure impacts based on non-experimental data;
  • Requirements to separate causal effects from correlations
  • How to handle endogeneity with different quasi-experimental methods

Skills

  • How to use R software for impact assessment;
  • Application of advanced statistical methods on real-world data
  • Inspecting data quality and selection of relevant variables to answer different research questions

General competence:

  • Critically compare the different methods, understand their relative strengths and weaknesses, and think about what is the best (combination) of methods in specific situations; and
  • Understand what it takes to do good and critical empirical analyses with sustainability as a guiding principle.

  • Learning activities

    There are lectures and four exercises in the course on use of different impact assessment methods. Each method and exercise is introduced through a lecture. The students then spend two weeks on completing each of the exercises. The course has a "learning by doing" philosophy and the students can seek help from the teacher when they face challenges. For each of the data exercises, the students have to inspect a data set and select the relevant variables for their analysis. Towards the end of the course the students are asked to compare the different methods, their strengths and weaknesses and consider how they may be combined to get further insights.

  • Teaching support

    Exercises with support from teacher/teaching assistant.

  • Syllabus

    Cameron, A. C. and Trivedi, P. K. (2010). Microeconometrics Using Stata. Revised Edition. Stata Press. Detailed list of readings is provided at the beginning of the course. Powerpoints related to lectures are provided in Canvas during the course.

  • Prerequisites

    ECN201 Econometrics, STAT100 Statistics, basic knowledge of R.

  • Recommended prerequisites

    ECN301 Econometric methods

  • Assessment method

    Final written in-class examination (3,5 hours) accounts for 100% of the grade.

    Written exam Karakterregel: Letter grades Hjelpemiddelkode: A1 No calculator, no other aids

  • About use of AI

    Mandatory activity: K3 - Full Use of AI. This category allows unrestricted use of AI, as long as it aligns with the Guidelines for the Use of Artificial Intelligence (AI) at NMBU.

    Exam: K1 - No Use of AI.

    Descriptions of AI-category codes.

  • Examiner scheme

    External examiner will control the quality of syllabus, questions for the final examination, and principles for the assessment of the examination answers.

  • Mandatory activity

    Creative Presentation of an Estimation Method. Students will work in groups and produce a creative presentation of the method based on course material and the materials listed in the syllabus. The assignment requires students to translate technical knowledge into a creative format such as a rap, parody song, storytelling piece, short play, spoken word performance, or similar creative expression. The students themselves must perform in the creative presentation. The performance must be recorded as a video and presented in class. The creative work must demonstrate a solid understanding of the chosen method. Approval of the mandatory assignment is required in order to sit the final exam. 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

    2 hours per week, combining lecture and exercise.

  • Reduction of credits

    There are some overlaps with ECN301 Econometric Methods but the course is intended to be complementary to ECN301 as it gives more practical exercises in the use of some of the methods introduced in ECN301.

  • Admission requirements

    Minimum requirements for entrance to higher education in Norway (general study competence)