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 methods for distinguishing causal relationships from mere correlations; and discuss the extent to which findings can 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, regression discontinuity, maximum likelihood estimation and binary and multinomial choice models. The students get exercises in use of the different methods. It is a "learning by doing" course.

Learning outcome

Knowledge

  • Have advanced knowledge about the challenges of identifying and measuring the causal effects of policies, projects, and exogenous shocks.
  • Have deep knowledge about the assumptions and conditions required to distinguish causal effects from mere correlations in empirical research.
  • Can apply knowledge on advanced statistical and econometric methods to estimate causal effects using observational data.
  • Can analyse endogeneity problems and address them using a range of quasi-experimental identification strategies.

Skills

  • Can analyze and critically assess data quality, measurement issues, and the selection of relevant variables for addressing different research questions.
  • Can analyze real-world data using advanced statistical methods to investigate causal relationships.
  • Can use relevant tools in R to manage data, perform econometric analyses, and interpret results.

General competence:

  • Can analyze relevant empirical methods critically, compare their strengths and weaknesses, and assess the most appropriate combination of approaches in specific contexts.
  • Can contribute to rigorous and ethically grounded empirical analyses, with sustainability as a guiding principle.
  • Can apply their knowledge and skills to their own academic work, including independent research projects such as a master’s thesis.

  • Learning activities

    There are lectures and exercises in the course on use of different 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

    Hjelpemiddel: A1 No calculator, no other aids



    School 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

    Five compulsory exercises must have been submitted and approved (quality check) before a candidate can take the 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

    There are 4 hours of lectures and exercises per week. Approximately 60% of the time is lectures and 40% of the time is exercises.

  • 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)