NIFK14001U Microeconomic and Econometric Production Analysis
MSc Programme in Agricultural Economics
MSc Programme in Environmental and Natural Resource Economics
Knowledge about production technologies and producer behavior is
important for politicians, managers, business organizations,
government administrations, financial institutions, the EU, and
other national and international organizations who desire to know
how contemplated or implemented policies and market conditions
(e.g., world market prices) can aﬀect production, prices, income,
and resource utilization in agriculture as well as in other
industries. The same knowledge is relevant for consulting single
ﬁrms that want to compare themselves with other ﬁrms and the
"best practice", whilst taking into account the
uncertainty in the data and in the results. The participants of
this course will obtain relevant qualiﬁcations in econometric
production analysis so that they can contribute to the knowledge
about production technologies and producer behavior. Knowledge
of production economical facts is also of importance in economic
consultancy for farmers and other firms.
This is an applied course that focuses on practical and empirical applications based on microeconomic production theory. The course will cover, for instance, following topics:
- advanced microeconomic production theory, e.g., production functions; distance functions; cost minimization and cost functions; profit maximization and profit functions; properties of these functions
- important indicators of production technologies, e.g., elasticities of scale, elasticities of substitution
- descriptive analysis of real-world production data, e.g., calculation of partial productivities and total factor productivities
- econometric estimation of production functions, distance functions, cost functions, and/or profit functions; interpretation of the estimation results
- further analysis based on estimation results, e.g., optimal firm size
- functional forms in applied production analysis such as Cobb-Douglas, Translog, etc.
- efficiency analysis using Stochastic Frontier Analysis (SFA); analyzing determinants of technical efficiencies
In the classroom exercises and homework assignments, the students will analyze production technologies using the free statistical software "R" and real-word production data sets (e.g., agricultural production, energy production). It is expected that students know the basics of "R", e.g., obtained in the MSc course "Applied Econometrics" (LOJK10272) or through self-study. Introductions to relevant "R" packages are given in the classroom exercises.
The primary objective of the course is to provide the students
with relevant knowledge, practical skills, and competences in
empirical microeconomic production analysis so that they are able
to analyze production technologies and producer behavior with
appropriate econometric methods.
After completing the course the students should be able to:
- Describe the primal and dual approaches in microeconomic production theory, e.g. production functions, distance functions, cost minimization and cost functions, profit maximization and profit functions, and important indicators of production technologies
- Describe procedures in econometric production analysis based on primal and dual approaches in microeconomic theory
- Describe approaches for efficiency analysis
- Describe the assumptions that are required to apply the various approaches
- Use the software package "R" for econometric analysis of production data
- Apply econometric production analysis and efficiency analysis using real-world data
- Interpret the results of econometric production analysis and efficiency analysis
- Calculate and interpret important indicators of production technologies
- Choose a relevant approach for econometric production analysis and efficiency analysis
- Evaluate approaches for econometric production analysis and efficiency analysis
- Use econometric production analysis and efficiency analysis to investigate various real-world questions
- Critically evaluate the appropriateness of a specific econometric production analysis or efficiency analysis for analyzing a specific real-world question
See Absalon for a list of course literature. The course literature could be, for instance, the textbook "Applied Production Analysis - A Dual Approach" (Chambers, Cambridge University Press), lecture notes, and other material provided by the teachers.
Academic qualifications equivalent to a BSc degree is recommended.
- Theory exercises
- Practical exercises
- Project work
Students get continuous oral feedback from the teachers and/or teaching assistants during theoretical and practical class-room exercises. Student groups get peer-feedback on their homework assignments from other course participants. They get brief written feedback from the teachers on the final versions of their homework assignments that they have improved based on the peer feedback.
- 7,5 ECTS
- Type of assessment
- Oral examination, 20 min. preparation + 20 min. oral examStudents will be asked to present their solution to one randomly selected homework assignment and to solve one randomly selected exercise. Furthermore, they are expected to answer questions regarding other topics of the course.
Students who did not submit a solution to the randomly chosen homework assignment or submitted their solution after the submission deadline must answer the questions of this homework assignment without the help of a solution.
- Only certain aids allowed
Students will get their solution to the selected homework assignment, no other aid allowed.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
As ordinary exam
Students who have a re-exam can decide whether they want to prepare and submit new solutions or re-use their solutions that they submitted during the course. New solutions to the homework assignments must be submitted to the course responsible no later than three weeks before the re-exam
Criteria for exam assesment
The participants will get the grade "12" if they have fully achieved the intended learning outcome.