Summer Course: Introduction to Econometric Production Analysis ...

Summer Course:
Introduction to Econometric Production
Analysis with R
Arne Henningsen
University of Copenhagen
Introduction
This one-week intensive course is designed for MSc students, PhD students, and any other
persons who are interested in learning econometric production analysis. The participants will
learn to analyse production technologies and producer behaviour by applying microeconomic
production theory and econometric methods. The course will brush up and deepen the participants’
knowledge in microeconomic production theory but it will focus on the application of
these methods and the interpretation of the estimation results using various hands-on exercises.
Intended Learning Outcomes
Knowledge about production technologies and producer behaviour is important for politicians,
business organizations, government administrations, financial institutions, the EU, and other
national and international organizations who desire to know how contemplated policies and
market conditions can affect production, prices, income, and resource utilization in agriculture
as well as in other industries. The same knowledge is relevant in consultancy of single firms who
also want to compare themselves with other firms and their technology with the best practice
technology. 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 behaviour. After completing the course the students should be able to:
• use econometric production analysis and efficiency analysis to analyse various real-world
questions,
• interpret the results of econometric production analyses and efficiency analyses,
• choose a relevant approach for econometric production and efficiency analysis, and
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• critically evaluate the appropriateness of a specific econometric production analysis or
efficiency analysis for analysing a specific real-world question.
Course Prerequisites
The participants are expected to have a basic knowledge of microeconomic production theory
(e.g. technology set, production function, isoquant, cost function, marginal product, partial
output elasticity, elasticity of scale, marginal rate of technical substitution, elasticity of
substitution), econometrics (e.g. ordinary least squares, hypothesis tests), and mathematics
(e.g. logarithms, partial derivatives). Furthermore, some experience with econometric software
(particularly R) is helpful. Students who are lacking knowledge in some of these topics are
encouraged to fill their knowledge gaps before the course.
Students should bring a laptop computer with R (http://www.r-project.org) and RStudio
(http://www.rstudio.org) installed to the course.
Course Schedule
Monday morning
• welcome
• introduction to the course
• brush-up: production functions and their properties
• preparing data for econometric production analysis
• introduction of the main data set used in the course
• brief introduction to R and RStudio
• calculation of variables needed for the analysis
Monday afternoon
• partial productivities
• total factor productivities
• linear production function
– specification
– estimation
– observed and predicted output quantities
– marginal products
– partial output elasticities
– elasticities of scale
– optimal firm size
– consistency with microeconomic theory
– marginal rates of technical substitution
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Tuesday morning
• Cobb-Douglas production function
– specification
– estimation
– observed and predicted output quantities
– marginal products
– partial output elasticities
– elasticities of scale
– optimal firm size
– consistency with microeconomic theory
– marginal rates of technical substitution
– relative marginal rates of technical substitution
Tuesday afternoon
• elasticities of substitution in case of two inputs
• elasticities of substitution in case of more than two inputs
• elasticities of substitution in linear production functions
• elasticities of substitution in Cobb-Douglas production functions
Wednesday morning
• Translog production function
– specification
– estimation
– observed and predicted output quantities
– marginal products
– partial output elasticities
– elasticities of scale
– optimal firm size
– consistency with microeconomic theory
– comparison to Cobb-Douglas functional form
Wednesday afternoon
• profit maximisation
• checking conditions for profit maximisation
• cost minimisation
• checking conditions for cost minimisation
• derived input demand functions and output supply functions
• derived price elasticities of input demand and output supply
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Thursday morning
• cost functions and their properties
• Shepard’s lemma
• Cobb-Douglas cost function
– specification
– estimation
– marginal costs
– cost flexibility, elasticity of size, and elasticity of scale
– consistency with microeconomic theory
Thursday afternoon
• Cobb-Douglas cost function (continued)
– imposing homogeneity in input prices
– derived input demand functions
– derived input demand elasticities and their properties
– marginal costs, average costs and total costs curve
• short-run cost functions
• Translog cost functions
Friday morning
• stochastic frontier analysis
• error components frontier
• stochastic frontier production function
• measuring technical (in)efficiency
• Cobb-Douglas stochastic frontier production function
• Translog stochastic frontier production function
• efficiency effects stochastic production frontier
• Cobb-Douglas efficiency effects stochastic production frontier
• stochastic cost frontiers
Friday afternoon
• technical change
• decomposition of changes of total factor productivity
• summing up
• farewell
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Course Literature
• Chambers, RG (1988): Applied Production Analysis – A Dual Approach, Cambridge
University Press.
• Henningsen, A (2012): Introduction to Econometric Production Analysis with R, unpublished
lecture notes, University of Copenhagen (will be provided to the participants
as PDF file).
Assessment, Work Load, and ECTS
The participants will get a (voluntary) homework assignment that they can send to the teacher
no later than four weeks after the course. In case of a positive assessment of the homework
assignment, the participants will get a certificate that they passed this MSc-level course and
that it had a work load of 70 hours, which corresponds to 2.5 ECTS credit points.
PhD students can alternatively choose to write a short paper, where they analyse an own
data set with the methods that they learned in the course. If they send the paper to the
teacher no later than three months after the course and their paper is positively assessed, they
will get a certificate that they passed this PhD-level course and that it had a work load of
170 hours, which corresponds to 6 ECTS credit points.
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