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DRPS : Course Catalogue : School of Geosciences : Postgraduate Courses (School of GeoSciences)

Postgraduate Course: Environmental Valuation (PGGE11223)

Course Outline
SchoolSchool of Geosciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThe purpose of this course is to provide students with a largely comprehensive introduction to the economic valuation of environmental resources and policies. The course will cover both key elements of economic theory that are needed to understand the methodologies covered, and an introduction to the analysis of data. The methods covered are of direct relevance to policy formulation, ecosystem service valuation, and cost-benefit analysis, though students will be encouraged to pursue reading on the theme of most interest to them.
By the end of the course, students will have insight into what economic valuation methods exist, the theory on which they rely, what form the data collected for these methods takes, and how data analysis can be conducted across a range of methods. This course will prepare students to pursue several paths, including each of the following: further development of environmental valuation skills and their application within cost-benefit analysis (or potentially multi-criteria analysis), the study of non-economic concepts and forms of value, critiquing the use of valuation methods, and the development of dissertations featuring environmental valuation.
Course description Week 1 . Introduction to Course
This week will introduce students the course, and how it will be run. It will also introduce students to the concept of economic valuation, and why it is important for them to learn about it.

Week 2. Market valuation of environmental resources
This week will introduce what economic values are and focus on markets, how they function, and on the contexts where market data is useful for valuing environmental resources.

Week 3. Introduction to R
This week will provide and introduction to the R software and do some practical exercises in R.

Week 4. Travel Cost Method
This week will be dedicated to the understanding of Travel Cost Method (TCM) and TCM data analysis.

Week 5. Contingent Valuation Method
This week will be dedicated to the understanding of the contingent valuation method (CVM) and CVM data analysis.

Week 6. Choice Experiments I
This week will introduce Choice Experiments (CE) and focus on understanding how to design a CE.

Week 7. Choice Experiments II
This week will focus on the CE essay and the analysis of a CE dataset that will be the basis for the essay.

Week 8. Benefits Transfer
In this week students will learn about the pros and cons of different ways of conducting benefits transfer , conduct examples of simple transfers and be introduced to meta-analysis.

Week 9. Topical applications to valuation of environmental goods and services
This week will focus on the use of valuation across different contexts and policy applications.

Week 10. Non-Monetary Valuation
This week will summarise current literature and explore non-monetary valuation methods.

Week 11. Deliberative Valuation
This week will introduce and explore the concept of deliberation with respect to valuation.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs No
Course Delivery Information
Academic year 2021/22, Not available to visiting students (SS1) Quota:  40
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 48, Feedback/Feedforward Hours 3, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 145 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Understand key features of (and the primary elements of economic theory behind) the most common environmental valuation methods used in economic analyses.
  2. Have acquired foundational skills in the analysis of environmental valuation data in R.
  3. Understand how the methods covered in class have been applied to policy areas of individual interest.
  4. Have authored mini - journal articles, demonstrating data analysis and interpretation skills.
  5. Have a solid basis for understanding and judging the quality of environmental valuation methods as applied by others in various contexts.
Reading List
Students will be given specific packets of introductory reading to do before each class. Some of this reading may take the form of tutorial booklets, and some of this reading will take the form of book chapters or journal articles. The use of pre-reading will facilitate the use of class time for looking at data and data analysis

Additionally, and for reference, the following companion text books are relevant for students to consult
Pricing Nature by Hanley and Barbier, available as an e book through the SRUC library
Economic Valuation using Stated Preference Methods: a manual by Bateman et al

A good, slightly more technical introduction into non-market valuation methods:
A Primer on Nonmarket Valuation by PA Champ, KJ Boyle and TC Brown

R will be introduced briefly but this course does not provide systematic learning of R as a tool for statistical analysis. Many introductions to R can be found as pdfs on the web or are available as books. Students may also try free, brief introductory online courses such as . The students will be able to follow the analysis in R through tutorials, and are encouraged to use this as a foundation to familiarising themselves with R

. In addition to the assigned pre-class readings, students will be required to consult peer-reviewed journal articles for their assignment and capstone project. Students are responsible for finding these journal articles and will also be responsible for balancing the reading of these articles with the required pre-class reading. It is recommended that students read about these methods throughout the course.

Additional Information
Course URL
Graduate Attributes and Skills Students will gain a semester of working in R
for data analysis
- Critiquing the quality of peer-reviewed studies
- Conducting and writing up the analysis of primary quantitative data
- Production of original, written arguments
- Linking primary research to policy questions/decision contexts
Study Abroad No
KeywordsEcological Economics,Ecosystem Services,Environmental Valuation
Course organiser Course secretaryMs Jennifer Gumbrell
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