GY526      Half Unit
Advanced Methods in Environmental and Resource Economics: Time, Risk and Environmental Policy

This information is for the 2018/19 session.

Teacher responsible

Dr Antony Millner TW2 Grantham Research Institute and Dr Benjamin Groom STC 420

Availability

This course is available on the MPhil/PhD in Environmental Economics. This course is available with permission as an outside option to students on other programmes where regulations permit.

A strong background in economics is required to take this course for credit. A Master's degree in economics or equivalent will usually be required. Students from the MSc in Environmental Economics and Climate Change and those enrolled on GY426: Environmental and Resource Economics are allowed to audit the course.

Pre-requisites

The course will be core training for the PhD in Environmental Economics. A background in Economics is therefore required to take this course. Students taking the MSc in Environmental Economics and Climate Change or students enrolled on the GY426: Environmental and Resource Economics can audit the course.

Course content

Many of the most important environmental problems require us to choose between policy options with very uncertain, very long-run, consequences.  Climate change provides an archetypal example, but this is also true of e.g. biodiversity loss and the decline in global fisheries.  This half unit course will introduce you to the decision tools economists use to inform long-run, uncertain, policy choices.  We will critically examine these tools, and how they are applied in environmental economics.  The aim is to provide you with enough technical background to be able to read current research papers in the field, evaluate their claims for yourself, and begin to formulate your own research questions.  Topics will include intertemporal choice and discounting, risk, uncertainty and learning, catastrophes, and some more advanced discussion of dynamic optimization.  We will connect some of the economics literature on these topics to parallel discussions in philosophy.  We will illustrate the theory we cover with applications to common-pool resource problems, climate change, and renewable and exhaustible resource management.

There will be 5 x 2 hour lectures:

1) Inter-temporal Decision Making;

2) Risk and Uncertainty;

3) Information and Learning;

4) The Economics of Catastrophes;

5) Elements of Dynamic Optimisation.

Teaching

10 hours of lectures and 5 hours of seminars in the LT.

There will be 5 x 2 hour lectures:

1) Inter-temporal Decision Making;

2) Risk and Uncertainty;

3) Information and Learning;

4) The Economics of Catastrophes;

5) Elements of Dynamic Optimisation.

Formative coursework

Students will be expected to produce 5 problem sets in the LT.



Formative coursework will take the form of a problem set each week.

Indicative reading

Human well-being and the natural environment. Partha Dasgupta, Oxford University Press, 2004; Valuing the Future: Economic Theory and Sustainability. Geoffrey Heal, Columbia University Press. 2000; Pricing the Planet's Future. Christian Gollier, Princeton University Press, 2012; Intergenerational Equity. Geir Asheim, Annual Review of Economics. volumer 2, 197-222; On Second-Best National Saving and Game Equilibrium Growth. E. Phelps and R. Pollak, Review of Economic Studies; The Economics of Risk and Time, Christian Gollier. MIT Press, 2004; Theories of Decision under Uncertainty. Itzhak Gilboa, Econometrics Society Monograph. 2009.

 




 

Assessment

Project (100%, 5000 words) in the ST.

The summative assessment project counts for 100% of the overall grade for the course. This project will test understanding of the theoretical methods and their application to real world problems.

Key facts

Department: Geography & Environment

Total students 2017/18: 3

Average class size 2017/18: 4

Lecture capture used 2017/18: Yes (LT)

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of numeracy skills
  • Specialist skills