GY428      Half Unit
Applied Quantitative Methods

This information is for the 2013/14 session.

Teacher responsible

Prof Kenneth Benoit and Dr Benjamin Groom

Availability

This course is compulsory on the MSc in Environmental Economics and Climate Change. This course is available on the MSc in Local Economic Development and MSc in Real Estate Economics and Finance. This course is available with permission as an outside option to students on other programmes where regulations permit.

Course content

This course will provide an introduction to quantitative methods in use in modern environmental and resource economics. Emphasis will be placed on the practical use of empirical tools. This applied focus will be complemented by the investigation of assumptions and proofs that can improve the understanding of empirical results. A number of relevant applications making use of computers will be presented and, in doing so, use of a wealth of interesting and topical environmental data sets will be made. To this end, ten seminars of one hour each will be provided. During the seminars the students will gain understanding of the software STATA. Additionally, in some of the seminars, selected papers in quantitative environmental economics will be critically discussed. Again the focus will be on relevant empirical papers published in the area. The module will cover several estimators. We will start with the standard linear regression model, its assumptions, violations and testing procedures. Extensions of the Linear regression model (e.g. Two Stages Least Squares and Panel Data) will be also covered. Non Linear Models will also be presented. These include Poisson Regression; Probit; Logit; Selection Models (Maximum Likelihood); Multivariate Probit and Logit; Conditional Logit and Mixed Logit Models.

Teaching

20 hours of lectures and 10 hours of seminars in the MT.

Indicative reading

Detailed reading lists will be provided to support each course component. The
following texts will be particularly useful: Stock J.H. and M.W. Watson. Introduction to Econometrics. Second
Edition Pearson International Editionb J. Wooldridge, Introductory Econometrics, Thomson. Bockstael, N. E., K. E. McConnell. Environmental and Resource Valuation with
Revealed Preferences: A Theoretical Guide to Empirical Models. Springer. 2006 Grossman, Gene and Alan B. Krueger (1995), Economic Growth and the
Environment, Quarterly Journal of Economics, 110(2), 353- 377. Black, Dan A. and Thomas J. Kniesner (2003), On the Measurement of Job Risk
in Hedonic Wage Models, Journal of Risk and Uncertainty, 27 (3), 205-20.Greenstone, M. (2002), The impacts of environmental regulations on industrial
activity: Evidence from the 1970 and 1977 Clean Air Act Amendments and the
Census of Manufacturers, Journal of Political Economy 110, 1175-1219 Hellerstein, D. (1991). Using count data models in travel cost analysis with
aggregate data, American Journal of Agricultural Economics. 73:860-867.Christa N. Brunnschweiler and Erwin H. Bulte (2008). The resource curse
revisited and revised: A tale of paradoxes and red herrings Journal of
Environmental Economics and Management Bateman, I., Carson, R.T., Day, B., Hanemann, M., Hanley, N., Hett, T.,
Jones-Lee, M., Loomes, G., Mourato, S., Ozdemiroglu, E., Pearce, D.W., Sugden,
R., and Swanson, J. (2002) Economic Valuation with Stated Preference Techniques:
A Manual. Edward Elgar, Cheltenham. Haab, T.C. and McConnell, K.E. (2002) Valuing Environmental and Resource
Economics: The Econometrics of Non-Market Valuation, Edward Elgar, Cheltenham.

Assessment

Exam (100%, duration: 2 hours) in the main exam period.

Student performance results

(2011/12 combined)

Classification % of students
Distinction 18.4
Merit 39.5
Pass 23.7
Fail 18.4

Key facts

Department: Geography & Environment

Total students 2012/13: 32

Average class size 2012/13: 16

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills