11/3/08 1 SYLLABUS Fall 2008 ENVR 890-007: Methods of Environmental Decision Analysis Time and location: Monday, Wednesday, Friday, 10:00 – 10:50 a.m., Michael Hooker 0015 Instructors: Jackie MacDonald (Rosenau 162B) and Jason West (Rosenau 164) Email addresses: [email protected], [email protected] Office hours: After class, 11:00 – 12:00 Course Description and Goals Decisions involving environmental resources and environmental health require both technical input and a complex balancing of outcomes, priorities, and uncertainties. This course will introduce students to tools for balancing conflicting priorities (such as costs versus human health protection) and evaluating uncertainties when making environmental decisions, either in government agencies or private industry. Course materials will span the range of environmental problems, from hazardous waste disposal to climate change. Students will learn to apply tools from engineering and business to evaluate alternative options for environmental protection. The course will emphasize the construction of quantitative, mechanistic computer models that can be used to compare the costs and benefits of alternative decisions under uncertainty. No previous programming experience is required. Students will learn to build decision models using spreadsheet add-on tools (PrecisionTree and @Risk) and stand-alone software (Analytica). Topics to be covered, in addition to model construction, will include cost accounting, time discounting of costs, uncertainty and sensitivity analysis, subjective probability, value of information, risk perception, human biases in risk perception, utility maximization, multi-attribute utility theory, and linear programming. The goal of the course is to learn how to provide structure to “messy” decision problems. By the end of the course, students will have learned new methods and tools for structuring such problems and providing advice on alternative choices to decision-makers. Prerequisites This graduate-level course is targeted toward students with technical backgrounds who are interested in applying their work for environmental management and policy. There are no prerequisites, although familiarity with spreadsheets and with probability theory will be helpful. Undergraduates will be admitted only with permission of the instructors.11/3/08 2 Course Requirements and Evaluation Class participation 10% Four quizzes (each 10%) 40% Homework assignments 35% Group project and presentation 15% 100% There is no final exam. Instead, the final exam period will be used for presentation of the group projects. There will be approximately nine homework assignments over the course of the semester. Homework must be turned in on time. You will lose 10% on your homework grade for each day that the assignment is late, except in very exceptional circumstances and with the prior approval of the instructors. You are encouraged to work in groups. However, each student is responsible for turning in his or her own results for their homework. If you do work with others, you are required to include a note on your homework with the names of the people you work with. Working with others does not count against you, but you will lose 20 points if you fail to acknowledge your collaborators. Textbooks Two textbooks are required: 1. Making Hard Decisions (With DecisionTools), by Robert T. Clemen and Terence Reilly, Duxbury, 2001. 2. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, by M. Granger Morgan and Max Henrion, Cambridge University Press, 1990. In addition, the following text is optional (but recommended): 3. Rational Choice in an Uncertain World: The Psychology of Judgment and Decision Making, by Reid Hastie and Robyn Dawes, Sage, 2001. Additional Readings Periodically throughout the semester, we will distribute readings from technical journals. You are expected to read these articles for discussion during the next class period.11/3/08 3 Course Schedule (subject to updates) Please complete the readings before each class. LECTURES READING Week Lecture Date Instructor Topic Clemen & Reilly Morgan & Henrion Other 1 1 Wed 8/20 MacDonald and West Why study decision analysis? 2 Fri 8/22 MacDonald Structuring decision models Chs.1-2 Gregory et al., 2006; Gregory et al., 2005 2 3 Mon 8/25 MacDonald Using decision models to make choices Ch. 3 pp. 43-82 Chs. 1-2 4 Wed 8/27 MacDonald Decisions with multiple objectives Ch. 4, pp. 111 - 146 Ch. 3 5 Fri 8/29 MacDonald Software tools for constructing decision models Ch. 3, pp. 83-91; Ch. 4, pp. 147-161 3 6 Wed 9/3 West Decisions involving financial consequences: time value of money Pp. 30-33 Hand-outs 7 Fri 9/5 West Time value of money (cont'd) Hand-outs11/3/08 4 LECTURES READING Week Lecture Date Instructor Topic Clemen & Reilly Morgan & Henrion Other 4 8 Mon 9/8 West Valuing nonmarket goods Hand-outs 9 Wed 9/10 West Decisions involving financial consequences: controversies concerning discount rates Hand-outs 10 Fri 9/12 MacDonald Modeling uncertainty: probability basics Ch. 7 5 11 Mon 9/15 MacDonald Probability basics (cont'd) Ch. 7 12 Wed 9/17 MacDonald and West Review 13 Fri 9/19 QUIZ 1 6 14 Mon 9/22 West Modeling uncertainty: theoretical probability models Ch. 9 Ch. 5, secs. 1-2 15 Wed 9/24 West Theoretical probability models (cont'd) Ch. 9 Ch. 5, sec 4-5 16 Fri 9/26 West Modeling uncertainty: estimating parameters for probability models Ch. 10 Ch. 5, sec 3 7 17 Mon 9/29 West Parameter estimation (cont'd) Ch. 10 Ch. 5, sec 611/3/08 5 LECTURES READING Week Lecture Date Instructor Topic Clemen & Reilly Morgan & Henrion Other 18 Wed 10/1 MacDonald Modeling uncertainty: subjective probability Ch. 8 Hastie and Dawes, Chapters 3-5 19 Fri 10/3 MacDonald Subjective probability: expert elicitation Chs. 6-7 Hastie and Dawes, Chapters 6-7; MacDonald et al., 2008 8 20 Mon 10/6 West Monte Carlo simulation: introduction Ch. 11 Hand-outs 21 Wed 10/8 West Monte Carlo simulation: examples in environmental context Ch. 10 22 Fri 10/10 MacDonald Monte Carlo simulation: Analytica and other software tools Hand-outs 9 23 Mon 10/13 MacDonald Sensitivity and uncertainty analysis Ch. 5 24 Wed 10/15 MacDonald
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