International Forecasting and Simulation 2104-M-D1PISM
1. Introduction to international forecasting. Course organization, aims, and learning outcomes.
2. Variable, variable distribution: central tendency and dispersion measures. Correlation and cause-effect relation.
3. a/ Methods and techniques of international forecasting - main concepts, classifications, methods: trend extrapolation, analogy, indicators, time series analysis, barometers, econometric models.
b/ small groups formation and the rules of case studies preparation
4. a/ Heuristic methods and working in small groups.
b/ discussion of case studies proposals provided by small groups
5. Examples of international forecasts. Critical analysis, discussion.
a/ The Limits of Growth
b/ Global Trends 2015
6. Game theory in international forecasting, part 1.
7. Game theory in international forecasting, part 2.
8. Presentation of drafts of forecasts developed by students, part 1.
9. Presentation of drafts of forecasts developed by students, part 2.
10. Heuristics and the most typical errors in inference.
11. Excessive self-confidence as a challenge in forecasting.
12. "Big data" and international forecasting.
13. Presentation of final versions forecasts developed by students, part 1.
14. Presentation of final versions forecasts developed by students, part 2.
15. Wrap-up.
Type of course
Mode
Prerequisites (description)
Course coordinators
Learning outcomes
Student:
- analyzes international reality using forecasting tools
- works in team, knows rules of team work, and strong and weak points of this method
- knows and uses basic rules of statistical inference, identifies typical errors in thinking
- links theoretical knowledge with practical applications, uses theoretical knowledge in analyses
- independently conducts basic research and critically assessed the quality of sources of data
- takes part in discussions, presents his/her point and provides arguments to support it
- systematically observes international life
K_W01, K_W05, K_U01, K_U02, K_U03, K_U04, K_K01, K_K02, K_K05
Assessment criteria
- student is obliged to attend the course and be prepared for every session, twice the student can be absent or/and be unprepared; every additional absence or unpreparedness will adversely affect the final grade
- distinctive contribution to the classes will be rewarded
- preparedness/unpreparedness and presence/absence and distinctive contribution together decide about the overall assessment of student's participation in the course
- the most important part of the grade come from the case study, which will be prepared in small groups and presented at the end of the course.
OPTION 1. In case of good cooperation with a given group, systematic involvement, and good familiarity with readings, grades will be given on the basis of the overall assessment of student's participation in the course + a case study.
OPTION 2: In case of poor cooperation with the group and poor familiarity with readings, the course will end with an exam. In this case grades will be given on the basis of the overall assessment of student's participation in the course + case study + exam.
Bibliography
M. Sułek, „Prognozowanie i symulacje międzynarodowe”, Warszawa 2010.
A. Wojciuk, Metody twórczej pracy grupowej w analizie polityki zagranicznej i dydaktyce stosunków międzynarodowych, w: "Stosunki międzynarodowe", nr 1 -2 (t.43), 2011.
D. Kahneman, "Pułapki myślenia. O myśleniu szybkim i wolnym", Media Rodzina, Warszawa, 2012.
B. Bueno de Mesquita, „The Predictioneer’s Game. Using the Logic of Brazen Self-Interest to See and Shape the Future”, New York: Random House, 2009.
G. Wieczorkowska, A. Wierzbiński, Statystyka. Analiza Badań społecznych, (all editions)
A. Dixit, S. Skeath, „Games of Strategy”, New York/London: Norton & Co. (all editions)
K. Cukier, V. Mayer-Schoenberger, "The Rise of Big Data. How It's Changing the Way We Think About the World", Foreign Affairs, May/June 2013.
Additionally:
G. Allison, P. Zelikow, „Essence of Decision. Explaining the Cuban Missile Crisis”, 2nd edition, Longman, 1999.
N. N. Taleb, „The Balck Swan. The Impact of Highly Improbable”, New York: Random House, 2007.
M. Granger Morgan, M. Henrion, „Uncertainty. A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis”, Cambridge University Press, 1990.
R. Heuer, R. Pherson, „Structured Analytic Techniques for Intelligence Analysis”, CQ Press, 2010.
R. Lempert, S. Popper, S. Bankes, Shaping the next one hundred years : new methods for quantitative, long-term policy analysis, RAND, 2003.
S. Renshon, D. Welch Larson, „Good Judgment in Foeign Policy. Theory and Application”, Oxford: Rowman, 2003.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: