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Forecasting the 21st Century: Politics, Business, Technology, Development, Environment, and Conflict.

2023-2024

FrFaculté de Gestion, Economie & Sciences Licences ( FGES LICENCES )

Code Cours :

2324-FGES-DIV-EN-3004


Niveau Année de formation Période Langue d'enseignement 
FrAnglais
Professeur(s) responsable(s)Paul Scott
Intervenant(s)Pas d'autre intervenant

    Ce cours apparaît dans les formations suivantes :
  • Faculté de Gestion, Economie & Sciences - Licences & Prépas - Classe Sup + Licence 3 parcours Economie Finance - S6 - 2 ECTS

Pré requis


None

Objectifs du cours


Forecasting is the capacity to predict future trends and events. This course will examine the variety of tools used by analysts in their attempt to decipher short, medium, and long term trends. Accurate forecasting must be scientific but also avoid the traps of a host of conceptual and behavioral biases. Moreover, extrapolating from the past to project the future can be of value in charting patterns of behavior but this can also lead to disastrous and inaccurate miscalculations. Forecasting is also decision-making and this is another set of challenges revolving around the accuracy of the information received, the process of reporting, time constraints, and structures of authority and responsibility. Risk analysis - which is a whole field in itself, also be examained. And finally, whether one works for McKinsey or the Direction générale de la sécurité extérieure, predicting megatrends is vital. Avoiding disasterous decisions is a prime focus of this class.


Grading: Class attendence and participation: 30%


Final presentation: 70%


Texts: All readings are embedded in the syllabus and available on-line.



Contenu du cours


Weekly topics and readings:




Weeks 1 and 2 : Introducing the course


Why forecast?


What can be forecasted


Examples of good and terrible forecasts, or


how could Madoff’s predictions be believed?


Forecasting methods


https://mech.at.ua/Forecasting.pdf



Week 3 “Black Swans” and how to predict the unpredictable (or how to see what is hidden).


https://www.amati-associates.com/black-swans/






Week 4 Upside and downside risks in economic forecasts.


What is positive risk?


https://hbr.org/2009/10/the-six-mistakes-executives-make-in-risk-management


https://www.huawei.com/minisite/explore/en/forecasting_future.html#:~:text=In%20recent%20years%2C%20the%20term,books%20on%20uncertainty%20and%20probability.&text=To%20have%20a%20gorilla%20imagine,on%20this%20in%20the%20industry.



Week 5 and 6 Perceptual bias and biased reporting.


Stakeholders, the bureaucracy, leadership, decision-making.


Cognitive biases


https://www.visualcapitalist.com/11-cognitive-biases-influence-politics/



Week 7



A look at the Pacific Economic Outlook (PEO) report on forecasts


https://pecc.org/resources/publications/regional-cooperation-1/2608-pecc-apec-2020-vision/file



Note: I was a member of the Pacific Economiuc Outlook Japan Committee which prepared a yearly economic projection. This was a sub-ministerial level structure which reported up to the ministerial level.



Weeks 8 and 9 Presentations



Possible presentation topics:




There are a variety of competitions that you can join regarding stock, housing prices,



Stock market predictions


Predicting commodity prices: oil, copper, frozen orange juice, etc.


The housing bubble: a case study


Forecasting the economic recovery from Covid


The Iraq War - decision-making



Simulations and case studies:


ACER Computer Case Study - Slide Share (https://www.slideshare.net/Fabian8a/acer-china-manufacturing)


Air travel demand forecasting: before and after COVID-19 (https://datascience.aero/air-travel-demand-forecasting-covid-19/)



We must also consider the assumption that events proceed in a logical and contained way but the literature on inadvertent escalation leads us to unhappily conclude that circumstances can easily spin out of control despite our best efforts. The outbreak of World War 1 is a prime example.



There are many case studies in how forecasting and risk analysis have failed. Five examples are: 1) The Cuban Missile Crisis is a case study of how easily so-called logical men could have started a nuclear war. 2) The 2008 Financial Crisis. 3) The recent pandemic. 4) Both the Afghan and Iraq wars.


And finally, insurance companies and their actuarial analysts are experts in analyzing date and calclulating the probability of and costs associated with certain events, such as product failure, accidents, property damage, injury, and death.



Modalités d'enseignement

Organisation du cours

See above

Méthodes pédagogiques


    Évaluation

    Contrôle continu : coeff. 1


    Bibliographie

    • See above


    Ressources internet


    • See above



     
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