Program

All sessions will be at :
Bloemstraat 36, Room BL.0018

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Tuesday Sept. 7
Wednesday Sept. 8
Thursday Sept. 9
Friday Sept. 10
9.15 - 12.45
Tutorials
Formal Methods and Philosophy of Public Policy

Luc Bovens
Changes in preferences

Sven Ove Hansson

Evolutionary game theory, the replicator dynamics and the social network approach

Jason Alexander

The Ethical Bases of Normative Economics

Prasanta K. Pattanaik

Lunch

13.45 - 15.15
Uppsala visits Groningen

Karl Pettersson
Normal and Non-Normal Deontic Logic: A Mixed Solution

Comments by:
Barteld Kooi
Davide Grossi (Amsterdam)
Karin Enflo
Measuring Opportunity
Comments by:
Martin van Hees
Constanze Binder

Per Algander
How extensive are our duties to benefit future
generations?


Comments by:
Bouwdewijn de Bruin
Peter Timmerman

Erik Carslon
Generalized Extensive Measurement for Lexicographic Orders

Comments by:
Prasanta K. Pattanaik
Break

15.30 - 17.00
Groningen visits Uppsala

Allard Tamminga
Deontic Logic for Strategic Games
Comments by:
Karl Pettersson
Kent Hurtig


Constanze Binder
Diversity Revealed
Comments by:
Karin Enflo
Per Algander

Martin van Hees & Matthew Braham
Responsibility in Games
Comments by:
Kent Hurtig
Erik Carlson

 
Invited Lecturers and Tutoral Program

 

Luc Bovens
Luc Bovens - London School of Economics

 

Formal Methods and Philosophy of Public Policy


I will present a smorgasbord of new and unpublished ideas that are unrelated, yet all at the intersection of Philosophy of Public Policy, Modelling and Statistics. I invite participants to think along with me about these topics. If you have a special interest in any of the topics, feel free to contact me at L.Bovens@LSE.ac.uk.The tutorial will be divided in three parts:

Part 1: Ethics, Risk and Public Works: An Economic Model of Optimal Risk Reduction
(Joint work with Marc Fleurbaey)
A public works programme requires that a number of more and less hazardous tasks are being performed by a number of different people over a period of time. Now we wish to minimise the risk to the workers involved in the programme. But what does this mean? Even if we constrain ourselves to the risk of death, there are multiple interpretations of the ideal of risk minimisation. Do we wish to minimize the number of expected deaths amongst workers? Do we wish to reduce the risk that is imposed on the most vulnerable workers? Do we wish to minimise the chance that even one worker dies? Do we wish to minimise the chance that more than an acceptable threshold of deaths will occur? These all constitute different ideals of risk minimisation. When we invest in risk minimisation, we need to take into account certain technological constraints. Some investments may be highly effective in that they make substantial reductions to the risk involved in certain tasks, whereas other investment decisions may be less effective in doing so. We construct a mathematical model to determine how we should allocate investments to reduce the spread of risk, given a particular technology and given particular ideal of risk minimisation.

Part 2: Error Statistics versus Bayesian Statistics for Two-By-Two Contingency Tables
Let there be two medicines, M1 and M2. We randomly assign patients to equal-sized groups treated by respectively M1 and M2 and conduct a double blind study. The outcome of the experiment is either recovery or non-recovery for each patient. The results of our experiment are expressed in 2-by-2 contingency tables. I construct all the possible pairs of evidence on which there are more recoveries in the M1 group than in the M2 group, i.e. all the pairs {i, j} with i being the number of recoveries on M1, j being the number of recoveries on M2 and i > j. I first analyse these pairs of evidence by means of Fisher's Exact Test, determine the p-value for each set of evidence, and construct an ordering over the pairs of evidence based on these p-values. Subsequently, I analyse these pairs of evidence by determining the posterior probability that M1 is more effective than M2 by means of Bayesian updating, starting from uniform priors, and construct an ordering over these pairs based on these posterior probabilities. My question is: How do these orderings compare?

Part 3: Measuring Fairness and Equal-Burden Sharing in EU Asylum Policy
(Joint work with Irini Moustaki and Laura Smead)
The data provided by the United Nations High Commissioner for Refugees provides information about numbers of asylum applicants and acceptance rates from particular countries of origin to the particular EU member states and number of acceptances over particular time periods. To avoid 'asylum shopping' - i.e. the practice of choosing member states that yield the highest chances of acceptance - the EU has tried over the last decade to develop a fair and equitable common European asylum policy. There are various ideals that such a policy might want to satisfy. What has gone largely unnoticed is that these ideals are not always jointly implementable. We construct measures of these ideals that can be applied to UNHCR data on a year by year basis. We can then examine how various policy changes have affected the distance of EU outcome data from these ideals. The field raises interesting moral and conceptual questions and poses interesting challenges of measurement and multivariate data analysis. It is also timely in that it responds to urgent policy challenges in EU politics.

 

Sven Ove Hansson
Sven Ove Hansson - Royal Institute of Technology, Stockholm

Changes in preferences


Handout

This tutorial will cover the following topics:

1. What is preference change? How do we express it in formal language? Different options for representation are discussed, but the main focus will be on representations that are fairly close to the AGM model in belief revision (that is also briefly introduced). Important differences between preferences and beliefs that require differences in the formal representation will be pointed out.

2. What is the relation between holistic preference change (changes in preferences referring to possible worlds) and changes referring to smaller entities? Can preferences referring to smaller entities be derived from preferences over possible worlds, and in that case how? Can changes on one of the two levels be reduced to changes on the other?

3. A combined framework containing both preference change and belief change is presented. This is a report from ongoing work dealing with questions such as: Can all preference changes be reconstructed as changes in beliefs? Can belief change and preference change basically independent of each other?


 

Jason M. Alexander
Jason M. Alexander - London School of Economics


Evolutionary game theory, the replicator dynamics and the social network approach

(Provisional abstract) In the firs part of the tutorial I will give a general introduction to evolutionary game theory and the replicator dynamics, looking at, for example, Skyrms' work from Evolution of the Social Contract. I will then identify a number of formal difficulties he encounters with the replicator dynamics. In the second part of the tutorial I will show how the social network approach is better able to address those formal difficulties.


Prasanta K. Pattanaik -
UC, Riverside

The Ethical Bases of Normative Economics

The tutorial will have two parts. The first part will develop a formal framework for distinguishing and analysing different types of value judgements that may be relevant for normative economics; the presentation here will be based on some current work by Yongsheng Xu and Prasanta K. Pattanaik. The second part of the tutorial will deal with one specific development in normative economics, namely, the functioning and capability approach to the notion of individual well-being. In particular, the second part will focus on the problem of aggregation involved in the notion of individual well-being in the functioning approach and some issues relating to the concept of capability in the context of strategic interaction among individuals.