Aggregating infinitely many probability measures

Herzberg F (2014) Center for Mathematical Economics Working Papers; 499.
Bielefeld: Center for Mathematical Economics.

Diskussionspapier | Veröffentlicht | Englisch
 
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Autor*in
Herzberg, Frederik
Abstract / Bemerkung
The problem of how to rationally aggregate probability measures occurs in particular (i) when a group of agents, each holding probabilistic beliefs, needs to rationalise a collective decision on the basis of a single ‘aggregate belief system’ and (ii) when an individual whose belief system is compatible with several (possibly infinitely many) probability measures wishes to evaluate her options on the basis of a single aggregate prior via classical expected utility theory (a psychologically plausible account of individual decisions). We investigate this problem by first recalling some negative results from preference and judgment aggregation theory which show that the aggregate of several probability measures should not be conceived as the probability measure induced by the aggregate of the corresponding expected-utility preferences. We describe how McConway’s (Journal of the American Statistical Association, vol. 76, no. 374, pp. 410– 414, 1981) theory of probabilistic opinion pooling can be generalised to cover the case of the aggregation of infinite profiles of finitely-additive probability measures, too; we prove the existence of aggregation functionals satisfying responsiveness axioms à la McConway plus additional desiderata even for infinite electorates. On the basis of the theory of propositional-attitude aggregation, we argue that this is the most natural aggregation theory for probability measures. Our aggregation functionals for the case of infinite electorates are neither oligarchic nor integral-based and satisfy (at least) a weak anonymity condition. The delicate set-theoretic status of integral-based aggregation functionals for infinite electorates is discussed.
Stichworte
probabilistic opinion pooling; general aggregation theory; Richard Bradley; multiple priors; Arrow’s impossibility theorem; Bayesian epistemology; society of mind; finite anonymity; ultrafilter; measure problem; non-standard analysis
Erscheinungsjahr
2014
Serientitel
Center for Mathematical Economics Working Papers
Band
499
Seite(n)
20
ISSN
0931-6558
Page URI
https://pub.uni-bielefeld.de/record/2675331

Zitieren

Herzberg F. Aggregating infinitely many probability measures. Center for Mathematical Economics Working Papers. Vol 499. Bielefeld: Center for Mathematical Economics; 2014.
Herzberg, F. (2014). Aggregating infinitely many probability measures (Center for Mathematical Economics Working Papers, 499). Bielefeld: Center for Mathematical Economics.
Herzberg, Frederik. 2014. Aggregating infinitely many probability measures. Vol. 499. Center for Mathematical Economics Working Papers. Bielefeld: Center for Mathematical Economics.
Herzberg, F. (2014). Aggregating infinitely many probability measures. Center for Mathematical Economics Working Papers, 499, Bielefeld: Center for Mathematical Economics.
Herzberg, F., 2014. Aggregating infinitely many probability measures, Center for Mathematical Economics Working Papers, no.499, Bielefeld: Center for Mathematical Economics.
F. Herzberg, Aggregating infinitely many probability measures, Center for Mathematical Economics Working Papers, vol. 499, Bielefeld: Center for Mathematical Economics, 2014.
Herzberg, F.: Aggregating infinitely many probability measures. Center for Mathematical Economics Working Papers, 499. Center for Mathematical Economics, Bielefeld (2014).
Herzberg, Frederik. Aggregating infinitely many probability measures. Bielefeld: Center for Mathematical Economics, 2014. Center for Mathematical Economics Working Papers. 499.
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2019-09-06T09:18:23Z
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