Policy-motivated candidates, noisy platforms, and non-robustness

to connected objects

Abstract: "A model of a two-candidate election is developed in which the candidates are mainly office-motivated but also to some arbitrarily small extent policy-motivated, and their chosen platforms are to some arbitrarily small extent noisy. The platforms' being noisy means that if a candidate has chosen a particular platform, the voters' perception is that she has, with positive probability, actually chosen some other platform. It is shown that (1) an equilibrium in which the candidates play pure exists whether or not there is a Condorcet winner among the policy alternatives, and (2) in this equilibrium the candidates choose their ideal points, which means that the platforms do not converge." (author's abstract)

Alternative title: Politikmotivierte Kandidaten, Plattformen mit Rauschen und Nichtrobustheit

Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource, 28 S.

Language: Englisch

Notes: Veröffentlichungsversion

Bibliographic citation: Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Marktprozeß und Unternehmensentwicklung, Abteilung Wettbewerbsfähigkeit und industrieller Wandel ; Bd. 00-17

Classification: Politik

Keyword: Spieltheorie
Noise trading
Arrow-Paradoxon
Theorie
Wahlkampf
Räumliche Konkurrenz

Event: Veröffentlichung

(where): Berlin

(when): 2000

Creator: Lagerlöf, Johan

Contributor: Wissenschaftszentrum Berlin für Sozialforschung gGmbH

URN: urn:nbn:de:0168-ssoar-116248

Rights: Open Access unbekannt; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:54 PM CET

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Show original at data provider

Associated

Lagerlöf, Johan
Wissenschaftszentrum Berlin für Sozialforschung gGmbH

Time of origin

2000

Other Objects (12)

Arbeitspapier

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier | Working paper

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier

Motivated Procrastination

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NOiSy

Arbeitspapier

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier | Working paper

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier

Motivated Procrastination

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NOiSy

Arbeitspapier

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier | Working paper

Policy-motivated candidates, noisy platforms, and non-robustness

Arbeitspapier

Motivated Procrastination

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Hochschulschrift

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

noiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NoiSy

Graffiti | Streetart

NOiSy

Cultural heritage institutions wishing to register will find more information here.

Fields marked * need to be filled in.

Username*

Please enter your username

Email*

Please enter your email address

Please do not fill this field

First name

Last name

Password*

Please enter your password

Confirm password*

Please enter the same password

I have read the terms of use and the privacy policy for the collection of personal data and accept them. *

This field is required.

I would like to subscribe to the newsletter of the Deutsche Digitale Bibliothek. See newsletter subscription info.

Account created

Your "My DDB" account has been successfully created. Before you can log in to your account, you must click the confirmation link in the message we just sent to the email address you provided.

Policy-motivated candidates, noisy platforms, and non-robustness

Object Details

References and Relationships

Classification and Topics

Contributors, Places and Time

Further information

Data provider

Associated

Time of origin

Other Objects (12)

Policy-motivated candidates, noisy platforms, and non-robustness

Policy-motivated candidates, noisy platforms, and non-robustness

Motivated Procrastination

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

noiSy

NoiSy

NoiSy

noiSy

NoiSy

NoiSy

NOiSy

Policy-motivated candidates, noisy platforms, and non-robustness

Policy-motivated candidates, noisy platforms, and non-robustness

Motivated Procrastination

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

noiSy

NoiSy

NoiSy

noiSy

NoiSy

NoiSy

NOiSy

Policy-motivated candidates, noisy platforms, and non-robustness

Policy-motivated candidates, noisy platforms, and non-robustness

Motivated Procrastination

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels

noiSy

NoiSy

NoiSy

noiSy

NoiSy

NoiSy

NOiSy

Related objects

Reset password