Loss Coverage: Why Insurance Works Better With Some Adverse Selection - Tapa blanda

Thomas, Guy

 
9781107495906: Loss Coverage: Why Insurance Works Better With Some Adverse Selection
Tapa blanda
ISBN 10: 1107495903 ISBN 13: 9781107495906
Editorial: Cambridge University Press, 2017

Sinopsis

Most academic and policy commentary represents adverse selection as a severe problem in insurance, which should always be deprecated, avoided or minimised. This book gives a contrary view. It details the exaggeration of adverse selection in insurers' rhetoric and insurance economics, and presents evidence that in many insurance markets, adverse selection is weaker than most commentators suggest. A novel arithmetical argument shows that from a public policy perspective, 'weak' adverse selection can be a good thing. This is because a degree of adverse selection is needed to maximise 'loss coverage', the expected fraction of the population's losses which is compensated by insurance. This book will be valuable for those interested in public policy arguments about insurance and discrimination: academics (in economics, law and social policy), policymakers, actuaries, underwriters, disability activists, geneticists and other medical professionals.

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Acerca del autor

Guy Thomas is an actuary and investor, and an honorary lecturer at the University of Kent, Canterbury. His academic publications have received prizes from the Institute and Faculty of Actuaries and the International Actuarial Association. He is also the author of Free Capital: How Twelve Private Investors Made Millions in the Stock Market.

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Editorial
Cambridge University Press
Año de publicación
2017
Idioma
Inglés
ISBN 10 
1107495903
ISBN 13 
9781107495906
Encuadernación
Tapa blanda
Número de páginas
284
Contacto del fabricante
no disponible
Persona responsable
Avery
https://www.avery.fr/

chemin des peupliers 27
Dardilly
Francia

Otras ediciones populares con el mismo título

9781107100336: Loss Coverage: Why Insurance Works Better with Some Adverse Selection

Edición Destacada

ISBN 10:  110710033X ISBN 13:  9781107100336
Editorial: Cambridge University Press, 2017
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