{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/85530"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/85530","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The Pricing Strategy of a Bayesian Learning Monopolistic Insurer","abstract":"Much of the standard literature on adverse selection insurance models assumes that the only unknown parameter is the accident probability and that all consumers have the same level of risk aversion. This paper relaxes these two assumptions by allowing consumers to have different levels of risk aversion, which the insurer has no prior knowledge of these levels of risk aversion when meeting consumers for the first time. Using Bayesian learning a monopolistic insurer tries to learn a consumer's level of risk aversion. This paper shows that an insurer who learns in the two-type consumer model offers either separating contracts to the two different types of consumer or does not insure one of the types of consumer. This result is identical to the result in Stiglitz (1977) where he assumes that the monopolistic insurer has prior knowledge of a consumer's level of risk aversion. However, the insurer who learns offers different contracts when compared to the insurer who knows a consumer's level of risk aversion. By offering different contracts than the insurer who knows a consumer's level of risk aversion, the insurer who learns earns less expected profit than the insurer who knows a consumer's level of risk aversion. Monte Carlo simulation results show that the expected percentage loss in profit is significantly larger than the corresponding expected percentage changes in prices and coverage of the insurance contracts as a result of the insurer learning the levels of risk aversion of the two different types of consumer.","abstract_html":"Much of the standard literature on adverse selection insurance models assumes that the only unknown parameter is the accident probability and that all consumers have the same level of risk aversion. This paper relaxes these two assumptions by allowing consumers to have different levels of risk aversion, which the insurer has no prior knowledge of these levels of risk aversion when meeting consumers for the first time. Using Bayesian learning a monopolistic insurer tries to learn a consumer's level of risk aversion. This paper shows that an insurer who learns in the two-type consumer model offers either separating contracts to the two different types of consumer or does not insure one of the types of consumer. This result is identical to the result in Stiglitz (1977) where he assumes that the monopolistic insurer has prior knowledge of a consumer's level of risk aversion. However, the insurer who learns offers different contracts when compared to the insurer who knows a consumer's level of risk aversion. By offering different contracts than the insurer who knows a consumer's level of risk aversion, the insurer who learns earns less expected profit than the insurer who knows a consumer's level of risk aversion. Monte Carlo simulation results show that the expected percentage loss in profit is significantly larger than the corresponding expected percentage changes in prices and coverage of the insurance contracts as a result of the insurer learning the levels of risk aversion of the two different types of consumer.","abstract_has_math":false,"creators":["Barber, Kevin D."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Economics","degree_department":null,"school":null,"contributors":["Stefan Krasa"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003","date_published":"2003","updated_at":"2026-07-22T22:26:25Z","subjects":["Economics, Theory"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3086009"],"render_values":[{"text":"(MiAaPQ)AAI3086009","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/85530","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Stefan Krasa"]},{"key":"dc:creator","label":"Author","values":["Barber, Kevin D."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2003","2015-09-25T22:47:15Z","10000-01-01"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Economics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Economics, Theory"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/85530","(MiAaPQ)AAI3086009"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Much of the standard literature on adverse selection insurance models assumes that the only unknown parameter is the accident probability and that all consumers have the same level of risk aversion. This paper relaxes these two assumptions by allowing consumers to have different levels of risk aversion, which the insurer has no prior knowledge of these levels of risk aversion when meeting consumers for the first time. Using Bayesian learning a monopolistic insurer tries to learn a consumer's level of risk aversion. This paper shows that an insurer who learns in the two-type consumer model offers either separating contracts to the two different types of consumer or does not insure one of the types of consumer. This result is identical to the result in Stiglitz (1977) where he assumes that the monopolistic insurer has prior knowledge of a consumer's level of risk aversion. However, the insurer who learns offers different contracts when compared to the insurer who knows a consumer's level of risk aversion. By offering different contracts than the insurer who knows a consumer's level of risk aversion, the insurer who learns earns less expected profit than the insurer who knows a consumer's level of risk aversion. Monte Carlo simulation results show that the expected percentage loss in profit is significantly larger than the corresponding expected percentage changes in prices and coverage of the insurance contracts as a result of the insurer learning the levels of risk aversion of the two different types of consumer.","Made available in DSpace on 2015-09-25T22:47:15Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3086009.pdf: 6438965 bytes, checksum: 824cbf20ea13f4d2a1465b6c76519494 (MD5) Previous issue date: 2003","Embargo set by: Seth Robbins for item 86811 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","150 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003."]},{"key":"dc:title","label":"Title","values":["The Pricing Strategy of a Bayesian Learning Monopolistic Insurer"]}]}],"canonical_facts":{"dc:contributor":["Stefan Krasa"],"dc:creator":["Barber, Kevin D."],"dc:date":["2003","2015-09-25T22:47:15Z","10000-01-01"],"dc:description":["Much of the standard literature on adverse selection insurance models assumes that the only unknown parameter is the accident probability and that all consumers have the same level of risk aversion. This paper relaxes these two assumptions by allowing consumers to have different levels of risk aversion, which the insurer has no prior knowledge of these levels of risk aversion when meeting consumers for the first time. Using Bayesian learning a monopolistic insurer tries to learn a consumer's level of risk aversion. This paper shows that an insurer who learns in the two-type consumer model offers either separating contracts to the two different types of consumer or does not insure one of the types of consumer. This result is identical to the result in Stiglitz (1977) where he assumes that the monopolistic insurer has prior knowledge of a consumer's level of risk aversion. However, the insurer who learns offers different contracts when compared to the insurer who knows a consumer's level of risk aversion. By offering different contracts than the insurer who knows a consumer's level of risk aversion, the insurer who learns earns less expected profit than the insurer who knows a consumer's level of risk aversion. Monte Carlo simulation results show that the expected percentage loss in profit is significantly larger than the corresponding expected percentage changes in prices and coverage of the insurance contracts as a result of the insurer learning the levels of risk aversion of the two different types of consumer.","Made available in DSpace on 2015-09-25T22:47:15Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3086009.pdf: 6438965 bytes, checksum: 824cbf20ea13f4d2a1465b6c76519494 (MD5) Previous issue date: 2003","Embargo set by: Seth Robbins for item 86811 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","150 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2003."],"dc:identifier":["http://hdl.handle.net/2142/85530","(MiAaPQ)AAI3086009"],"dc:language":["eng"],"dc:subject":["Economics, Theory"],"dc:title":["The Pricing Strategy of a Bayesian Learning Monopolistic Insurer"],"dc:type":["text"],"thesis:degree_discipline":["Economics"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:25Z"}