Insurance loss coverage and demand elasticities

MingJie Hao, Angus Smith Macdonald, Pradip Tapadar, R. Guy Thomas

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)
45 Downloads (Pure)


Restrictions on insurance risk classification may induce adverse selection, which is usually perceived as a bad outcome. We suggest a counter-argument to this perception in circumstances where modest levels of adverse selection lead to an increase in ‘loss coverage’, defined as expected losses compensated by insurance for the whole population. This happens if the shift in coverage towards higher risks under adverse selection more than offsets the fall in number of individuals insured. The possibility of this outcome depends on insurance demand elasticities for higher and lower risks. We state elasticity conditions which ensure that for any downward-sloping insurance demand functions, loss coverage when all risks are pooled at a common price is higher than under fully risk-differentiated prices. Empirical evidence suggests that these conditions may be realistic for some insurance markets.
Original languageEnglish
Pages (from-to)15-25
Number of pages11
JournalInsurance: Mathematics and Economics
Early online date13 Dec 2017
Publication statusPublished - Mar 2018


  • Adverse selection
  • Loss coverage
  • Elasticity of demand
  • Arc elasticity of demand
  • Heterogeneous risk preferences


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