From a public policy perspective, insurance works better with some adverse selection.<\/p>\n
Under adverse selection, restrictions on insurance risk classification (e.g genetic tests, gender, big data) may lead to a rise in average price and a fall in numbers insured (both usually seen as disadvantages).\u00a0 But as a matter of simple arithmetic, they also lead to in a shift in coverage towards higher risks – the ‘right ‘ risks, the people who need insurance most.<\/em> If this shift in coverage is large enough, it can more than out-weigh the fall in numbers insured, so that expected population losses compensated by insurance<\/em> rises – that is, loss coverage<\/em> rises.<\/p>\n Three-minute version: <\/strong>here<\/a>.<\/p>\n Alternative versions:<\/strong> for actuaries<\/a>, for economists<\/a>, for lawyers<\/a>, for general readers<\/a>.<\/p>\n Videos:<\/strong> Example<\/a> (5 mins); Objections<\/a>; Youtube channel<\/a>.<\/p>\n Teaching & presentation materials <\/strong>(free use, no attribution necessary): a one-page graphic<\/a>; a\u00a010-minute lecture segment<\/a> ; a list of references<\/a>.<\/p>\n Other stuff:<\/strong> book<\/a>, journal papers<\/a>, articles<\/a> and talks<\/a>.<\/p>\n