6533b85cfe1ef96bd12bca69
RESEARCH PRODUCT
Data granularity in mid-year life table construction
Josep LledóNatalia SalazarJose M. Pavíasubject
QcaDeath ratesbusiness.industryWeb dataBig dataLibrary scienceConferencePlsExposed-to-risk populationBig dataMid-year estimatorsLife tableBig microdataPolitical scienceSemAgency (sociology)Table (database)Christian ministryMortality tablesbusinessInternet datadescription
[EN] Life tables have a substantial influence on both public pension systems and life insurance policies. National statistical agencies construct life tables from death rate estimates (𝑚���𝑥���), or death probabilities (𝑞���𝑥��� ), after applying various hypotheses to the aggregated figures of demographic events (deaths, migrations and births). The use of big data has become extensive across many disciplines, including population statistics. We take advantage of this fact to create new (more unrestricted) mortality estimators within the family of period-based estimators, in particular, when the exposed-to-risk population is computed through mid-year population estimates. We use actual data of the Spanish population to explore, by exploiting the detailed microdata of births, deaths and migrations (in total, more than 186 million demographic events), the effects that different assumptions have on calculating death probabilities. We also analyse their impact on a sample of insurance product. Our results reveal the need to include granular data, including the exact birthdate of each person, when computing period midyear life tables.
year | journal | country | edition | language |
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2020-07-08 | CARMA 2020 - 3rd International Conference on Advanced Research Methods and Analytics |