The sensitivity analysis of population projections
<b>Background</b>: Population projections using the cohort component method can be written as time-varyingmatrix population models. The matrices are parameterized by schedules of mortality, fertility,immigration, and emigration over the duration of the projection. A variety of dependentv...
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| Format: | Article |
| Language: | English |
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Max Planck Institute for Demographic Research
2015-10-01
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| Series: | Demographic Research |
| Online Access: | http://www.demographic-research.org/volumes/vol33/28/ |
| _version_ | 1819134284121767936 |
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| author | Hal Caswell Nora Sánchez Gassen |
| author_facet | Hal Caswell Nora Sánchez Gassen |
| author_sort | Hal Caswell |
| collection | DOAJ |
| description | <b>Background</b>: Population projections using the cohort component method can be written as time-varyingmatrix population models. The matrices are parameterized by schedules of mortality, fertility,immigration, and emigration over the duration of the projection. A variety of dependentvariables are routinely calculated (the population vector, various weighted population sizes, dependency ratios, etc.) from such projections. <b>Objective</b>: Our goal is to derive and apply theory to compute the sensitivity and the elasticity (proportional sensitivity) of any projection outcome to changes in any of the parameters, where those changes are applied at any time during the projection interval. <b>Methods</b>: We use matrix calculus to derive a set of equations for the sensitivity and elasticity of any vector valued outcome ξ(t) at time t to any perturbation of a parameter vector Ɵ(s) at anytime s. <b>Results</b>: The results appear in the form of a set of dynamic equations for the derivatives that areintegrated in parallel with the dynamic equations for the projection itself. We show resultsfor single-sex projections and for the more detailed case of projections including age distributions for both sexes. We apply the results to a projection of the population of Spain, from 2012 to 2052, prepared by the Instituto Nacional de Estadística, and determine the sensitivity and elasticity of (1) total population, (2) the school-age population, (3) the population subject to dementia, (4) the total dependency ratio, and (5) the economicsupport ratio. <b>Conclusions</b>: Writing population projections in matrix form makes sensitivity analysis possible. Such analyses are a powerful tool for the exploration of how detailed aspects of the projectionoutput are determined by the mortality, fertility, and migration schedules that underlie theprojection. |
| first_indexed | 2024-12-22T10:00:44Z |
| format | Article |
| id | doaj.art-e80e0be444374e03843b6782c1847bfb |
| institution | Directory Open Access Journal |
| issn | 1435-9871 |
| language | English |
| last_indexed | 2024-12-22T10:00:44Z |
| publishDate | 2015-10-01 |
| publisher | Max Planck Institute for Demographic Research |
| record_format | Article |
| series | Demographic Research |
| spelling | doaj.art-e80e0be444374e03843b6782c1847bfb2022-12-21T18:30:09ZengMax Planck Institute for Demographic ResearchDemographic Research1435-98712015-10-01332810.4054/DemRes.2015.33.282711The sensitivity analysis of population projectionsHal Caswell0Nora Sánchez Gassen1University of AmsterdamUniversity of Southampton<b>Background</b>: Population projections using the cohort component method can be written as time-varyingmatrix population models. The matrices are parameterized by schedules of mortality, fertility,immigration, and emigration over the duration of the projection. A variety of dependentvariables are routinely calculated (the population vector, various weighted population sizes, dependency ratios, etc.) from such projections. <b>Objective</b>: Our goal is to derive and apply theory to compute the sensitivity and the elasticity (proportional sensitivity) of any projection outcome to changes in any of the parameters, where those changes are applied at any time during the projection interval. <b>Methods</b>: We use matrix calculus to derive a set of equations for the sensitivity and elasticity of any vector valued outcome ξ(t) at time t to any perturbation of a parameter vector Ɵ(s) at anytime s. <b>Results</b>: The results appear in the form of a set of dynamic equations for the derivatives that areintegrated in parallel with the dynamic equations for the projection itself. We show resultsfor single-sex projections and for the more detailed case of projections including age distributions for both sexes. We apply the results to a projection of the population of Spain, from 2012 to 2052, prepared by the Instituto Nacional de Estadística, and determine the sensitivity and elasticity of (1) total population, (2) the school-age population, (3) the population subject to dementia, (4) the total dependency ratio, and (5) the economicsupport ratio. <b>Conclusions</b>: Writing population projections in matrix form makes sensitivity analysis possible. Such analyses are a powerful tool for the exploration of how detailed aspects of the projectionoutput are determined by the mortality, fertility, and migration schedules that underlie theprojection.http://www.demographic-research.org/volumes/vol33/28/ |
| spellingShingle | Hal Caswell Nora Sánchez Gassen The sensitivity analysis of population projections Demographic Research |
| title | The sensitivity analysis of population projections |
| title_full | The sensitivity analysis of population projections |
| title_fullStr | The sensitivity analysis of population projections |
| title_full_unstemmed | The sensitivity analysis of population projections |
| title_short | The sensitivity analysis of population projections |
| title_sort | sensitivity analysis of population projections |
| url | http://www.demographic-research.org/volumes/vol33/28/ |
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