Stochastic mortality forecasts for Bangladesh
Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality an...
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| Veröffentlicht in: | PloS one 2022-11, Vol.17 (11), p.e0276966-e0276966 |
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| description | Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality and life expectancy of Bangladesh. A functional data analysis approach is used to decompose the smoothed log-mortality rates in Lee-Carter framework for higher goodness-of-fit of the models and for longer forecast horizons. Bangladesh has been experiencing a mortality transition and has gained life expectancy in last few decades. The fitted model here showed higher pace of mortality decline for women in Bangladesh than that of men. The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh. |
| doi_str_mv | 10.1371/journal.pone.0276966 |
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The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. 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The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh.</description><subject>Age groups</subject><subject>Aging</subject><subject>Bangladesh</subject><subject>Biology and Life Sciences</subject><subject>Data analysis</subject><subject>Decomposition</subject><subject>Demographic aspects</subject><subject>Developing countries</subject><subject>Evaluation</subject><subject>Females</subject><subject>Fertility</subject><subject>Forecasting</subject><subject>Forecasting techniques</subject><subject>Goodness of fit</subject><subject>Infant mortality</subject><subject>LDCs</subject><subject>Learning models (Stochastic processes)</subject><subject>Life expectancy</subject><subject>Life span</subject><subject>Maternal & child health</subject><subject>Maternal mortality</subject><subject>Mathematical models</subject><subject>Medicine and Health Sciences</subject><subject>Mortality</subject><subject>People and Places</subject><subject>Physical Sciences</subject><subject>Population</subject><subject>Registration</subject><subject>Research and Analysis Methods</subject><subject>Women</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNqNkk1rFTEUhoNYbK3-AxcXBNHF3CaTycdshLb4USgUrLoNuZmTOymZyTXJiP335tJRO8VFySKHk-e8CW9ehF4RvCZUkJObMMVR-_UujLDGteAt50_QEWlpXfEa06f36kP0PKUbjBmVnD9Dh5RTxiTGR6i6zsH0OmVnVkOIWXuXb1c2RDClmfbV6kyPW687SP0LdGC1T_By3o_Rt48fvp5_ri6vPl2cn15WhtUyVxyKuLW8oURq0bQbyWVjObEbi4XsKBGgDWUWa2mpZR2jHZZUYtANLU829Bi9v9PdTZsBOgNjjtqrXXSDjrcqaKeWJ6Pr1Tb8VC1vpBB1EXg7C8TwY4KU1eCSAe_1CGFKqhaUEVETyQv6-gE6OztTmHFJ_lFb7UG50YZyr9mLqlNRcywJFm2h1v-hyupgcKZ8lHWlvxh4txgoTIZfeaunlNTF9ZfHs1ffl-ybe2wP2uc-BT9lF8a0BJs70MSQUgT712SC1T5nf9xQ-5ypOWf0N93vw5g</recordid><startdate>20221110</startdate><enddate>20221110</enddate><creator>Fazle Rabbi, Ahbab Mohammad</creator><creator>Khan, Hafiz T. 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A</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stochastic mortality forecasts for Bangladesh</atitle><jtitle>PloS one</jtitle><date>2022-11-10</date><risdate>2022</risdate><volume>17</volume><issue>11</issue><spage>e0276966</spage><epage>e0276966</epage><pages>e0276966-e0276966</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Mortality forecasts are essential part for policymaking in any aging society. In recent years, methods to model and forecast mortality have improved considerably. Among them, Lee-Carter method is one of the most influential method. In this paper, Lee-Carter method is applied to forecast mortality and life expectancy of Bangladesh. A functional data analysis approach is used to decompose the smoothed log-mortality rates in Lee-Carter framework for higher goodness-of-fit of the models and for longer forecast horizons. Bangladesh has been experiencing a mortality transition and has gained life expectancy in last few decades. The fitted model here showed higher pace of mortality decline for women in Bangladesh than that of men. The forecasts showed continuation of mortality improvement in long run and by 2060 life expectancy at birth is expected to reach over 80 years for both sexes in Bangladesh. The study also predicts the effect of reduction in infant mortality on the life expectancy in Bangladesh.</abstract><cop>San Francisco</cop><pub>Public Library of Science</pub><pmid>36355800</pmid><doi>10.1371/journal.pone.0276966</doi><tpages>e0276966</tpages><orcidid>https://orcid.org/0000-0002-1817-3730</orcidid><orcidid>https://orcid.org/0000-0001-8627-187X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Age groups Aging Bangladesh Biology and Life Sciences Data analysis Decomposition Demographic aspects Developing countries Evaluation Females Fertility Forecasting Forecasting techniques Goodness of fit Infant mortality LDCs Learning models (Stochastic processes) Life expectancy Life span Maternal & child health Maternal mortality Mathematical models Medicine and Health Sciences Mortality People and Places Physical Sciences Population Registration Research and Analysis Methods Women |
| title | Stochastic mortality forecasts for Bangladesh |
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