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A new inference strategy for general population mortality tables

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Academic year: 2021

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❆ ♥❡✇ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ❢♦r ❣❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥

♠♦rt❛❧✐t② t❛❜❧❡s

❆❧❡①❛♥❞r❡ ❇♦✉♠❡③♦✉❡❞

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✱ ▼❛r❝ ❍♦✛♠❛♥♥

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✱ P❛✉❧✐❡♥ ❏❡✉♥❡ss❡

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❆♣r✐❧ ✷✷✱ ✷✵✶✽

❆❜str❛❝t ❲❡ ♣r♦♣♦s❡ ❛ ♥❡✇ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ❢♦r ❣❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥ ♠♦rt❛❧✐t② t❛✲ ❜❧❡s ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ ❛♥❞ ❞❡❛t❤ ❡st✐♠❛t❡s✱ ❝♦♠♣❧❡t❡❞ ❜② ♠♦♥t❤❧② ❜✐rt❤ ❝♦✉♥ts✳ ❲❡ r❡❧② ♦♥ ❛ ❞❡t❡r♠✐♥✐st✐❝ ♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s ♠♦❞❡❧ ❛♥❞ ❡s✲ t❛❜❧✐s❤ ❢♦r♠✉❧❛s t❤❛t ❧✐♥❦s t❤❡ ❞❡❛t❤ r❛t❡s t♦ ❜❡ ❡st✐♠❛t❡❞ ✇✐t❤ t❤❡ ♦❜s❡r✈❛❜❧❡s ❛t ❤❛♥❞✳ ❚❤❡ ✐♥❢❡r❡♥❝❡ ❛❧❣♦r✐t❤♠ t❛❦❡s t❤❡ ❢♦r♠ ♦❢ ❛ r❡❝✉rs✐✈❡ ❛♥❞ ✐♠♣❧✐❝✐t s❝❤❡♠❡ ❢♦r ❝♦♠♣✉t✐♥❣ ❞❡❛t❤ r❛t❡ ❡st✐♠❛t❡s✳ ❚❤✐s ♣❛♣❡r ❞❡♠♦♥str❛t❡s ❜♦t❤ t❤❡♦r❡t✐❝❛❧❧② ❛♥❞ ♥✉♠❡r✐❝❛❧❧② t❤❡ ❡✣❝✐❡♥❝② ♦❢ ✉s✐♥❣ ❛❞❞✐t✐♦♥❛❧ ♠♦♥t❤❧② ❜✐rt❤ ❝♦✉♥ts ❢♦r ❛♣♣r♦♣r✐❛t❡❧② ❝♦♠♣✉t✐♥❣ ❛♥♥✉❛❧ ♠♦rt❛❧✐t② t❛❜❧❡s✳ ❆s ❛ ♠❛✐♥ r❡✲ s✉❧t✱ t❤❡ ✐♠♣r♦✈❡❞ ♠♦rt❛❧✐t② ❡st✐♠❛t♦rs s❤♦✇ ❜❡tt❡r ❢❡❛t✉r❡s✱ ✐♥❝❧✉❞✐♥❣ t❤❡ ❢❛❝t t❤❛t ♣r❡✈✐♦✉s ❛♥♦♠❛❧✐❡s ✐♥ t❤❡ ❢♦r♠ ♦❢ ✐s♦❧❛t❡❞ ❝♦❤♦rt ❡✛❡❝ts ❞✐s❛♣♣❡❛r✱ ✇❤✐❝❤ ❝♦♥✜r♠s ❢r♦♠ ❛ ♠❛t❤❡♠❛t✐❝❛❧ ♣❡rs♣❡❝t✐✈❡ t❤❡ ♣r❡✈✐♦✉s ❝♦♥tr✐❜✉t✐♦♥s ❜② ❘✐❝❤❛r❞s ✭✷✵✵✽✮✱ ❈❛✐r♥s ❡t ❛❧✳ ✭✷✵✶✻✮ ❛♥❞ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮✳ ❑❡②✇♦r❞s✿ ▼♦rt❛❧✐t② t❛❜❧❡s✱ ❣❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥✱ st❛t✐st✐❝❛❧ ✐♥❢❡r❡♥❝❡✱ ♣♦♣✉❧❛t✐♦♥ ❞②✲ ♥❛♠✐❝s✱ ❝♦❤♦rt ❡✛❡❝t✳ ❏❊▲✿ ❈✵✷✵ ▼❙❈ ✭✷✵✶✵✮✿ ✾✷❉✷✺✱ ✻✷P✵✺✱ ✻✷◆✵✷

✶ ■♥tr♦❞✉❝t✐♦♥

●❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥ ♠♦rt❛❧✐t② t❛❜❧❡s ❛r❡ ❝r✉❝✐❛❧ ✐♥♣✉ts ❢♦r ❛❝t✉❛r✐❛❧ st✉❞✐❡s ❛s t❤❡② ♣r♦✈✐❞❡ ❡st✐♠❛t❡s ♦❢ ♠♦rt❛❧✐t② r❛t❡s ❢♦r s❡✈❡r❛❧ ❛❣❡ ❝❧❛ss❡s ❛t s❡✈❡r❛❧ ♣❡r✐♦❞s ✐♥ ✶▼✐❧❧✐♠❛♥ ❘✫❉✱ ✶✹ ❆✈❡♥✉❡ ❞❡ ❧❛ ●r❛♥❞❡ ❆r♠é❡✱ ✼✺✵✶✼ P❛r✐s✱ ❋r❛♥❝❡✳ ❊♠❛✐❧✿ ❛❧❡①❛♥❞r❡✳❜♦✉♠❡③♦✉❡❞❅♠✐❧❧✐♠❛♥✳❝♦♠ ✷❈❊❘❊▼❆❉❊✱ ❈◆❘❙✲❯▼❘ ✼✺✸✹✱ ❯♥✐✈❡rs✐t❡ P❛r✐s ❉❛✉♣❤✐♥❡✱ P❧❛❝❡ ❞✉ ♠❛ré❝❤❛❧ ❞❡ ▲❛ttr❡ ❞❡ ❚❛ss✐❣♥② ✼✺✵✶✻ P❛r✐s✱ ❋r❛♥❝❡✳ ❊♠❛✐❧✿ ❤♦✛♠❛♥♥❅❝❡r❡♠❛❞❡✳❞❛✉♣❤✐♥❡✳❢r ✸❈❊❘❊▼❆❉❊✱ ❈◆❘❙✲❯▼❘ ✼✺✸✹✱ ❯♥✐✈❡rs✐t❡ P❛r✐s ❉❛✉♣❤✐♥❡✱ P❧❛❝❡ ❞✉ ♠❛ré❝❤❛❧ ❞❡ ▲❛ttr❡ ❞❡ ❚❛ss✐❣♥② ✼✺✵✶✻ P❛r✐s✱ ❋r❛♥❝❡✳ ❊♠❛✐❧✿ ❥❡✉♥❡ss❡❅❝❡r❡♠❛❞❡✳❞❛✉♣❤✐♥❡✳❢r ✶

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t✐♠❡✳ ❙✐♥❝❡ t❤❡ ♣✉❜❧✐❝❛t✐♦♥ ♦❢ t❤❡ ✜rst ♠♦rt❛❧✐t② t❛❜❧❡s ✭❛ttr✐❜✉t❡❞ t♦ ❏♦❤♥ ●r❛✉♥t ✐♥ ✶✻✻✷✮✱ t❤❡ ♠❛t❤❡♠❛t✐❝❛❧ ♣r♦❜❧❡♠ ♦❢ ♣r♦✈✐❞✐♥❣ ❝♦♥s✐st❡♥t st❛t✐st✐❝❛❧ ❡st✐♠❛t❡s ♦❢ ♠♦rt❛❧✐t② ❤❛s ❢❛s❝✐♥❛t❡❞ ♠❛t❤❡♠❛t✐❝✐❛♥s ✲ ❢♦r ❛ ❜r✐❡❢ ❤✐st♦r② t❤❡ r❡❛❞❡r ✐s r❡❢❡rr❡❞ t♦ t❤❡ ✇❡❧❧ ❞♦❝✉♠❡♥t❡❞ ❞❡❞✐❝❛t❡❞ ♣❛rt ♦❢ t❤❡ ✐♥tr♦❞✉❝t✐♦♥ ♦❢ ❉❛❧❡② ❛♥❞ ❱❡r❡✲❏♦♥❡s ✭✷✵✵✸✮✳ ❚✇♦ ❝❡♥t✉r✐❡s ❧❛t❡r✱ t❤❡r❡ ✇❛s ❛ ❤✉❣❡ ❞❡✈❡❧♦♣♠❡♥t ♦❢ ❣r❛♣❤✐❝❛❧ ❢♦r♠❛❧✐③❛✲ t✐♦♥s ♦❢ ❧✐❢❡ tr❛❥❡❝t♦r✐❡s ✇✐t❤✐♥ ❛ ♣♦♣✉❧❛t✐♦♥ ❜② ▲❡①✐s ✭✶✽✼✺✮ ❛♥❞ ❤✐s ❝♦♥t❡♠♣♦r❛r✐❡s✳ ❚❤❡s❡ ✜rst ❞❡♠♦❣r❛♣❤❡rs s❤♦✇❡❞ t❤❛t ✐t ✐s ❝r✉❝✐❛❧ t♦ ❛❞❞r❡ss s✐♠✉❧t❛♥❡♦✉s❧② t✇♦ ❝♦♠♣♦♥❡♥ts✿ ✭✶✮ ❈♦♥s✐❞❡r t❤❡ ❢❛❝t t❤❛t t❤❡ ❞❡❛t❤ r❛t❡ ❞❡♣❡♥❞s ♦♥ ❜♦t❤ ❛❣❡ ❛♥❞ t✐♠❡ ✭♥♦♥✲❤♦♠♦❣❡♥❡♦✉s s❡tt✐♥❣✮ ❛♥❞ ✭✷✮ ❯♥❞❡rst❛♥❞ t❤❡ ♠♦rt❛❧✐t② r❛t❡ ❛s ❛♥ ❛❣❣r❡✲ ❣❛t❡ q✉❛♥t✐t② ✇❤✐❝❤ ❞❡♣❡♥❞s ♦♥ ❛♥ ✉♥❞❡r❧②✐♥❣ ♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s✳ ❘❡❝❡♥t❧②✱ s❡✈❡r❛❧ ♣❛♣❡rs ❛♥❞ ♣✉❜❧✐❝❛t✐♦♥s ♣❛✐❞ ❛tt❡♥t✐♦♥ t♦ ❞❛t❛ q✉❛❧✐t② ✐ss✉❡s ✐♥ t❤❡ ✇❛② ✇❡ ✉s✉❛❧❧② ❜✉✐❧❞ ♠♦rt❛❧✐t② t❛❜❧❡s✱ ❡s♣❡❝✐❛❧❧② ✐♥ r❡❧❛t✐♦♥ ✇✐t❤ t❤❡ ✬❞✐s✲ ❝r❡t❡ t✐♠❡✬ ♥❛t✉r❡ ♦❢ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ♣r♦✈✐❞❡❞ ❜② ♥❛t✐♦♥❛❧ ❝❡♥s✉s❡s✳ ❚♦ ♦✉r ❦♥♦✇❧❡❞❣❡✱ t❤❡ ✜rst ✐♥s✐❣❤ts ❤❛✈❡ ❜❡❡♥ s✉❣❣❡st❡❞ ❜② ❘✐❝❤❛r❞s ✭✷✵✵✽✮❀ ❤✐s ❝♦♥❥❡❝t✉r❡ ✇❛s ❢♦❝✉s❡❞ ♦♥ t❤❡ ✶✾✶✾ ❜✐rt❤ ❝♦❤♦rt ❢♦r ❊♥❣❧❛♥❞ ✫ ❲❛❧❡s✱ ❢♦r ✇❤✐❝❤ ❤❡ s✉❣❣❡st❡❞ t❤❛t ❡rr♦rs ♦❝❝✉rr❡❞ ✐♥ t❤❡ ❝♦♠♣✉t❛t✐♦♥ ♦❢ ♠♦rt❛❧✐t② r❛t❡s ❞✉❡ t♦ s❤♦❝❦s ✐♥ t❤❡ ❜✐rt❤s s❡r✐❡s✳ ❚❤❡ ❖◆❙ ♠❡t❤♦❞♦❧♦❣② ❤❛s t❤❡♥ ❜❡❡♥ st✉❞✐❡❞ ❜② ❈❛✐r♥s ❡t ❛❧✳ ✭✷✵✶✻✮ ✐♥ s❡✈❡r❛❧ ❞✐r❡❝t✐♦♥s✱ ✇❤♦ ❝♦♥✜r♠❡❞ t❤❡ ❝♦♥❥❡❝t✉r❡ ❜② ❘✐❝❤❛r❞s ✭✷✵✵✽✮ ❛♥❞ ♣r♦✲ ♣♦s❡❞ ❛♥ ❛♣♣r♦❛❝❤ t♦ ✐❧❧✉str❛t❡ ❛♥❞ ❝♦rr❡❝t ♠♦rt❛❧✐t② t❛❜❧❡s✱ ❛♣♣❧✐❡❞ t♦ t❤❡ ❞❛t❛ ❢♦r ❊♥❣❧❛♥❞ ✫ ❲❛❧❡s❀ t❤❡ ❈♦♥✈❡①✐t② ❆❞❥✉st♠❡♥t ❘❛t✐♦ ✐♥tr♦❞✉❝❡❞ ✐♥ t❤❡✐r ✇♦r❦ ❤❛s t❤❡♥ ❜❡❡♥ ❛❞❛♣t❡❞ ❜② ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮ ✇❤♦ ❢♦❝✉s❡❞ ♦♥ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ❍▼❉ ✭✷✵✶✽✮ ✲ ✇❤✐❝❤ ♣r♦✈✐❞❡s ♠♦rt❛❧✐t② t❛❜❧❡s ❢♦r ♠♦r❡ t❤❛♥ ✸✵ ❝♦✉♥tr✐❡s ❛♥❞ r❡❣✐♦♥s ✇♦r❧❞✇✐❞❡ ✲ ❛♥❞ s❤♦✇❡❞ t❤❛t t❤❡s❡ ❛♥♦♠❛❧✐❡s ❛r❡ ✉♥✐✈❡rs❛❧ ✇❤✐❧❡ ✉s✲ ✐♥❣ t❤❡ ✬♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s✬ ♣♦✐♥t ♦❢ ✈✐❡✇ t♦ ♣r♦♣❡r❧② ❞❡✜♥❡ ♠♦rt❛❧✐t② ❡st✐♠❛t❡s✳ ❚♦ ❜✉✐❧❞ ♥❡✇ ♠♦rt❛❧✐t② t❛❜❧❡s ❢♦r s❡✈❡r❛❧ ❝♦✉♥tr✐❡s✱ ❛ ❧✐♥❦ ✇✐t❤ t❤❡ ❍✉♠❛♥ ❋❡rt✐❧✐t② ❉❛t❛❜❛s❡ ✭❍❋❉ ✭✷✵✶✽✮✱ t❤❡ ❍▼❉ ❝♦✉♥t❡r♣❛rt ❢♦r ❢❡rt✐❧✐t②✮ ❤❛s ❜❡❡♥ ♠❛❞❡ t♦ ❝♦rr❡❝t s✉❝❤ ❡rr♦rs ✐♥ ❛ s②st❡♠❛t✐❝ ✇❛②✳ ❍♦✇❡✈❡r✱ ❛❧❧ ♣r❡❝❡❞❡♥t ❝♦♥tr✐❜✉t✐♦♥s ❞✐❞ ♥♦t s✉❝❝❡❡❞ t♦ ✐♥tr♦❞✉❝❡ ❛ ♣r♦♣❡r ♠❛t❤✲ ❡♠❛t✐❝❛❧ s❡tt✐♥❣ ❢♦r ❝♦♠♣✉t✐♥❣ ♠♦rt❛❧✐t② r❛t❡s ❜❛s❡❞ ♦♥ ✐♥❢♦r♠❛t✐♦♥ ❡①tr❛❝t❡❞ ❢r♦♠ ❝❡♥s✉s❡s✳ ■♥ t❤✐s ♣❛♣❡r✱ ✇❡ ❛✐♠ ❛t ♣❡r❢♦r♠✐♥❣ ❛ ✜rst st❡♣ ✐♥ t❤✐s ❞✐r❡❝t✐♦♥ ❜② ❞❡✲ r✐✈✐♥❣ ❛♥ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ❢r♦♠ ❛ ❞❡t❡r♠✐♥✐st✐❝ ♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s ♠♦❞❡❧✳ ❚❤❡ ❞❡r✐✈❛t✐♦♥ ♦❢ ❛ ❝♦♥s✐st❡♥t t❤❡♦r② ✐♥ t❤❡ st♦❝❤❛st✐❝ s❡tt✐♥❣ ✐s ✐♥ ♣❛r❛❧❧❡❧ ♣r♦✈✐❞❡❞ ✐♥ ❛ ❝♦♠♣❛♥✐♦♥ t❤❡♦r❡t✐❝❛❧ ♣❛♣❡r✱ s❡❡ ❇♦✉♠❡③♦✉❡❞ ❡t ❛❧✳ ✭✷✵✶✽✮✳ ❚❤❡ ♠❛✐♥ ❞✐✣❝✉❧t② ✐♥ ❡st❛❜❧✐s❤✐♥❣ ❛ ❝♦♥s✐st❡♥t t❤❡♦r② t♦ ❡st✐♠❛t❡ ♠♦rt❛❧✐t② r❛t❡s ❧✐❡s ✐♥ ♣♦✐♥ts ✭✶✮ ❛♥❞ ✭✷✮ ♠❡♥t✐♦♥❡❞ ❛❜♦✈❡✱ ✇❤✐❝❤ ❝❛♥ ❜❡ s✉♠♠❛r✐③❡❞ ❛s ❢♦❧❧♦✇s✿ ✐♥❢❡rr✐♥❣ ❛♥ ❛❣❡ ❛♥❞ t✐♠❡ ❞❡♣❡♥❞❡♥t ♠♦rt❛❧✐t② r❛t❡ ❜❛s❡❞ ♦♥ ❛ ♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s ♠♦❞❡❧✳ ■♥ t❤❡ ❧✐t❡r❛t✉r❡✱ ✇❡ ❛r❣✉❡ t❤❛t ❡❛❝❤ ♣♦✐♥t ✐s tr❡❛t❡❞ s❡♣❛r❛t❡❧②✳ ❚❤❡ ✐♥❢❡r❡♥❝❡ ♦❢ ❛ t✐♠❡ ❞❡♣❡♥❞❡♥t ❞❡❛t❤ r❛t❡ ❛❧s♦ ❞❡♣❡♥❞✐♥❣ ♦♥ ❛ t✐♠❡✲❞❡♣❡♥❞❡♥t ❝♦✈❛r✐❛t❡ ✭♣♦ss✐❜❧② ❛❣❡✮✱ ✇❤✐❝❤ r❡❧❛t❡s t♦ ♣♦✐♥t ✭✶✮✱ ❤❛s ❜❡❡♥ ❛❞❞r❡ss❡❞ ❢r♦♠ ❛ ♥♦♥✲ ✷✴✷✷

(3)

♣❛r❛♠❡tr✐❝ ♣❡rs♣❡❝t✐✈❡ ❜② ❇❡r❛♥ ✭✶✾✽✶✮✱ ❉❛❜r♦✇s❦❛ ✭✶✾✽✼✮✱ ❑❡✐❞✐♥❣ ✭✶✾✾✵✮✱ ▼❝❑✲ ❡❛❣✉❡ ❛♥❞ ❯t✐❦❛❧ ✭✶✾✾✵✮✱ ◆✐❡❧s❡♥ ❛♥❞ ▲✐♥t♦♥ ✭✶✾✾✺✮✱ ❇r✉♥❡❧ ❡t ❛❧✳ ✭✷✵✵✽✮✱ ❈♦♠t❡ ❡t ❛❧✳ ✭✷✵✶✶✮✳ ❋r♦♠ ❑❡✐❞✐♥❣ ✭✶✾✾✵✮✱ ✧❖♥❡ ✇❛② ♦❢ ✉♥❞❡rst❛♥❞✐♥❣ t❤❡ ❞✐✣❝✉❧t✐❡s ✐♥ ❡st❛❜❧✐s❤✐♥❣ ❛♥ ❆❛❧❡♥ t❤❡♦r② ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠ ✐s t❤❛t ❛❧t❤♦✉❣❤ t❤❡ ❞✐❛❣r❛♠ ✐s t✇♦✲❞✐♠❡♥s✐♦♥❛❧✱ ❛❧❧ ♠♦✈❡♠❡♥ts ❛r❡ ✐♥ t❤❡ s❛♠❡ ❞✐r❡❝t✐♦♥ ✭s❧♦♣❡ ✶✮ ❛♥❞ ✐♥ t❤❡ ❢✉❧❧② ♥♦♥✲♣❛r❛♠❡tr✐❝ ♠♦❞❡❧ t❤❡ ❞✐❛❣r❛♠ ❞✐s✐♥t❡❣r❛t❡s ✐♥t♦ ❛ ❝♦♥t✐♥✉✉♠ ♦❢ ❧✐❢❡ ❧✐♥❡s ♦❢ s❧♦♣❡ ✶ ✇✐t❤ ❢r❡❡❧② ✈❛r②✐♥❣ ✐♥t❡♥s✐t✐❡s ❛❝r♦ss ❧✐♥❡s✳ ❚❤❡ ❝✉♠✉❧❛t✐♦♥ tr✐❝❦ ❢r♦♠ ❆❛❧❡♥✬s ❡st✐♠❛t♦r ✭❣❡♥❡r❛❧✐③✐♥❣ ♦r❞✐♥❛r② ❡♠♣✐r✐❝❛❧ ❞✐str✐❜✉t✐♦♥ ❢✉♥❝t✐♦♥s ❛♥❞ ❑❛♣❧❛♥ ✫ ▼❡✐❡r✬s ✭✶✾✺✽✮ ♥♦♥✲♣❛r❛♠❡tr✐❝ ❡♠♣✐r✐❝❛❧ ❞✐str✐❜✉t✐♦♥ ❢✉♥❝t✐♦♥ ❢r♦♠ ❝❡♥s♦r❡❞ ❞❛t❛✮ ❞♦❡s ♥♦t ❤❡❧♣ ✉s ❤❡r❡✳✧ ❚❤✐s ❡①♣❧❛✐♥s ✇❤② ❞❛t❛ ❛❣❣r❡❣❛✲ t✐♦♥ ❛♥❞ s♠♦♦t❤✐♥❣ ✐s r❡q✉✐r❡❞ t♦ ❞❡r✐✈❡ ❛♥ ❡st✐♠❛t❡ ✇✐t❤ t✇♦ ❝r♦ss✐♥❣ ❞✐♠❡♥s✐♦♥s✱ ❛❣❡ ❛♥❞ t✐♠❡✳ ❖♥ t❤❡ ♦t❤❡r s✐❞❡✱ t❤❡ ✐♥❢❡r❡♥❝❡ ♦❢ ❛♥ ❛❣❡✲❞❡♣❡♥❞❡♥t ❞❡❛t❤ r❛t❡ ✐♥ ❛♥ ❤♦♠♦❣❡✲ ♥❡♦✉s ❜✐rt❤✲❞❡❛t❤ ♠♦❞❡❧ ✭♦r s✐♠✐❧❛r✮ ✲ ♣♦✐♥t ✭✷✮ ✲ ❤❛s ❜❡❡♥ ❛❞❞r❡ss❡❞ ❜② ❈❧é♠❡♥ç♦♥ ❡t ❛❧✳ ✭✷✵✵✽✮✱ ❉♦✉♠✐❝ ❡t ❛❧✳ ✭✷✵✶✺✮✱ ❍♦✛♠❛♥♥ ❛♥❞ ❖❧✐✈✐❡r ✭✷✵✶✻✮✳ ❚♦ ♦✉r ❦♥♦✇❧❡❞❣❡✱ ♥♦ st❛t✐st✐❝❛❧ ♠❡t❤♦❞ ❞❡❛❧s ✇✐t❤ t❤❡ ✉s✉❛❧ ♣r♦❜❧❡♠ ❢❛❝❡❞ ❜② ❞❡♠♦❣r❛♣❤❡rs r❡❧❛t❡❞ t♦ t❤❡ ❝♦♥str✉❝t✐♦♥ ♦❢ ❛ ♠♦rt❛❧✐t② t❛❜❧❡ ❜❛s❡❞ ♦♥ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ❛♥❞ ❞❡❛t❤ ❝♦✉♥ts✳ ■♥ t❤✐s ♣❛♣❡r✱ ✇❡ r❡❧② ♦♥ ❛ ❞❡t❡r♠✐♥✐st✐❝ ❛❣❡✲str✉❝t✉r❡❞ ♣♦♣✉❧❛t✐♦♥ ♠♦❞❡❧ ❛♥❞ ❞❡r✐✈❡ ❡①❛❝t ❢♦r♠✉❧❛s ✐♥ t❤❡ s♦✲❝❛❧❧❡❞ ▲❡①✐s ❞✐❛❣r❛♠✱ ❛❧❧♦✇✐♥❣ t♦ ❜✉✐❧❞ ♥❡✇ ❛♥❞ ✐♠♣r♦✈❡❞ ♠♦rt❛❧✐t② ❡st✐♠❛t❡s✳ ❚❤❡ ✐♥❢❡r❡♥❝❡ ♣r♦❜❧❡♠ ✐s s✉♠♠❛r✐③❡❞ ❛s ❢♦❧❧♦✇s✿ • ❚❤❡ ❞❡❛t❤ r❛t❡ ❞❡♣❡♥❞s ♦♥ ❜♦t❤ ❛❣❡ ❛♥❞ t✐♠❡ ❛♥❞ ✐s t♦ ❜❡ ❡st✐♠❛t❡❞✱ • ❚❤❡ ♣♦♣✉❧❛t✐♦♥ ❡✈♦❧✈❡s ❛s ❛♥ ❛❣❡✲str✉❝t✉r❡❞ ❛♥❞ t✐♠❡ ✐♥❤♦♠♦❣❡♥❡♦✉s ❜✐rt❤✲ ❞❡❛t❤ ❞②♥❛♠✐❝s✱ • ❚❤❡ ❢♦❧❧♦✇✐♥❣ ♦❜s❡r✈❛❜❧❡s ❛r❡ ❛✈❛✐❧❛❜❧❡ ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠✿ ✕ ❚❤❡ ♥✉♠❜❡r ♦❢ ✐♥❞✐✈✐❞✉❛❧s ✐♥ ❡❛❝❤ ♦♥❡✲②❡❛r ❛❣❡✲❝❧❛ss✱ ❛ss✉♠❡❞ t♦ ❜❡ r❡❝♦r❞❡❞ ❛t ❡❛❝❤ ❜❡❣✐♥♥✐♥❣ ♦❢ ②❡❛r✱ ✕ ❚❤❡ ♥✉♠❜❡r ♦❢ ❞❡❛t❤s ✐♥ ❛♥♥✉❛❧ ▲❡①✐s tr✐❛♥❣❧❡s✱ ✕ ❚❤❡ ♥✉♠❜❡r ♦❢ ❜✐rt❤s✱ ❛✈❛✐❧❛❜❧❡ ❡❛❝❤ ♠♦♥t❤ ✭♦r ♠♦r❡ ❣❡♥❡r❛❧❧② ❛t s♦♠❡ ✐♥tr❛✲②❡❛r ❢r❡q✉❡♥❝②✮✳ ◆♦t❡ t❤❛t t❤❡ ♣r❛❝t✐❝❛❧ ❛✈❛✐❧❛❜✐❧✐t② ♦❢ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ❛s ✇❡❧❧ ❛s ❞❡❛t❤ ❝♦✉♥ts ✐♥ t❤❡ ▲❡①✐s tr✐❛♥❣❧❡ ❝❛♥ ❜❡ ❛❝❤✐❡✈❡❞ ❛❝❝♦r❞✐♥❣ t♦ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡✱ ✇❤❡r❡❛s t❤❡ ❍✉♠❛♥ ❋❡rt✐❧✐t② ❉❛t❛❜❛s❡ ✐s ❛ ♣✉❜❧✐❝ s♦✉r❝❡ ♣r♦✈✐❞✐♥❣ ✐♥ ♣❛rt✐❝✉❧❛r ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❜② ♠♦♥t❤s ❢♦r s❡✈❡r❛❧ ❝♦✉♥tr✐❡s✳ ❙✉❝❤ ♣♦♣✉❧❛t✐♦♥✱ ❞❡❛t❤ ❛♥❞ ❢❡rt✐❧✐t② ❞❛t❛ ❛❧❧♦✇s ❛t t❤✐s ❞❛t❡ t❤❡ ♠❡t❤♦❞ ♣r♦♣♦s❡❞ ✐♥ t❤✐s ♣❛♣❡r t♦ ❜❡ ❛♣♣❧✐❡❞ t♦ ❛r♦✉♥❞ ✶✵ ❝♦✉♥tr✐❡s✳ ❋♦r ♦t❤❡r ❝♦✉♥tr✐❡s✱ t❤❡ ❞❛t❛ ✭❡s♣❡❝✐❛❧❧② ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❜② ♠♦♥t❤✮ ❤❛s t♦ ❜❡ r❡❛❝❤❡❞ ❜② ♠❡❛♥s ♦❢ ♥❛t✐♦♥❛❧ ✐♥st✐t✉t❡s✳ ✸✴✷✷

(4)

❚❤❡ ♣❛♣❡r ✐s ♦r❣❛♥✐③❡❞ ❛s ❢♦❧❧♦✇s✳ ■♥ ❙❡❝t✐♦♥ ✷✱ ✇❡ ♣r❡s❡♥t t❤❡ ♥♦♥✲❤♦♠♦❣❡♥❡♦✉s ❜✐rt❤✲❞❡❛t❤ ♠♦❞❡❧ ❛♥❞ ❞❡r✐✈❡ t❤❡ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ✲ t❤❡ r❡❧❛t❡❞ ✐♥t❡r♣r❡t❛t✐♦♥s ❛♥❞ ❧✐♥❦ ✇✐t❤ ❡①✐st✐♥❣ ❡st✐♠❛t♦rs ✐s ❞✐s❝✉ss❡❞ ✐♥ ❙✉❜s❡❝t✐♦♥ ✷✳✻✳ ■♥ ❙❡❝t✐♦♥ ✸✱ ✇❡ ❝♦♠♣✉t❡ ♠♦rt❛❧✐t② t❛❜❧❡s ❛❝❝♦r❞✐♥❣ t♦ ♦✉r ♠❡t❤♦❞ ❛♥❞ ❝♦♠♣❛r❡ ✐t t♦ t❤♦s❡ ♦❜t❛✐♥❡❞ ❜② t❤❡ ✉s✉❛❧ ❢♦r♠✉❧❛s✳ ❚❤❡ ♣❛♣❡r ❡♥❞s ✇✐t❤ s♦♠❡ ❝♦♥❝❧✉❞✐♥❣ r❡♠❛r❦s ✐♥ ❙❡❝t✐♦♥ ✹✳

✷ ▼♦❞❡❧ ❛♥❞ ✐♥❢❡r❡♥❝❡ str❛t❡❣②

✷✳✶ ◆♦♥✲❤♦♠♦❣❡♥❡♦✉s ❜✐rt❤✲❞❡❛t❤ ❞②♥❛♠✐❝s

▲❡t ✉s ❞❡♥♦t❡ ❜② µ(a, t) t❤❡ ♠♦rt❛❧✐t② r❛t❡ ❛t ❡①❛❝t ❛❣❡ a ∈ R+ = [0, ∞) ❛♥❞ ❡①❛❝t t✐♠❡ t ∈ R+✱ ✇✐t❤ ❛♥ ❛r❜✐tr❛r② t✐♠❡ ♦r✐❣✐♥ ✲ ❧❡t ✉s ❛❧s♦ ❞❡♥♦t❡ ❜② g(a, t) t❤❡ ♣♦♣✉❧❛t✐♦♥ ❞❡♥s✐t② ❛t (a, t)✱ ❛ ♥♦♥✲♥❡❣❛t✐✈❡ r❡❛❧ ✈❛❧✉❡✳ ■♥ ✐ts ❝♦r❡ ❞❡✜♥✐t✐♦♥✱ t❤❡ ❞❡❛t❤ r❛t❡ ❞r✐✈❡s t❤❡ ♥✉♠❜❡r ♦❢ ❧✐✈✐♥❣ ✐♥ ❛ ❝❧♦s❡❞ ♣♦♣✉❧❛t✐♦♥✳ ❋♦r♠❛❧❧②✱ ❝♦♥s✐❞❡r g(0, ν) t❤❡ ♥❡✇❜♦r♥ ❛t ✭❡①❛❝t✮ t✐♠❡ ν ✭st❛rt✐♥❣ ♥✉♠❜❡r ✐♥ t❤❡ ❝♦❤♦rt ❜♦r♥ ❛t t✐♠❡ ν✮✱ t❤❡♥ t❤❡ s✉r✈✐✈♦rs ❛t s♦♠❡ ❛❣❡ a > 0 ✐♥ t❤❡ ❝♦❤♦rt ✇r✐t❡ g(a, ν + a) = g(0, ν) exp  − Z a 0 µ(s, ν + s)ds  . ❈❤❛♥❣✐♥❣ ✈❛r✐❛❜❧❡s t♦ r❡♣r❡s❡♥t g(a, t)✱ ❛♥❞ ❞✐✛❡r❡♥t✐❛t✐♥❣ ❜② ❛❣❡ ❛♥❞ t✐♠❡✱ ❧❡❛❞s t♦ t❤❡ tr❛♥s♣♦rt ❝♦♠♣♦♥❡♥t ♦❢ t❤❡ s♦✲❝❛❧❧❡❞ ▼❝❑❡♥❞r✐❝❦✲❱♦♥ ❋♦❡rst❡r ❡q✉❛t✐♦♥ ✭s❡❡ ▼❝❑❡♥❞r✐❝❦ ✭✶✾✷✻✮ ❛♥❞ ❱♦♥ ❋♦❡rst❡r ✭✶✾✺✾✮✮✿

( ∂a+ ∂t)g(a, t) = −µ(a, t)g(a, t), ✭✶✮

✇✐t❤ ♥♦t❛t✐♦♥ ∂a≡ ∂/∂a✳ ❈❧❡❛r❧②✱ ❛t t❤✐s st❛❣❡✱ t❤❡ ♣♦♣✉❧❛t✐♦♥ ❞②♥❛♠✐❝s ♦❢ g(a, t) ✐s ♥♦t ❢✉❧❧② s♣❡❝✐✜❡❞ ❛s t❤❡ ❢✉t✉r❡ ♣❛t❤ ♦❢ g(a, t) ❞❡♣❡♥❞s ♦♥ t❤❡ q✉❛♥t✐t② g(0, t−a)✳ ❚❤❡ ▼❝❑❡♥❞r✐❝❦✲❱♦♥ ❋♦❡rst❡r s♣❡❝✐✜❡s ❤♦✇ ❜✐rt❤s ❛r❡ ❣✐✈❡♥ ✐♥ t❤❡ ✭❛s❡①✉❛❧✮ ♣♦♣✉❧❛t✐♦♥✱ ❜❛s❡❞ ♦♥ ❛ ❜✐rt❤ r❛t❡ b(a, t)✱ ❛s ❢♦r ❡❛❝❤ t✐♠❡ ν > 0, g(0, ν) =Z ∞ 0

g(a, ν)b(a, ν)da.

❚❤❛t ✐s s✐♠♣❧②✱ t❤❡ ♥❡✇❜♦r♥ ❛t ❡❛❝❤ t✐♠❡ ✐s ❣✐✈❡♥ ❜② t❤❡ t♦t❛❧ ♥✉♠❜❡r ♦❢ ❜✐rt❤ ❢r♦♠ ❛❧❧ ♣❛r❡♥ts ❛❧✐✈❡ ❛t t❤❡ s❛♠❡ t✐♠❡✳

✷✳✷ ❖❜s❡r✈❛❜❧❡s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠

❲❡ ✇♦r❦ ❤❡r❡ ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠ ✲ t❤❛t ✐s ✇❡ st✉❞② ❧✐❢❡❧✐♥❡s ✐♥ t❤❡ t✐♠❡ × ❛❣❡ ❝♦♦r❞✐♥❛t❡s✳ ■♥ ❛♥ ✐❞❡❛❧ ❞❡♠♦❣r❛♣❤✐❝ ✇♦r❧❞✱ t✇♦ ❦✐♥❞s ♦❢ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ❛r❡ r❡❝♦r❞❡❞ ✐♥ t❤❡ ♦♥❡✲②❡❛r ❛❣❡ × t✐♠❡ sq✉❛r❡✿ ✹✴✷✷

(5)

✷✳✷ ❖❜s❡r✈❛❜❧❡s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠ • P♦♣✉❧❛t✐♦♥ ❛t ❡①❛❝t t✐♠❡ t✱ ✇✐t❤ ❛❣❡ x ❛t ✐ts ❧❛st ❜✐rt❤❞❛②✿ P (x, t) = Z x+1 x g(a, t)da. ✭✷✮ • ■♥❞✐✈✐❞✉❛❧s ✇❤♦ ❛tt❛✐♥❡❞ ❡①❛❝t ❛❣❡ x ❞✉r✐♥❣ t❤❡ ②❡❛r [t, t + 1)✿ N (x, t) = Z t+1 t g(x, s)ds. ❆♥ ✐❧❧✉str❛t✐♦♥ ♦❢ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s P (x, t) ❢♦r t❤❡ ❋r❡♥❝❤ ♣♦♣✉❧❛t✐♦♥ ❡①✲ tr❛❝t❡❞ ❢♦r♠ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ✐s ❣✐✈❡♥ ✐♥ ❋✐❣✉r❡ ✶✳ ❚❤✐s ❝❛♥ ❜❡ ❛♥❛❧②s❡❞ ✐♥ t❤❡ ❧✐❣❤t ♦❢ ❛ ▲❡①✐s ❞✐❛❣r❛♠ ✐♥ s❡✈❡r❛❧ ❞✐r❡❝t✐♦♥s✳ ❋✐rst✱ t❤❡ ❞✐❛❣♦♥❛❧ ❡✛❡❝ts ❛♣♣❡❛r ❝❧❡❛r❧② s❤♦✇✐♥❣ t❤❛t ❣❡♥❡r❛t✐♦♥s ✭♦r ❝♦❤♦rts✮ ❛r❡ ♥♦t ❡q✉❛❧❧② r❡♣r❡✲ s❡♥t❡❞✿ ❛s ❛♥ ❡①❛♠♣❧❡✱ t❤❡ ❣❡♥❡r❛t✐♦♥s ❜♦r♥ ❜❡t✇❡❡♥ ❛r♦✉♥❞ ✶✾✶✺ ❛♥❞ ✶✾✷✵ ❛r❡ ❧❡ss r❡♣r❡s❡♥t❡❞ ✭❲♦r❧❞ ❲❛r ■✮✱ ✇❤❡r❡❛s t❤❡ ❣❡♥❡r❛t✐♦♥s ❜♦r♥ ❛❢t❡r ❛r♦✉♥❞ ✶✾✹✻ ❛r❡ ❤✐❣❤❧② r❡♣r❡s❡♥t❡❞ ✭❇❛❜② ❇♦♦♠✮✳ ■♥ t❤✐s ✇♦r❦✱ t❤❡ ✐♠♣❛❝t ♦❢ t❤❡ ❞✐s❝r❡♣❛♥❝② ❜❡✲ t✇❡❡♥ ❜✐rt❤ ♣❛tt❡r♥s ❢r♦♠ ♦♥❡ ②❡❛r t♦ t❤❡ ♥❡①t ✐s ♦❢ ✐♥t❡r❡st✱ ❛s ✐t ✐♥tr♦❞✉❝❡s s♦♠❡ ❜✐❛s ✐♥ t❤❡ ❝❧❛ss✐❝❛❧ ❢♦r♠✉❧❛s ✉s❡❞ ✐♥ ♣r❛❝t✐❝❡ ❢♦r ❞❡❛t❤ r❛t❡ ❡st✐♠❛t✐♦♥✳

Population estimates 1st January (France)

Year Age 40 60 80 1970 1980 1990 2000 0e+00 2e+05 4e+05 6e+05 8e+05 ❋✐❣✉r❡ ✶✿ P♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ❢♦r ❋r❛♥❝❡ ❜② ②❡❛r ❢♦r ♦♥❡✲②❡❛r ❛❣❡ ❝❧❛ss❡s ❡①tr❛❝t❡❞ ❢r♦♠ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ❆❧s♦✱ ❞❡❛t❤ ❝♦✉♥ts ❛r❡ ♣r♦✈✐❞❡❞ ♦♥ t❤❡ ✉♣♣❡r ❛♥❞ ❧♦✇❡r tr✐❛♥❣❧❡s ♦❢ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠✱ ❛s ❞❡✜♥❡❞ ❜❡❧♦✇✳ ❉❡✜♥✐t✐♦♥ ✶✳ ❚❤❡ ✉♣♣❡r ✭❯✮ ❛♥❞ ❧♦✇❡r ✭▲✮ tr✐❛♥❣❧❡s ❢♦r ❡❛❝❤ ❛❣❡ r❛♥❣❡ x ❛♥❞ ♦❜s❡r✈❛t✐♦♥ ②❡❛r t ❛r❡ t❤❡ ❛❣❡ × t✐♠❡s s❡ts ❞❡✜♥❡❞ ❜② TU(x, t) = {(a, s) : a ∈ [x, x + 1) ❛♥❞ s ∈ [t, t − x + a)}, ✭✸✮ ❛♥❞ TL(x, t) = {(a, s) : a ∈ [x, x + 1) ❛♥❞ s ∈ [t − x + a, t + 1)}. ✭✹✮ ✺✴✷✷

(6)

✷✳✷ ❖❜s❡r✈❛❜❧❡s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠

❇❛s❡❞ ♦♥ t❤✐s ❞❡✜♥✐t✐♦♥✱ t❤❡ ♥✉♠❜❡r ♦❢ ❞❡❛t❤ ✐♥ t❤❡ ▲❡①✐s tr✐❛♥❣❧❡s ❝❛♥ ❜❡ ✇r✐tt❡♥

DU(x, t) =

ZZ

TU(x,t)

µ(a, s)g(a, s)dads ❛♥❞ DL(x, t) =

ZZ

TL(x,t)

µ(a, s)g(a, s)dads. ✭✺✮ ❆♥ ✐❧❧✉str❛t✐♦♥ ♦❢ ❞❡❛t❤ ❝♦✉♥ts ✐♥ t❤❡ ▲❡①✐s tr✐❛♥❣❧❡s (x, t) ❢♦r t❤❡ ❋r❡♥❝❤ ♣♦♣✉❧❛t✐♦♥ ❡①tr❛❝t❡❞ ❢♦r♠ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ✐s r❡♣r❡s❡♥t❡❞ ✐♥ ❋✐❣✉r❡ ✷✳ ❱❛r✐❛t✐♦♥s ✐♥ ♥✉♠❜❡r ♦❢ ❞❡❛t❤s ❛r❡ ❝❧♦s❡❧② ❧✐♥❦❡❞ t♦ t❤♦s❡ ♦❢ t❤❡ ✉♥❞❡r❧②✐♥❣ ❡①♣♦s✉r❡ ✭❋✐❣✉r❡ ✶✮ ❜✉t ❛❧s♦ t♦ t❤❡ ❞❡❛t❤ r❛t❡ ✐ts❡❧❢✱ t♦ ❜❡ ❡st✐♠❛t❡❞✳

Deaths in lower triangles (France)

Year Age 40 60 80 1970 1980 1990 2000 0 2000 4000 6000 8000 10000 12000

Deaths in upper triangles (France)

Year Age 40 60 80 1970 1980 1990 2000 0 2000 4000 6000 8000 10000 12000 ❋✐❣✉r❡ ✷✿ ❉❡❛t❤ ❝♦✉♥ts ✐♥ ▲❡①✐s tr✐❛♥❣❧❡s ❡①tr❛❝t❡❞ ❢r♦♠ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ❆ss✉♠✐♥❣ t❤❛t t❤❡ ♣♦♣✉❧❛t✐♦♥ ✐s ❝❧♦s❡❞✱ t❤❡ ❢♦❧❧♦✇✐♥❣ ❢✉♥❞❛♠❡♥t❛❧ r❡❧❛t✐♦♥s ❛♣✲ ♣❧② ✭✇❤✐❝❤ ❝❛♥ ❜❡ ♣r♦✈❡❞ ❜② ✐♥t❡❣r❛t✐♦♥ ❜② ♣❛rts✮✿ N (x + 1, t) = P (x, t) − DU(x, t), P (x, t + 1) = N (x, t) − DL(x, t). ✭✻✮ ❚❤❡ ❛ss✉♠♣t✐♦♥ ♦❢ ❝❧♦s❡❞✲♣♦♣✉❧❛t✐♦♥ ✐s ❢✉rt❤❡r ❞✐s❝✉ss❡❞ ✐♥ ❙✉❜s❡❝t✐♦♥ ✷✳✻✳ ■♥ ❛❞❞✐t✐♦♥ t♦ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s ❛♥❞ ❞❡❛t❤ ❝♦✉♥ts✱ ❛s ❛♥❛❧②③❡❞ ❜② ❈❛✐r♥s ❡t ❛❧✳ ✭✷✵✶✻✮ ❛♥❞ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮✱ ✇❡ ❛✐♠ ❛t ✐♥❝❧✉❞✐♥❣ ❜✐rt❤ ❝♦✉♥ts ❜② ♠♦♥t❤ ✐♥ t❤❡ ✐♥❢❡r❡♥❝❡ ♣r♦❝❡ss ✲ t❤❡s❡ ❝❛♥ ❜❡ ❡①tr❛❝t❡❞ ❢r♦♠ t❤❡ ❍✉♠❛♥ ❋❡rt✐❧✐t② ❉❛t❛❜❛s❡ ❢♦r ❛ ✈❛r✐❡t② ♦❢ ❝♦✉♥tr✐❡s✳ ❚❤❡ ❞②♥❛♠✐❝s ♦❢ ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❜② ♠♦♥t❤ ✐♥ ❋r❛♥❝❡ ✐s ✐❧❧✉str❛t❡❞ ✐♥ ❋✐❣✉r❡ ✸✳ ❚❤❡ ✐♥t❡r♣r❡t❛t✐♦♥ ♦❢ t❤✐s ❞②♥❛♠✐❝s ❝❛♥ ❜❡ ❧✐♥❦❡❞ t♦ t❤❛t ♦❢ ❋✐❣✉r❡s ✶ ✭♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s✱ s❡❡ ✭✷✮✮ ❛♥❞ ✷ ✭❞❡❛t❤ ❝♦✉♥ts ✐♥ ▲❡①✐s tr✐❛♥❣❧❡s✱ ❛s ❞❡✜♥❡❞ ✐♥ ✭✺✮✮✳ ■♥❞❡❡❞✱ ❛ s✐♠✐❧❛r ✐♥❢♦r♠❛t✐♦♥ ❛r✐s❡s ❛s t❤❡ ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❛r❡ ❧♦✇ ✐♥ t❤❡ ♣❡r✐♦❞ ✶✾✶✺✲✶✾✷✵✱ ✇❤✐❝❤ ❡①♣❧❛✐♥s ✐♥ ♣❛rt✐❝✉❧❛r t❤❡ ❞✐❛❣♦♥❛❧ ❡✛❡❝t ✐♥ ❋✐❣✉r❡ ✶✳ ❊✈❡♥ ♠♦r❡ ✐♠♣♦rt❛♥t❧②✱ t❤❡ ❞②♥❛♠✐❝s ❛t t❤❡ ♠♦♥t❤❧② s❝❛❧❡ ❣✐✈❡s ✐♥s✐❣❤t ♦♥ ✇❤❛t ❤❛♣♣❡♥s ✐♥s✐❞❡ ❡❛❝❤ ②❡❛r✱ t❤❡♥ ❝❛♥ ❜❡ ✉s❡❞ t♦ ❛ss❡ss ❤♦✇ t❤❡ ♣♦♣✉❧❛t✐♦♥ ✻✴✷✷

(7)

✷✳✸ ❉❡❛t❤ r❛t❡ ✐♥❢❡r❡♥❝❡ ✐s ❞✐str✐❜✉t❡❞ ✐♥s✐❞❡ ❛ ❣✐✈❡♥ ❛❣❡ ❜❛♥❞✳ ❚❤✐s ✐s ♦❢ ❣r❡❛t ✐♥t❡r❡st ❛s t❤❡ ♣♦♣✉❧❛t✐♦♥ ❞✐str✐❜✉t✐♦♥ ❛♣♣❡❛rs ❝❧❛ss✐❝❛❧❧② ✐♥ t❤❡ ❢♦r♠ ♦❢ ❛♥ ✬❡①♣♦s✉r❡✲t♦✲r✐s❦✬✱ ❛♥❞ ♠♦r❡ ♣r❡✲ ❝✐s❡❧② t❤❡ ❢♦r♠✉❧❛s ✇❡ ❡①❤✐❜✐t ✐♥ ♦r❞❡r t♦ ❡st✐♠❛t❡ t❤❡ ❞❡❛t❤ r❛t❡ r❡❧② ❡①♣❧✐❝✐t❧② ♦♥ t❤❡ ❜✐rt❤s ❞✐str✐❜✉t✐♦♥ ✲ ❛s s✉❝❤✱ ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❜② ♠♦♥t❤ ❛r❡ t❤❡ ❦❡② ✐♥♣✉ts ❢♦r t❤❡ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ♣r♦♣♦s❡❞ ❤❡r❡ ❛s ✐t r❡✜♥❡s st❛♥❞❛r❞ ❛♥♥✉❛❧ ❡st✐♠❛t❡s✳ ❚❤✐s ✐s ❞❡✈❡❧♦♣❡❞ ✐♥ t❤❡ ❢♦❧❧♦✇✐♥❣✳

1900

1950

2000

30000

50000

70000

90000

Number of births by month (France)

❋✐❣✉r❡ ✸✿ ◆✉♠❜❡r ♦❢ ❜✐rt❤ ❜② ♠♦♥t❤ ❡①tr❛❝t❡❞ ❢r♦♠ t❤❡ ❍✉♠❛♥ ❋❡rt✐❧✐t② ❉❛t❛❜❛s❡

✷✳✸ ❉❡❛t❤ r❛t❡ ✐♥❢❡r❡♥❝❡

❲❤❡♥ t✇♦ t✐♠❡✲❞❡♣❡♥❞❡♥t ❞✐♠❡♥s✐♦♥s ❛r❡ ✐♥✈♦❧✈❡❞ ✭❤❡r❡ ❛❣❡ ❛♥❞ ❝❛❧❡♥❞❛r t✐♠❡✮✱ t❤❡ ♥❛t✉r❛❧ ❣❡♥❡r❛❧✐③❛t✐♦♥ ♦❢ ❝❧❛ss✐❝❛❧ ♥♦♥✲♣❛r❛♠❡tr✐❝ ❡st✐♠❛t❡s ♦❢ t❤❡ ❞❡❛t❤ r❛t❡ ✐s ♥♦t ❞✐r❡❝t ✭s❡❡ ❛❣❛✐♥ t❤❡ ❞✐s❝✉ss✐♦♥ ✐♥ ❑❡✐❞✐♥❣ ✭✶✾✾✵✮✮✱ t❤❡r❡❢♦r❡ s♠♦♦t❤✐♥❣ ✐s r❡q✉✐r❡❞ ✲ s❡❡ ❡✳❣✳ ▼❝❑❡❛❣✉❡ ❛♥❞ ❯t✐❦❛❧ ✭✶✾✾✵✮ ❛♥❞ ◆✐❡❧s❡♥ ❛♥❞ ▲✐♥t♦♥ ✭✶✾✾✺✮ ❢♦r t❤❡ ❛♥❛❧②s✐s ♦❢ s✉❝❤ t✇♦ ❞✐♠❡♥s✐♦♥❛❧ ❦❡r♥❡❧ ❡st✐♠❛t♦r ❜❛s❡❞ ♦♥ ❝♦♥t✐♥✉♦✉s ♦❜s❡r✲ ✈❛t✐♦♥✳ ❯♥❢♦rt✉♥❛t❡❧②✱ ❢♦r ❜✉✐❧❞✐♥❣ ♥❛t✐♦♥❛❧ ♠♦rt❛❧✐t② t❛❜❧❡s ♦♥❡ ❞♦❡s ♥♦t ♦❜s❡r✈❡ ❝♦♥t✐♥✉♦✉s❧② t❤❡ ❧✐✈✐♥❣ ♣♦♣✉❧❛t✐♦♥ ✭♦♥❧② ♣♦ss✐❜❧② t❤❡ ❞❛t❡ ♦❢ ❞❡❛t❤ t❤r♦✉❣❤ ❞❡❛t❤ ❝❡rt✐✜❝❛t❡s✮✱ t❤❡r❡❢♦r❡ st❛♥❞❛r❞ ❦❡r♥❡❧ s♠♦♦t❤✐♥❣ t❡❝❤♥✐q✉❡s ❛r❡ ♥❡✐t❤❡r ❛♣♣❧✐❝❛❜❧❡ ❤❡r❡✳ ❚❤✐s ❧❡❛❞s t♦ ❞❡✜♥❡ s♦♠❡ ❣❡♦♠❡tr② ♦♥ ✇❤✐❝❤ t❤❡ ❞❡❛t❤ r❛t❡ ✐s ❛ss✉♠❡❞ t♦ ❜❡ ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t✱ ✇❤✐❝❤ ❛❧❧♦✇s t♦ ✉s❡ ❛❣❣r❡❣❛t❡ ✐♥❢♦r♠❛t✐♦♥ ❜② ②❡❛r ❛♥❞ ❛❣❡✲❝❧❛ss t♦ ❞❡r✐✈❡ ✭❛♣♣r♦①✐♠❛t❡✮ ❡st✐♠❛t♦rs✳ ✼✴✷✷

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✷✳✸ ❉❡❛t❤ r❛t❡ ✐♥❢❡r❡♥❝❡ ■♥ t❤❡ ❝❧❛ss✐❝❛❧ ❞❡♠♦❣r❛♣❤✐❝ ❛♥❞ ❛❝t✉❛r✐❛❧ ♣r❛❝t✐❝❡✱ ✐t ✐s ❝♦♥s✐❞❡r❡❞ t✇♦ ✈❡rs✐♦♥s ♦❢ ❣❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥ ♠♦rt❛❧✐t② t❛❜❧❡s✿ ♣❡r✐♦❞ ❛♥❞ ❝♦❤♦rt✳ ❲❡ ♣r♦♣♦s❡ ❤❡r❡ ❛ ❜r✐❡❢ ❞✐s❝✉ss✐♦♥ ♦❢ t❤❡s❡ t✇♦ ✈❡rs✐♦♥s ❛♥❞ r❡❢❡r t❤❡ r❡❛❞❡r t♦ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮ ❢♦r ♠♦r❡ ❞❡t❛✐❧s ✭❛♥❞ ❛ st✉❞② ❞❡❞✐❝❛t❡❞ t♦ ♣❡r✐♦❞ ♠♦rt❛❧✐t② t❛❜❧❡s✮✳ ❚❤❡ t✇♦ ✈❡rs✐♦♥s ❛r❡ ✐❧❧✉str❛t❡❞ ✐♥ ❋✐❣✉r❡ ✹✳ • ❚❤❡ ♣❡r✐♦❞ t❛❜❧❡ ♣r♦✈✐❞❡s ❞❡❛t❤ r❛t❡ ❡st✐♠❛t❡s ❜❛s❡❞ ♦♥ t❤❡ ❛ss✉♠♣t✐♦♥ t❤❛t ✐t ✐s ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ♦♥ sq✉❛r❡s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠❀ ❡❛❝❤ sq✉❛r❡ (x, t) ✐s ❡q✉❛❧ t♦ t❤❡ r❡❣✐♦♥ TU(x, t)∪TL(x, t)✱ ✇❤❡r❡ t❤❡ ▲❡①✐s tr✐❛♥❣❧❡s TU ❛♥❞ TL❤❛✈❡ ❜❡❡♥ ❞❡✜♥❡❞ ✐♥ ❊q✉❛t✐♦♥s ✭✸✮ ❛♥❞ ✭✹✮✳ ❚❤❡ ❦❡② ❛❞✈❛♥t❛❣❡ ♦❢ ♣❡r✐♦❞ t❛❜❧❡s ✐s t❤❛t t❤❡② ♣r♦✈✐❞❡ ❛♥ ❡st✐♠❛t❡ ♦❢ ❞❡❛t❤ r❛t❡ ❜② ✉s✐♥❣ ✐♥❢♦r♠❛t✐♦♥ ♦❢ ❛ s✐♥❣❧❡ ②❡❛r❀ t❤❡ r❡❧❛t❡❞ ❞r❛✇❜❛❝❦ ✐s t❤❛t t✇♦ ❣❡♥❡r❛t✐♦♥s ✭❝♦❤♦rts✮ ❛r❡ ♠❡r❣❡❞ ❢♦r ❛ ❣✐✈❡♥ ❞❡❛t❤ r❛t❡ ❛t (x, t)✿ t❤❡ ❧✐❢❡❧✐♥❡s ❝r♦ss✐♥❣ t❤❡ tr✐❛♥❣❧❡ TL(x, t) ❛r❡ ❜♦r♥ ✐♥ ②❡❛r t − x✱ ✇❤❡r❡❛s t❤♦s❡ ❝r♦ss✐♥❣ TU(x, t)❛r❡ ❜♦r♥ ✐♥ ②❡❛r t − x − 1✳ ❚❤✐s ✇❛②✱ t❤❡ ♣❡r✐♦❞ t❛❜❧❡s ❞♦ ♥♦t str✐❝t❧② r❡✢❡❝t t❤❡ ♠♦rt❛❧✐t② ♦❢ s✐♥❣❧❡ ❝♦❤♦rts✳ • ❚❤❡ ❝♦❤♦rt t❛❜❧❡ ✐s ❜❛s❡❞ ♦♥ t❤❡ ❛ss✉♠♣t✐♦♥ t❤❛t t❤❡ ❞❡❛t❤ r❛t❡ ✐s ❝♦♥st❛♥t ♦♥ ♣❛r❛❧❧❡❧♦❣r❛♠s TL(x, t) ∪ TU(x, t + 1)✱ ✇✐t❤ t❤❡ ❛❞✈❛♥t❛❣❡ t❤❛t ❛ ❣✐✈❡♥ ❞❡❛t❤ r❛t❡ ❛t (x, t) r❡❧❛t❡s t♦ ❧✐❢❡❧✐♥❡s ❛r✐s✐♥❣ ❢r♦♠ ❛ s✐♥❣❧❡ ❝♦❤♦rt✿ t❤❛t ♦❢ ♣❡♦♣❧❡ ❜♦r♥ ✐♥ ②❡❛r t − x✳ ❍♦✇❡✈❡r✱ t❤❡ ✐♥❢♦r♠❛t✐♦♥ ♣r♦✈✐❞❡❞ ❜② t❤✐s ❞❡❛t❤ r❛t❡ r❡✢❡❝ts ❝♦♥❞✐t✐♦♥s ♦❢ t❤❡ t✇♦ ❝♦♥s❡❝✉t✐✈❡ ②❡❛rs t ❛♥❞ t + 1✱ ❛s ✐❧❧✉str❛t❡❞ ✐♥ ❋✐❣✉r❡ ✹✳ ❋✐❣✉r❡ ✹✿ P♦♣✉❧❛t✐♦♥ ✉s❡❞ ✭✐♥ ❣r❡②✮ ❢♦r t❤❡ ❝♦♠♣✉t❛t✐♦♥ ♦❢ t❤❡ ❝♦❤♦rt ❞❡❛t❤ r❛t❡ ✭❧❡❢t✮ ❛♥❞ ♣❡r✐♦❞ ❞❡❛t❤ r❛t❡ ✭r✐❣❤t✮ ❢♦r ❛❣❡ ✻✹ ❛♥❞ ②❡❛r ✷✵✵✾✳ ❖✈❡r❛❧❧✱ ♣❡r✐♦❞ ❛♥❞ ❝♦❤♦rt t❛❜❧❡s ♣r♦✈✐❞❡ ❝♦♠♣❧❡♠❡♥t❛r② ✐♥❢♦r♠❛t✐♦♥ ❛♥❞ t❤❡✐r ✉s❡ ✐s ❞r✐✈❡♥ ❜② t❤❡ ✉♥❞❡r❧②✐♥❣ ♦❜❥❡❝t✐✈❡✳ ■♥ t❤✐s ♣❛♣❡r✱ ✇❡ ✐❧❧✉str❛t❡ ♦✉r ♠❡t❤♦❞ ♦♥ t❤❡ ❝♦♠♣✉t❛t✐♦♥ ♦❢ tr✐❛♥❣❧❡✲❜❛s❡❞ ♠♦rt❛❧✐t② t❛❜❧❡s✱ ✇❤✐❝❤ ❣❡♥❡r❛❧✐③❡ ♣❡r✐♦❞ ❛♥❞ ❝♦❤♦rt ♠♦rt❛❧✐t② t❛❜❧❡s ✐♥ ❛ ♥❛t✉r❛❧ ✇❛② ❛s t❤❡ ❞❡❛t❤ r❛t❡ ✐s ❛ss✉♠❡❞ t♦ ❜❡ ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ♦♥ ▲❡①✐s tr✐❛♥❣❧❡s✱ ✐♥st❡❛❞ ♦❢ sq✉❛r❡s ♦❢ ♣❛r❛❧❧❡❧♦❣r❛♠s✳ ❚❤✐s ✇✐❧❧ ❛❧❧♦✇ ✉s t♦ ❞r❛✇ ❛♥❛❧②s❡s ❛t ❛ ♠♦r❡ ❣r❛♥✉❧❛r s❝❛❧❡ ❝♦♠♣❛r❡❞ t♦ t❤❡ t✇♦ ✈❡rs✐♦♥s ❛✈❛✐❧❛❜❧❡ ✐♥ ♣r❛❝t✐❝❡✳ ✽✴✷✷

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✷✳✹ ▼❛✐♥ r❡s✉❧t

✷✳✹ ▼❛✐♥ r❡s✉❧t

■♥ t❤❡ ❞❡r✐✈❛t✐♦♥ ♦❢ t❤❡ ✐♥❢❡r❡♥❝❡ ❢♦r♠✉❧❛s✱ ✇❡ ❛ss✉♠❡ t❤❡ ❞❡❛t❤ r❛t❡ t♦ ❜❡ ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ♦♥ ▲❡①✐s tr✐❛♥❣❧❡s✿ ❆ss✉♠♣t✐♦♥ ✶✳ ❚❤❡ ❞❡❛t❤ r❛t❡ ✐s ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ♦♥ ▲❡①✐s tr✐❛♥❣❧❡s✱ t❤❛t ✐s ❢♦r ❡❛❝❤ ✐♥t❡❣❡r x ❛♥❞ t✱ ∀(a, s) ∈ TL(x, t), µ(a, s) = µL(x, t), ∀(a, s) ∈ TU(x, t), µ(a, s) = µU(x, t). ❋r♦♠ t❤❡ tr❛♥s♣♦rt ❝♦♠♣♦♥❡♥t ❞❡s❝r✐❜❡❞ ✐♥ ❊q✉❛t✐♦♥ ✭✶✮✱ ❢♦r ❛♥② ✉♣♣❡r ♦r ❧♦✇❡r tr✐❛♥❣❧❡ ✇❤✐❝❤ ✇❡ ❞❡♥♦t❡ T ✱ ❛♥❞ ♦♥ ✇❤✐❝❤ t❤❡ ❞❡❛t❤ r❛t❡ ✐s ❝♦♥st❛♥t ❡q✉❛❧ t♦ µT✱ ✐t ❢♦❧❧♦✇s t❤❛t✿ ZZ T ( ∂a+ ∂s)g(a, s)dads = − ZZ T

µ(a, s)g(a, s)dads = −µT

ZZ T g(a, s)dads. ❆s t❤❡ ❧❡❢t ❤❛♥❞ s✐❞❡ ✐s t❤❡ ♦♣♣♦s✐t❡ ♦❢ t❤❡ ♥✉♠❜❡r ♦❢ ❞❡❛t❤s ❛s ✐♥tr♦❞✉❝❡❞ ✐♥ ❊q✉❛t✐♦♥ ✭✺✮✱ ✐t ❢♦❧❧♦✇s ❢r♦♠ t❤❡ ♣r❡✈✐♦✉s ❡q✉❛t✐♦♥ t❤❛t t❤❡ ❞❡❛t❤ r❛t❡ ❝❛♥ ❜❡ ✇r✐tt❡♥ ❛s t❤❡ r❛t✐♦ µL(x, t) = DL(x, t) EL(x, t) ❛♥❞ µU(x, t) = DU(x, t) EU(x, t) , ✇❤❡r❡ EL(x, t) = ZZ TL(x,t) g(a, s)dads ❛♥❞ EU(x, t) = ZZ TU(x,t) g(a, s)dads, ❛r❡ t❤❡ s♦✲❝❛❧❧❡❞ ✬❡①♣♦s✉r❡s✲t♦✲r✐s❦✬ ✐♥ t❤❡ ❧♦✇❡r ❛♥❞ ✉♣♣❡r tr✐❛♥❣❧❡ r❡s♣❡❝t✐✈❡❧②✳ ◆♦✇✱ t❤❡ ♥✉♠❜❡r ♦❢ ❞❡❛t❤s ✐♥ ▲❡①✐s tr✐❛♥❣❧❡s ❜❡✐♥❣ ♦❜s❡r✈❡❞ ✭❛s ♣r♦✈✐❞❡❞ ❜② t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡✮✱ ✐t r❡♠❛✐♥s t♦ ❛♣♣r♦♣r✐❛t❡❧② ❝♦♠♣✉t❡ t❤❡ ❡①♣♦s✉r❡✲t♦✲ r✐s❦✳ ■♥ t❤❡ ❧✐t❡r❛t✉r❡ ❞❡❞✐❝❛t❡❞ t♦ ❧♦♥❣❡✈✐t② st✉❞✐❡s✱ t❤✐s q✉❛♥t✐t② ✐s ❛♣♣r♦①✐♠❛t❡❞ ❜② ❛♥♥✉❛❧ ♦❜s❡r✈❛❜❧❡s✱ s❡❡ ❡✳❣✳ P✐t❛❝❝♦ ❡t ❛❧✳ ✭✷✵✵✾✮ ❙❡❝t✐♦♥ ✷✳✸✳✹✱ ❛s ✇❡❧❧ ❛s t❤❡ ❱❡rs✐♦♥ ✺ ▼❡t❤♦❞s Pr♦t♦❝♦❧ ♦❢ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡✱ s❡❡ ❲✐❧♠♦t❤ ❡t ❛❧✳ ✭✷✵✵✼✮✳ ❚❤❡ r❡❝❡♥t ✉♣❞❛t❡ ♦❢ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ♠❡t❤♦❞♦❧♦❣② ❛❧❧♦✇✐♥❣ t♦ ✐♥❝❧✉❞❡ ♠♦♥t❤❧② ❜✐rt❤ ❞❛t❛ ✐s ❢✉rt❤❡r ❞✐s❝✉ss❡❞ ✐♥ ❙✉❜s❡❝t✐♦♥ ✷✳✻✳ ❚❤❡ st❛♥❞❛r❞ ❛♥♥✉❛❧ ❛♣♣r♦①✐♠❛t✐♦♥ ❝❛♥ ❜❡ ✐❧❧✉str❛t❡❞ ❢♦r ♣❡r✐♦❞ t❛❜❧❡s ✭s❡❡ ❙✉❜s❡❝t✐♦♥ ✷✳✸✮ ❢♦r ✇❤✐❝❤ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ✇r✐t❡s E(x, t) = Z t+1 t Z x+1 x g(a, s)dads = Z t+1 t P (x, s)ds. ❆ ♣♦ss✐❜❧❡ ❛♣♣r♦①✐♠❛t✐♦♥ ✐s t❤❡r❡❢♦r❡ ❣✐✈❡♥ ❜② t❤❡ tr❛♣❡③♦✐❞ r✉❧❡ ❛s E(x, t) ≈ 1 2[P (x, t) + P (x, t + 1)] . ✾✴✷✷

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✷✳✹ ▼❛✐♥ r❡s✉❧t

❖♥ t❤❡ ♦t❤❡r ❤❛♥❞✱ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ✭♣❡r✐♦❞ t❛❜❧❡✮ ❝❛♥ ❛❧s♦ ❜❡ ✇r✐tt❡♥ ❛s

E(x, t) = Rxx+1N (a, t)da ❛♥❞ t❤❡♥ ❛♣♣r♦①✐♠❛t❡❞ ❜② 1

2 [N (x, t) + N (x + 1, t)] = 1 2[P (x, t) + P (x + 1, t)]+ 1 2[DL(x, t) − DU(x, t)]✱ ✇❤✐❝❤ ❧❡❛❞s t♦ ❛♥♦t❤❡r ♣♦ss✐❜❧❡ ❛♣✲ ♣r♦①✐♠❛t✐♦♥✳ ◆♦t❡ t❤❛t t❤❡ ❱❡rs✐♦♥ ✺ ❡st✐♠❛t❡s ♦❢ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ r❡❧② ♦♥ ❛ ❞❡♠♦❣r❛♣❤✐❝ r❡❛s♦♥✐♥❣ ❧❡❛❞✐♥❣ t♦ ❛♥ ❛♣♣r♦①✐♠❛t✐♦♥ ✐♥ ❜❡t✇❡❡♥ t❤❡ t✇♦ ♣r❡✈✐♦✉s ♦♥❡s ✲ s❡❡ t❤❡ ❛♥❛❧②s✐s ✐♥ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮ ❢♦r ♠♦r❡ ❞❡t❛✐❧s✳ ❖✈❡r❛❧❧✱ ❝❧❛ss✐❝❛❧ ❛♣♣r♦①✐♠❛t✐♦♥s ❤❛✈❡ t❤❡ ❛❞✈❛♥t❛❣❡ ♦❢ ❜❡✐♥❣ ❜❛s❡❞ ♦♥ ♦❜s❡r✈✲ ❛❜❧❡s ♦♥❧②✱ ❧❡❛❞✐♥❣ t♦ ❛ ❝❧♦s❡❞✲❢♦r♠ ❢♦r t❤❡ ❞❡❛t❤ r❛t❡ ❡st✐♠❛t❡✳ ❚❤❡ ❝♦✉♥t❡r♣❛rt ♦❢ t❤✐s ❢❡❛t✉r❡ ✐s t❤❛t t❤❡ ✈❛❧✐❞✐t② ♦❢ t❤❡ ✉♥❞❡r❧②✐♥❣ ❛♣♣r♦①✐♠❛t✐♦♥ ❝❛♥ ❜❡ ♣✉t ✐♥t♦ q✉❡st✐♦♥ ❢♦r ②❡❛rs ✐♥ ✇❤✐❝❤ t❤❡ ♣♦♣✉❧❛t✐♦♥ ❝✉r✈❡ s 7→ P (s, x) ❛♣♣❡❛rs ❢❛r ❢r♦♠ ❧✐♥❡❛r✳ ❲❡ ♥♦✇ ❞❡t❛✐❧ t❤❡ r❡❝✉rs✐✈❡ ❛♥❞ ✐♠♣❧✐❝✐t s❝❤❡♠❡ ❢♦r ❝♦♠♣✉t✐♥❣ ❞❡❛t❤ r❛t❡ ❡st✐✲ ♠❛t❡s✱ ❜❛s❡❞ ♦♥ ❡q✉❛t✐♦♥s ❧✐♥❦✐♥❣ t❤❡ ❞❡❛t❤ r❛t❡ ✇✐t❤ t❤❡ ♦❜s❡r✈❛❜❧❡s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠ ✐♥tr♦❞✉❝❡❞ ✐♥ ❙✉❜s❡❝t✐♦♥ ✷✳✷✳ ❇❡❢♦r❡ st❛t✐♥❣ t❤❡ ♠❛✐♥ r❡s✉❧t✱ ✇❡ ✐♥tr♦❞✉❝❡ t✇♦ ❦❡② q✉❛♥t✐t✐❡s✿ ✜rst✱ t❤❡ ▲❛♣❧❛❝❡ tr❛♥s❢♦r♠ ♦❢ t❤❡ r❛♥❞♦♠ ✈❛r✐❛❜❧❡ ✬❞❛t❡ ♦❢ ❜✐rt❤ ✐♥ ②❡❛r y✬✱ ✐♥tr♦❞✉❝❡❞ ❛s✿ Ly(θ) = R1 0 g(0, y + v) exp(−θv)dv R1 0 g(0, y + v)dv , ❛♥❞ s❡❝♦♥❞✱ t❤❡ ❝✉♠✉❧❛t✐✈❡ ❣❛✐♥ ✐♥ ❧♦♥❣❡✈✐t② ❛t ❛❣❡ x ❧❛st ❜✐rt❤❞❛② ✇✐t❤✐♥ t❤❡ s❛♠❡ ❝♦❤♦rt ❜♦r♥ ✐♥ ②❡❛r t − x ✭❛ ❞✐❛❣♦♥❛❧ ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠✮✱ t❤❛t ✐s ❜❡t✇❡❡♥ t❤♦s❡ ❜♦r♥ ❛t ❡①❛❝t t✐♠❡ t − x ❛♥❞ t❤♦s❡ ❜♦r♥ ❛t t❤❡ ❡♥❞ ♦❢ t❤❡ ②❡❛r [t − x, t − x + 1)✱ ❞❡✜♥❡❞ ❜②✿ H(x, t) = x−1 X y=0

µU(y, t − x + y + 1) − µL(y, t − x + y), x ∈ N

∗ . ✭✼✮ ❚❤❡ r❡s✉❧t ❛t t❤❡ ❝♦r❡ ♦❢ t❤❡ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ✐s st❛t❡❞ ❜❡❧♦✇✿ Pr♦♣♦s✐t✐♦♥ ✶✳ ❈♦♥s✐❞❡r t❤❡ tr❛♥s♣♦rt ❊q✉❛t✐♦♥ ✭✶✮✳ ❯♥❞❡r ❆ss✉♠♣t✐♦♥ ✶✱ t❤❡ ❢♦❧❧♦✇✐♥❣ ❡q✉❛❧✐t✐❡s ❤♦❧❞✿ exp (−µL(x, t)) Lt−x H(x, t) − µL(x, t)  =  1 −DL(x, t) N (x, t)  Lt−x H(x, t)  , ✭✽✮ ❛♥❞ Lt−x−1 H(x, t − 1) − µL(x, t − 1)  =  1 + DU(x, t) N (x + 1, t)  Lt−x−1 H(x, t − 1) − µL(x, t − 1) + µU(x, t)  . ✭✾✮ ❚❤❡ ♣r♦♦❢ ✐s ❞❡t❛✐❧❡❞ ✐♥ t❤❡ ♥❡①t ♣❛rt✱ ❛❧♦♥❣ ✇✐t❤ ❛ ❞❡t❛✐❧❡❞ ❞✐s❝✉ss✐♦♥ ✐♥ ❙✉❜✲ s❡❝t✐♦♥ ✷✳✻✳ ❚❤❡ r❡s✉❧t✐♥❣ ❛❧❣♦r✐t❤♠ ✐s ❞❡s❝r✐❜❡❞ ✐♥ ❙❡❝t✐♦♥ ✸✳ ✶✵✴✷✷

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✷✳✺ Pr♦♦❢ ♦❢ Pr♦♣♦s✐t✐♦♥ ✶

✷✳✺ Pr♦♦❢ ♦❢ Pr♦♣♦s✐t✐♦♥ ✶

❚♦ ♣r♦✈❡ ✭✽✮✱ ❧❡t ✉s ✜rst ❢♦❝✉s ♦♥ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ✐♥ t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡ EL(x, t) = Rt+1 t Rx+s−t x g(a, s)dads. ❆❝❝♦r❞✐♥❣ t♦ t❤❡ tr❛♥s♣♦rt ❡q✉❛t✐♦♥ ✭✶✮✱ t❤❡ ♣♦♣✉❧❛t✐♦♥ ❞❡♥s✐t② ✐♥ t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡ ❝❛♥ ❜❡ ❡①♣r❡ss❡❞ ❛s g(a, s) = g(x, s − a + x) exp  − Z a x µ(u, s − a + u)du  = g(x, s − a + x) exp (−(a − x)µL(x, t)) . ✇❤❡r❡ t❤❡ ❧❛st ❡q✉❛❧✐t② ❝♦♠❡s ❢r♦♠ t❤❡ ❛ss✉♠♣t✐♦♥ ♦❢ ❛ ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ❞❡❛t❤ r❛t❡ ♦♥ ▲❡①✐s tr✐❛♥❣❧❡s✳ ❇② t❤❡ ❝❤❛♥❣❡ ♦❢ ✈❛r✐❛❜❧❡ v ← s − a + x − t✱ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ❝❛♥ t❤❡♥ ❜❡ r❡✇r✐tt❡♥ ❛s EL(x, t) = Z t+1 t Z x+s−t x

g(x, s − a + x) exp (−(a − x)µL(x, t)) dads

= Z 1 0 Z t+1 t+v g(x, t + v) exp (−(s − v − t)µL(x, t)) dsdv. ❇② str❛✐❣❤t❢♦r✇❛r❞ ❝♦♠♣✉t❛t✐♦♥✱ ♦♥❡ ✜♥❛❧❧② ❣❡ts t❤❡ ❢♦❧❧♦✇✐♥❣ ❡①♣r❡ss✐♦♥ ❢♦r t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ✐♥ t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡✿ EL(x, t) = Z 1 0 g(x, t + v)1 − exp ((v − 1)µL(x, t)) µL(x, t) dv. ✭✶✵✮ ❆❧s♦ ♥♦t❡ t❤❛t DL(x, t) = µL(x, t)EL(x, t) = R1 0 g(x, t+v) (1 − exp ((v − 1)µL(x, t))) dv ❛♥❞ N(x, t) =R1 0 g(x, t + v)dv s♦ t❤❛t N (x, t) − DL(x, t) = Z 1 0 g(x, t + v) exp ((v − 1)µL(x, t)) dv. ▲❡t ✉s ♥♦✇ ❞❡r✐✈❡ t❤❡ ♣♦♣✉❧❛t✐♦♥ ❞❡♥s✐t② ❛t ❡①❛❝t ❛❣❡ x✱ ❢♦r ❛♥② v ∈ [0, 1)✱ g(x, t + v) = g(0, t − x + v) exp  − Z x 0 µ(u, t − x + v + u)du  = g(0, t − x + v) exp − x−1 X y=0 Z y+1 y µ(u, t − x + v + u)du ! = g(0, t − x + v) exp − x−1 X y=0 Z y+1−v y µ(u, t − x + v + u)du − x−1 X y=0 Z y+1 y+1−v µ(u, t − x + v + u)du ! = g(0, t − x + v) exp −(1 − v) x−1 X y=0 µL(y, t − x + y) − v x−1 X y=0 µU(y, t − x + y + 1) ! = S(x, t)g(0, t − x + v) exp (−vH(x, t)) , ✭✶✶✮

✇❤❡r❡ S(x, t) = exp−Px−1y=0µL(y, t − x + y)



✐s t❤❡ s✉r✈✐✈❛❧ ❢✉♥❝t✐♦♥ ❛t ❛❣❡ x ❢♦r ✐♥❞✐✈✐❞✉❛❧s ✇❤✐❝❤ ❛tt❛✐♥❡❞ ✭❡①❛❝t✮ ❛❣❡ x ❛t ✭❡①❛❝t✮ t✐♠❡ t✱ ❛♥❞ ✇❤❡r❡ t❤❡ ❝✉♠✉❧❛t✐✈❡

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✷✳✻ ❉✐s❝✉ss✐♦♥ ❞❡❛t❤ r❛t❡ ❞✐✛❡r❡♥t✐❛❧ ✇✐t❤✐♥ t❤❡ ❝♦❤♦rt H(x, t) ❤❛s ❜❡❡♥ ✐♥tr♦❞✉❝❡❞ ✐♥ ❊q✉❛t✐♦♥ ✭✼✮✳ ▲❡t ✉s ♥♦✇ ❝♦♠❜✐♥❡ t❤❡ ♣r❡✈✐♦✉s r❡s✉❧ts t♦ ❣❡t N (x, t) − DL(x, t) = S(x, t)e −µL(x,t) Z 1 0 g(0, t − x + v)e−v(H(x,t)−µL(x,t)) dv, ❛♥❞ ✜♥❛❧❧②✱ ❧❡t ✉s ❛♣♣❧② s♦♠❡ r❡♥♦r♠❛❧✐③❛t✐♦♥ ♦❢ t❤❡ r✐❣❤t ❤❛♥❞ s✐❞❡✱ ✜rst ❜② N(x, t) ❛♥❞ s❡❝♦♥❞ ❜② R1 0 g(0, t − x + v)dv t♦ ❣❡t t❤❡ ❢♦❧❧♦✇✐♥❣ ❢♦r♠✉❧❛✱ ✇❤✐❝❤ r❡❞✉❝❡s t♦ ❊q✉❛t✐♦♥ ✭✽✮✿ 1 − DL(x, t) N (x, t) = S(x, t)e−µL(x,t)R1 0 g(0, t − x + v)e˜ −v(H(x,t)−µL(x,t))dv S(x, t)R01˜g(0, t − x + v)e−vH(x,t) dv . ✇❤❡r❡ ˜g(0, t − x + v) = g(0,t−x+v) R1 0 g(0,t−x+v)dv ✳ ❚❤❡ ♣r♦♦❢ ♦❢ ✭✾✮ ❢♦❧❧♦✇s s✐♠✐❧❛r❧②✳ ❙✐♥❝❡ EU(x, t) = Rt+1 t Rx+1 x+s−tg(a, s)dads ❛♥❞

g(a, s) = g(x + 1, s + x + 1 − a) exp ((x + 1 − a)µU(x, t))✱ t❤❡♥ ❜② ❝❤❛♥❣✐♥❣ ✈❛r✐❛❜❧❡s✱

♦♥❡ ❣❡ts EU(x, t) = R1 0 g(x + 1, t + v) exp(vµU(x,t))−1 µU(x,t) dv,s♦ t❤❛t N (x + 1, t) + DU(x, t) = Z 1 0 g(x + 1, t + v) exp (vµU(x, t)) dv. ❚❤❡♥ ❛s g(x+1, t+v) = g(0, t−x−1+v)S(x+1, t) exp (−vH(x + 1, t))✱ ♦♥❡ ✜♥❛❧❧② ♦❜t❛✐♥s  1 + DU(x, t) N (x + 1, t)  Lt−x−1(H(x + 1, t)) = Lt−x−1(H(x + 1, t) − µU(x, t)) , ✇❤✐❝❤ ❧❡❛❞s t♦ t❤❡ r❡s✉❧t✱ ❛s t❤❡ ❢♦❧❧♦✇✐♥❣ ❡q✉❛❧✐t② ✐s ✈❡r✐✜❡❞ ❢r♦♠ t❤❡ ❞❡✜♥✐t✐♦♥ ✐♥ ❊q✉❛t✐♦♥ ✭✼✮✿ H(x + 1, t) = H(x, t − 1) + µU(x, t) − µL(x, t − 1).

✷✳✻ ❉✐s❝✉ss✐♦♥

❊①♣♦s✉r❡✲t♦✲r✐s❦ ✐♥t❡r♣r❡t❛t✐♦♥✳ ❚❤❡ ❡q✉❛❧✐t② ✭✶✵✮ ❝❛♥ ❜❡ ✐♥t❡r♣r❡t❡❞ ❛s ❢♦❧✲ ❧♦✇s✿ ❢♦r ❡❛❝❤ ✐♥❞✐✈✐❞✉❛❧ ❛tt❛✐♥✐♥❣ ❡①❛❝t ❛❣❡ x ❛t t✐♠❡ t + v✱ ✐ts ❝♦♥tr✐❜✉t✐♦♥ t♦ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ✐♥ t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡ ✐s 1−exp((v−1)µL(x,t)) µL(x,t) ✱ ✇❤✐❝❤ ❞❡♣❡♥❞s ♦♥ t❤❡ ✉♥♦❜s❡r✈❡❞ ❞❡❛t❤ r❛t❡ t♦ ❜❡ ❡st✐♠❛t❡❞✳ ❚❤✐s ❝♦♥tr❛sts ✇✐t❤ ❝❧❛ss✐❝❛❧ ♠❡t❤♦❞s ✇❤✐❝❤ ❝♦♠♣✉t❡ ❛♣♣r♦①✐♠❛t✐♦♥s ♦❢ t❤❡ ❡①♣♦s✉r❡✲t♦✲r✐s❦ ❜❛s❡❞ ♦♥ ♦❜s❡r✈❛❜❧❡s✳ ❆t ✜rst ♦r✲ ❞❡r✱ ❛ss✉♠✐♥❣ µL(x, t) << 1✱ ♦♥❡ r❡❝♦✈❡rs t❤❛t EL(x, t) ≈ R1 0 g(x, t + v)(1 − v)dv ❛♥❞ t❤❡ r❡❧❛t❡❞ ✐♥t❡r♣r❡t❛t✐♦♥ t❤❛t t❤❡ ❝♦♥tr✐❜✉t✐♦♥ ♦❢ ❛♥② ✐♥❞✐✈✐❞✉❛❧ ✇❤✐❝❤ ❛tt❛✐♥❡❞ ❡①❛❝t ❛❣❡ x ❛t t✐♠❡ t + v ❛♥❞ ❧✐✈✐♥❣ t❤r♦✉❣❤ t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡ ✐s s✐♠♣❧② 1 − v ❛s ✐t ❝❛♥ ❜❡ ♠❡❛s✉r❡❞ ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠✳ ✶✷✴✷✷

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✷✳✻ ❉✐s❝✉ss✐♦♥ ❇✐❛s❡❞ ❜✐rt❤❞❛② ❞❡♥s✐t②✳ ❚❤❡ ❢♦r♠✉❧❛ ❞❡r✐✈❡❞ ✐♥ ✭✶✶✮ s❤♦✇s t❤❛t t❤❡ ❜✐rt❤✲ ❞❛②s ❞❡♥s✐t② ❛t s♦♠❡ ❛❣❡ x ✐s ❡①♣♦♥❡♥t✐❛❧❧② ❜✐❛s❡❞ t❤r♦✉❣❤ H(x, t) ❝♦♠♣❛r❡❞ t♦ t❤❡ ✐♥✐t✐❛❧ ❜✐rt❤❞❛②s ❞✐str✐❜✉t✐♦♥ ✭❛t ❛❣❡ ③❡r♦✮✳ ❚❤✐s ✐s tr✉❡ ✐♥ ❣❡♥❡r❛❧ ✐♥ t❤❡ tr✐✲ ❛♥❣❧❡ ♠♦❞❡❧ ❢♦r t❤❡ ♣✐❡❝❡✇✐s❡ ❝♦♥st❛♥t ❞❡❛t❤ r❛t❡ ✭❆ss✉♠♣t✐♦♥ ✶✮✱ ❛s ✇❡❧❧ ❛s ✐♥ t❤❡ ♣❡r✐♦❞ t❛❜❧❡ ❢♦r ✇❤✐❝❤ t❤❡ ❝✉♠✉❧❛t✐✈❡ ❞❡❛t❤ r❛t❡ ❞✐✛❡r❡♥❝❡ ♠❛tr✐① r❡❞✉❝❡s t♦

H(x, t) =Px−1y=0µ(y, t − x + y + 1) − µ(y, t − x + y) ✇❤❡r❡ µ(x, t) ❞❡♥♦t❡s t❤❡ ♣❡r✐♦❞

❞❡❛t❤ r❛t❡ ❢♦r t❤❡ sq✉❛r❡ (x, t)✳ ▼♦r❡♦✈❡r✱ ❛s ♦♥❡ ❡①♣❡❝ts ✐♥ ❣❡♥❡r❛❧ s♦♠❡ ♠♦rt❛❧✐t② ✐♠♣r♦✈❡♠❡♥t ♦✈❡r t❤❡ ②❡❛rs✱ ❛❣❡ ❜❡✐♥❣ ✜①❡❞✱ ♦♥❡ ♠❛② ❜❡ ✐♥t❡r❡st❡❞ ✐♥ ✐♥t❡r♣r❡t✐♥❣ t❤❡ ❝❛s❡ H(x, t) < 0 ✲ ✐♥ t❤✐s s✐t✉❛t✐♦♥✱ ♦♥❡ s❡❡s t❤❛t t❤❡ ✐♥✐t✐❛❧ ❜✐rt❤❞❛②s ❞✐str✐✲ ❜✉t✐♦♥ ✐s ❞✐st♦rt❡❞ t♦ t❤❡ ❤✐❣❤❡st ❜✐rt❤❞❛②s ✭②♦✉♥❣❡st ✐♥❞✐✈✐❞✉❛❧s✮ ✐♥ t❤❡ ❝♦❤♦rt ❛s ❛❣❡ ❣♦❡s✳ ❚❤✐s ❞❡♠♦♥str❛t❡s ❤♦✇ ❡✈❡♥ ✐♥ ❛ ❞✐s❝r❡t❡ t✐♠❡ s♣❡❝✐✜❝❛t✐♦♥✱ ✐♥❞✐✈✐❞✉❛❧s ✐♥ t❤❡ s❛♠❡ ❝♦❤♦rt ♠❛② ❡①♣❡r✐❡♥❝❡ ❞✐✛❡r❡♥t ❞❡❛t❤ r❛t❡s ♦✈❡r ❧✐❢❡ ✭♠♦r❡ ♣r❡❝✐s❡❧② t❤❡② ♣❛ss t❤r♦✉❣❤ t❤❡ s❛♠❡ r❛t❡s ❜✉t ❞♦ ♥♦t ✬s♣❡♥❞ t❤❡ s❛♠❡ t✐♠❡✬ ✐♥ ❡❛❝❤ tr✐❛♥✲ ❣❧❡ ♦r sq✉❛r❡✱ s♦ t❤❛t t❤❡ r❡s✉❧t✐♥❣ s✉r✈✐✈❛❧ ❢✉♥❝t✐♦♥s ❛r❡ ❞✐✛❡r❡♥t✮✳ ❍♦✇❡✈❡r✱ ✐t ✐s ✐♥t❡r❡st✐♥❣ t♦ ♥♦t❡ t❤❛t ❢♦r t❤❡ ❝♦❤♦rt t❛❜❧❡✱ ✇❤✐❝❤ ❜② ❞❡✜♥✐t✐♦♥ ❛ss✉♠❡s t❤❛t µ(y, t − x + y + 1) = µ(y, t − x + y)✱ t❤❡ H ♠❛tr✐① ✈❛♥✐s❤❡s✱ s♦ t❤❛t t❤❡ ✐♥✐t✐❛❧ ❜✐rt❤❞❛②s ❞✐str✐❜✉t✐♦♥ ♣❡r❢❡❝t❧② ♣r♦♣❛❣❛t❡s t♦✇❛r❞s ❤✐❣❤❡st ❛❣❡s✳ ❈❧♦s❡❞ ♣♦♣✉❧❛t✐♦♥ ❛ss✉♠♣t✐♦♥✳ ❉✉❡ t♦ t❤❡ r❡♥♦r♠❛❧✐③❛t✐♦♥ ✐♥ t❤❡ ✜♥❛❧ r❡s✉❧t ✭✽✮✱ t❤❡ ❞❡❛t❤ r❛t❡ r❡❧❛t❡s t♦ t❤❡ ❝❧♦s❡st ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡❀ t❤❡r❡❢♦r❡✱ t❤❡ ❛ss✉♠♣t✐♦♥ t❤❛t t❤❡ ♣♦♣✉❧❛t✐♦♥ ✐s ❝❧♦s❡❞ ✐s ♦♥❧② ❧♦❝❛❧ ✐♥ t❡r♠s ♦❢ ♣♦♣✉❧❛t✐♦♥ ❝♦✉♥t✱ ❛s t❤❡ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡ N ♠❛② ✐♥❝❧✉❞❡ ♣♦♣✉❧❛t✐♦♥ ✢♦✇ ❡✛❡❝ts✳ ❆❧s♦✱ t❤❡ ❛ss✉♠♣t✐♦♥ ♦❢ ❛ ❝❧♦s❡❞ ♣♦♣✉❧❛t✐♦♥ ✐♠♣❧✐❡s ❤❡r❡ t❤❛t t❤❡ ❜✐rt❤❞❛②s ❞✐str✐❜✉t✐♦♥ ❛t s♦♠❡ ❛❣❡ ✐s ♦❜t❛✐♥❡❞ ❛s ❛ tr❛♥s❢♦r♠❛t✐♦♥ ♦❢ t❤❡ ✐♥✐t✐❛❧ ❜✐rt❤ ❞✐str✐❜✉t✐♦♥ ✲ t♦ t❤✐s ❡①t❡♥t t❤❡ ❛ss✉♠♣t✐♦♥ ❛♣♣❧✐❡s ❣❧♦❜❛❧❧② ✐♥ ❡❛❝❤ ❝♦❤♦rt✳ ▲✐♥❦ ✇✐t❤ ❡st✐♠❛t❡s ♦❢ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡✳ ■t ✐s ✇♦rt❤ ♠❡♥✲ t✐♦♥✐♥❣ t❤❛t ❛t t❤❡ t✐♠❡ ♦❢ ✇r✐t✐♥❣✱ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ r❡❧❡❛s❡❞ ❛♥ ✉♣❞❛t❡ ♦♥ ❋❡❜r✉❛r② ✷✵✶✽✱ ✐♥❝❧✉❞✐♥❣ ✐♥ ♣❛rt✐❝✉❧❛r ❛ r❡✈✐s✐♦♥ ♦❢ ❡①♣♦s✉r❡ ❝❛❧❝✉❧❛t✐♦♥ ❜❛s❡❞ ♦♥ ♠♦♥t❤❧② ❜✐rt❤ ❝♦✉♥ts✳ ❲❡ ♥♦✇ ♠❛❦❡ t❤❡ ❧✐♥❦ ✇✐t❤ ❜♦t❤ t❤❡ ♥❡✇ ❱❡rs✐♦♥ ✻ ❛♥❞ t❤❡ ♦❧❞ ❱❡rs✐♦♥ ✺ ♦❢ t❤❡ ❍▼❉ ▼❡t❤♦❞s Pr♦t♦❝♦❧✳ ❋r♦♠ ✭✶✵✮✱ ✐t ❝❛♥ ❜❡ s❤♦✇♥ ❜② ♣❡r❢♦r♠✐♥❣ ❛ ✜rst ♦r❞❡r ❡①♣❛♥s✐♦♥ ✐♥ µL(x, t)t❤❛t EL(x, t) ≈ EL(1)(x, t) − µL(x, t)EL(2)(x, t), ✇❤❡r❡ EL1(x, t) := N (x, t)  1 + L ′ t−x(H(x, t)) Lt−x(H(x, t))  , ❛♥❞ EL(2)(x, t) = 1 2N (x, t)  1 + 2L ′ t−x(H(x, t)) + L ′′ t−x(H(x, t)) Lt−x(H(x, t))  . ✶✸✴✷✷

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▲❡t ✉s ❞❡♥♦t❡ ❜② Bt−x t❤❡ r❛♥❞♦♠ ✈❛r✐❛❜❧❡ ✇✐t❤ ✈❛❧✉❡s ✐♥ [0, 1] t❤❛t r❡♣r❡s❡♥ts t❤❡ t✐♠❡ ♦❢ ❜✐rt❤ ✐♥ t❤❡ ②❡❛r t − x✱ ✇✐t❤ ♠❡❛♥ mt−x := E [Bt−x] ❛♥❞ ✈❛r✐❛♥❝❡ σ2 t−x:= Var(Bt−x)✳ ❯♥❞❡r t❤❡ ❛ss✉♠♣t✐♦♥ H(x, t) = 0✱ t❤❛t ✐s ♥♦ ♠♦rt❛❧✐t② ✐♠♣r♦✈❡♠❡♥t ❜❡t✇❡❡♥ t❤❡ ②♦✉♥❣❡st ❛♥❞ ♦❧❞❡st ✐♥❞✐✈✐❞✉❛❧s ✇✐t❤✐♥ t❤❡ s❛♠❡ ❝♦❤♦rt✱ ♦♥❡ ❝❛♥ ✇r✐t❡ EL(x, t) ≈ N (x, t) (1 − mt−x) − 1 2µL(x, t)N (x, t) (1 − mt−x) 2+ σ2 t−x  . ◆♦t❡ ❛❣❛✐♥ t❤❛t t❤❡ ❛ss✉♠♣t✐♦♥ H(x, t) = 0 ✐s ♥♦t ❝♦♥s✐st❡♥t ✇✐t❤ t❤❡ ♣✐❡❝❡✇✐s❡ ❝♦♥✲ st❛♥t ❞❡❛t❤ r❛t❡ ❛ss✉♠♣t✐♦♥ ♦♥ ▲❡①✐s tr✐❛♥❣❧❡s✱ ♥♦r ✇✐t❤ t❤❡ ❢r❛♠❡✇♦r❦ ✉♥❞❡r❧②✐♥❣ t❤❡ ♣❡r✐♦❞ t❛❜❧❡s✳ ◆♦✇✱ ✐❢ ♦♥❡ ✉s❡s ✭✻✮ ❛♥❞ r❡♣❧❛❝❡s µL(x, t) = D L(x,t) EL(x,t) ❜② ✐ts ③❡r♦ ♦r❞❡r ❛♣♣r♦①✐♠❛✲ t✐♦♥ µL(x, t) ≈ DL(x, t) N (x, t) (1 − mt−x) , ♦♥❡ ✜♥❛❧❧② ♦❜t❛✐♥s t❤❡ ❢♦r♠✉❧❛ ✭✺✶✮ ❞✐s♣❧❛②❡❞ ✐♥ t❤❡ ❱❡rs✐♦♥ ✻ ✐♥ t❤❡ ❍▼❉ ♠❡t❤♦❞s ♣r♦t♦❝♦❧✿ EL(x, t) ≈ P (x, t + 1) (1 − mt−x) + DL(x, t) 2(1 − mt−x) (1 − mt−x)2− σt−x2  . ❋✐♥❛❧❧②✱ ✐❢ ♦♥❡ ❛ss✉♠❡s ❜✐rt❤s t♦ ❜❡ ✉♥✐❢♦r♠❧② ❞✐str✐❜✉t❡❞✱ t❤❡♥ mt−x = 12 ❛♥❞ σ2 t−x= 1/12s♦ t❤❛t t❤❡ ❝❧❛ss✐❝❛❧ ❢♦r♠✉❧❛ ✐♥ ❱❡rs✐♦♥ ✺ ♠❡t❤♦❞s ♣r♦t♦❝♦❧ ✐s r❡❝♦✈❡r❡❞ ✭s❡❡ ❆♣♣❡♥❞✐① ❊ t❤❡r❡✐♥ ❢♦r t❤❡ ♦r✐❣✐♥❛❧ ❞❡r✐✈❛t✐♦♥✮✿ EL(x, t) ≈ 1 2P (x, t + 1) + 1 6DL(x, t).

✸ ◆✉♠❡r✐❝❛❧ r❡s✉❧ts

❇❛s❡❞ ♦♥ Pr♦♣♦s✐t✐♦♥ ✶✱ ♦♥❡ ❝❛♥ ❡①❤✐❜✐t ❛ r❡❝✉rs✐✈❡ ❛♥❞ ✐♠♣❧✐❝✐t s❝❤❡♠❡ ❢♦r ❝♦♠✲ ♣✉t✐♥❣ t❤❡ ❞❡❛t❤ r❛t❡s✱ ❛s ❞❡s❝r✐❜❡❞ ❜❡❧♦✇✳ ❆❧❣♦r✐t❤♠ ✶✳ ❋♦r ❛❣❡ x st❛rt✐♥❣ ❛t ③❡r♦✿ ✭✐✮ ❙♦❧✈❡ ❊q✉❛t✐♦♥ ✭✽✮ t♦ ❡st✐♠❛t❡ t❤❡ ❞❡❛t❤ r❛t❡ µL(x, t) ❢♦r t❤❡ ❧♦✇❡r tr✐❛♥❣❧❡s ♦❢ ❛♥② ❛✈❛✐❧❛❜❧❡ ②❡❛r t✱ ✭✐✐✮ ❚❤❡♥ ❜❛s❡❞ ♦♥ t❤❡ ♣r❡✈✐♦✉s ❡st✐♠❛t❡s✱ s♦❧✈❡ ❊q✉❛t✐♦♥ ✭✾✮ t♦ ✐♥❢❡r t❤❡ ❞❡❛t❤ r❛t❡ µU(x, t) ❢♦r t❤❡ ✉♣♣❡r tr✐❛♥❣❧❡s ♦❢ ❛♥② ❛✈❛✐❧❛❜❧❡ ②❡❛r t✱ ✭✐✐✮ ❈♦♠♣✉t❡ t❤❡ ✈❛❧✉❡ ❢♦r H(x + 1, t) = H(x, t − 1) + µU(x, t) − µL(x, t − 1) ❢♦r ❛❧❧ ♣♦ss✐❜❧❡ ②❡❛rs t✱ ❧❡t x ← x + 1 ❛♥❞ ❣♦ t♦ st❡♣ ✭✐✮ ✳ ❘❡♠❛r❦ ✶✳ ◆♦t❡ t❤❛t t❤❡ ♠❡t❤♦❞ ✐s ♣❛st ❞❡♣❡♥❞❡♥t ✲ t❤✐s ✐s ♥❛t✉r❛❧ ❛s ❛♥② ❝❤❛♥❣❡ ✐♥ ♣❛st ❞❡❛t❤ r❛t❡s ♠♦❞✐❢② t❤❡ ❢✉t✉r❡ ❜✐rt❤❞❛②s ❞✐str✐❜✉t✐♦♥ ✐♥ t❤❡ ❝♦❤♦rt✳ ❚❤✐s ✇❛②✱ ✶✹✴✷✷

(15)

❛♥② r❡✈✐s✐♦♥ ♦❢ ♣❛st ❞❡❛t❤ ♦r ♣♦♣✉❧❛t✐♦♥ ❝♦✉♥t ❛t (x, t)✱ ✇❤✐❝❤ ♠❛② ♦❝❝✉r ✐♥ ♣r❛❝t✐❝❡✱ r❡q✉✐r❡s t❤❡ r❡✲✉s❡ ♦❢ t❤❡ ♠❡t❤♦❞♦❧♦❣② ✇❤✐❝❤ ✇✐❧❧ ♣r♦✈✐❞❡ ❛♥ ✉♣❞❛t❡ ♦❢ t❤❡ ♠♦rt❛❧✐t② r❛t❡s ❛t (y, t + y − x) ❢♦r y ≥ x✳ ■♥ ❋✐❣✉r❡s ✺ t♦ ✽✱ ✇❡ ❞❡♣✐❝t t❤❡ ❞❡❛t❤ r❛t❡ ❡st✐♠❛t❡s ♦❜t❛✐♥❡❞ ✇✐t❤ t❤❡ ♠❡t❤♦❞ ❞❡✈❡❧♦♣❡❞ ✐♥ t❤✐s ♣❛♣❡r ❛♣♣❧✐❡❞ t♦ ❋r❡♥❝❤ ❞❛t❛ s♦✉r❝❡❞ ❢r♦♠ t❤❡ ❍✉♠❛♥ ▼♦rt❛❧✐t② ❉❛t❛❜❛s❡ ✭❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ ❡st✐♠❛t❡s✱ ❋✐❣✉r❡ ✶ ❛♥❞ ♥✉♠❜❡r ♦❢ ❞❡❛t❤s ✐♥ ▲❡①✐s tr✐❛♥❣❧❡s✱ ❋✐❣✉r❡ ✷✮ ❛♥❞ t❤❡ ❍✉♠❛♥ ❋❡rt✐❧✐t② ❉❛t❛❜❛s❡ ✭❜✐rt❤s ❜② ♠♦♥t❤s✱ ❋✐❣✉r❡ ✸✮✳ ❚❤❡ ♥✉♠❜❡r ♦❢ ❜✐rt❤s ❜② ♠♦♥t❤ ❛r❡ ✉s❡❞ t♦ ❛♣♣r♦①✐♠❛t❡ t❤❡ ▲❛♣❧❛❝❡ tr❛♥s❢♦r♠ ♦❢ t❤❡ ❜✐rt❤❞❛②s ❞✐str✐❜✉t✐♦♥ ✇❤✐❝❤ ✐s ✉s❡❞ ✐♥ t❤❡ ✐♥❢❡r❡♥❝❡ ♣r♦❝❡ss✳ ❚❤❡ r❡s✉❧ts ❛r❡ ❝♦♠♣❛r❡❞ ✇✐t❤ ❡st✐♠❛t❡s ❛s t❤❡② ✇♦✉❧❞ ❜❡ ❝❧❛ss✐❝❛❧❧② ❝♦♠♣✉t❡❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♦❜s❡r✈❛❜❧❡s ✭s❡❡ ❲✐❧♠♦t❤ ❡t ❛❧✳ ✭✷✵✵✼✮ ❛♥❞ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮ ❢♦r ❢✉rt❤❡r ❞❡t❛✐❧s✮✿ c µL(x, t) = DL(x, t) 1 2N (x, t) − 1 3DL(x, t) ❛♥❞ cµU(x, t) = DU(x, t) 1 2N (x + 1, t) + 1 3DU(x, t) . ❊❛❝❤ ✜❣✉r❡ ✐♥❝❧✉❞❡s ♦♥ t❤❡ r✐❣❤t t❤❡ r❛t✐♦ ❜❡t✇❡❡♥ t❤❡ ♥❡✇ ❛♥❞ t❤❡ ♦❧❞ ❡st✐♠❛t❡✱ ✇❤✐❝❤ ❤❡❧♣s q✉❛♥t✐❢② t❤❡ ❞✐✛❡r❡♥❝❡s ❜❡t✇❡❡♥ ❜♦t❤✳ ❋✐rst✱ t❤❡ r❛t✐♦ ✐s ❢♦r s❡✈❡r❛❧ ❛❣❡ ❝❧❛ss❡s ❝❧♦s❡ t♦ ♦♥❡✱ ✇❤✐❝❤ ✐♥❞✐❝❛t❡s t❤❛t t❤❡ ♥❡✇ ❡st✐♠❛t❡ ❞♦❡s ♥♦t ❞✐✛❡r ♠✉❝❤ ❢r♦♠ t❤❡ ❝❧❛ss✐❝❛❧ ♦♥❡✱ ✐♥ ♦t❤❡r ✇♦r❞s t❤❛t t❤❡ ❝❧❛ss✐❝❛❧ ❛♣♣r♦①✐♠❛t✐♦♥ ✐s ✈❛❧✐❞✳ ❍♦✇❡✈❡r✱ ♦♥❡ s❡❡s str♦♥❣ ❞❡✈✐❛t✐♦♥s ❢♦r s♣❡❝✐✜❝ ❛❣❡s ✐♥ t✐♠❡✱ ❛♥❞ t❤✐s tr❛♥s❧❛t❡s ♦✈❡r t✐♠❡ ❛♥❞ ❛❣❡s✱ s♦ t❤❛t ✐t ❛♣♣❡❛rs t❤❛t t❤❡ ❛♥♦♠❛❧✐❡s ❜❡❧♦♥❣ t♦ s♣❡❝✐✜❝ ❣❡♥❡r❛t✐♦♥s✳ ❆s ❞✐s♣❧❛②❡❞✱ r❡❧❛t✐✈❡ ❞✐s❝r❡♣❛♥❝✐❡s ❜❡t✇❡❡♥ t❤❡ t✇♦ ❡st✐♠❛t❡s ❝❛♥ r❡❛❝❤ ✉♣ t♦ ❛r♦✉♥❞ ✰✴✲ ✷✵✪✳ ❚♦ ❛ss❡ss t❤✐s s♣❡❝✐✜❝✐t②✱ ✇❡ ❞❡♣✐❝t ✐♥ ❋✐❣✉r❡ ✾ ♠♦rt❛❧✐t② ✐♠♣r♦✈❡♠❡♥t r❛t❡s s❡♣❛r❛t❡❞ ❜❡t✇❡❡♥ ✉♣♣❡r ❛♥❞ ❧♦✇❡r tr✐❛♥❣❧❡s ❛s µL(x, t + 1) − µL(x, t) µL(x, t) ❛♥❞ µU(x, t + 1) − µU(x, t) µU(x, t) . ❈❧❡❛r❧②✱ t❤❡ ✐s♦❧❛t❡❞ ❝♦❤♦rt ❡✛❡❝ts ❞✐s❛♣♣❡❛r ✐♥ t❤❡ ♥❡✇ ♠♦rt❛❧✐t② t❛❜❧❡s✿ ♠❛✐♥❧② t❤❡ ❞✐❛❣♦♥❛❧s ❛r♦✉♥❞ ✶✾✶✺ ❛♥❞ ✶✾✷✵✱ ❛♥❞ t♦ ❛ ❧♦✇❡r ❡①t❡♥t t❤♦s❡ ❜♦r♥ ❛r♦✉♥❞ ✶✾✹✵❀ ♥♦t❡ t❤❛t t❤✐s ✐♥❞❡❡❞ ❝♦rr❡s♣♦♥❞s t♦ t❤❡ s❤♦❝❦s ✐♥ ❜✐rt❤ ♥✉♠❜❡rs ❛s ✐❧❧✉str❛t❡❞ ✐♥ ❋✐❣✉r❡ ✸✱ ✇❤✐❝❤ ❝♦♥✜r♠s ❢r♦♠ ❛ ♠❛t❤❡♠❛t✐❝❛❧ ♣❡rs♣❡❝t✐✈❡ t❤❡ ♣r❡✈✐♦✉s ❝♦♥tr✐❜✉t✐♦♥s ❜② ❘✐❝❤❛r❞s ✭✷✵✵✽✮✱ ❈❛✐r♥s ❡t ❛❧✳ ✭✷✵✶✻✮ ❛♥❞ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮✳ ✶✺✴✷✷

(16)

1900 1950 2000

0.00

0.05

0.10

0.15

UT mortality rate at age 0

Year Monthly based Annual based 1900 1950 2000 0.90 1.00 1.10 1.20

UT mortality rate at age 0 − Ratio

Year 1900 1950 2000 0.00 0.10 0.20 0.30

LT mortality rate at age 0

Year Monthly based Annual based 1900 1950 2000 0.85 0.95 1.05 1.15

LT mortality rate at age 0 − Ratio

Year ❋✐❣✉r❡ ✺✿ ▲❡❢t✿ ❞❡❛t❤ r❛t❡s ❡st✐♠❛t❡❞ ❜❛s❡❞ ♦♥ t❤❡ ♥❡✇ ✐♥❢❡r❡♥❝❡ ♠❡t❤♦❞ ✭✐♥ ❜❧❛❝❦✮✱ ❛♥❞ ❝♦♠♣❛r❡❞ t♦ ❡st✐♠❛t❡s ✉s✐♥❣ t❤❡ st❛♥❞❛r❞ ♠❡t❤♦❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ r❡❝♦r❞s ✭✐♥ r❡❞✮✳ ❘✐❣❤t✿ r❛t✐♦ ❜❡t✇❡❡♥ ♥❡✇ ❛♥❞ ♦❧❞ ❡st✐♠❛t❡s✳ ❚♦♣✿ ❯♣♣❡r tr✐❛♥❣❧❡✳ ❇♦tt♦♠✿ ▲♦✇❡r tr✐❛♥❣❧❡✳ ✶✻✴✷✷

(17)

1900 1940 1980

0.000

0.010

0.020

0.030

UT mortality rate at age 30

Year Monthly based Annual based 1900 1940 1980 0.90 1.00 1.10 1.20

UT mortality rate at age 30 − Ratio

Year

1900 1940 1980

0.00

0.02

0.04

LT mortality rate at age 30

Year Monthly based Annual based 1900 1940 1980 0.85 0.95 1.05 1.15

LT mortality rate at age 30 − Ratio

Year ❋✐❣✉r❡ ✻✿ ▲❡❢t✿ ❞❡❛t❤ r❛t❡s ❡st✐♠❛t❡❞ ❜❛s❡❞ ♦♥ t❤❡ ♥❡✇ ✐♥❢❡r❡♥❝❡ ♠❡t❤♦❞ ✭✐♥ ❜❧❛❝❦✮✱ ❛♥❞ ❝♦♠♣❛r❡❞ t♦ ❡st✐♠❛t❡s ✉s✐♥❣ t❤❡ st❛♥❞❛r❞ ♠❡t❤♦❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ r❡❝♦r❞s ✭✐♥ r❡❞✮✳ ❘✐❣❤t✿ r❛t✐♦ ❜❡t✇❡❡♥ ♥❡✇ ❛♥❞ ♦❧❞ ❡st✐♠❛t❡s✳ ❚♦♣✿ ❯♣♣❡r tr✐❛♥❣❧❡✳ ❇♦tt♦♠✿ ▲♦✇❡r tr✐❛♥❣❧❡✳ ✶✼✴✷✷

(18)

1920 1940 1960 1980 2000

0.010

0.015

0.020

0.025

UT mortality rate at age 60

Year Monthly based Annual based 1920 1940 1960 1980 2000 0.90 1.00 1.10 1.20

UT mortality rate at age 60 − Ratio

Year 1920 1940 1960 1980 2000 0.010 0.015 0.020 0.025

LT mortality rate at age 60

Year Monthly based Annual based 1920 1940 1960 1980 2000 0.85 0.95 1.05 1.15

LT mortality rate at age 60 − Ratio

Year ❋✐❣✉r❡ ✼✿ ▲❡❢t✿ ❞❡❛t❤ r❛t❡s ❡st✐♠❛t❡❞ ❜❛s❡❞ ♦♥ t❤❡ ♥❡✇ ✐♥❢❡r❡♥❝❡ ♠❡t❤♦❞ ✭✐♥ ❜❧❛❝❦✮✱ ❛♥❞ ❝♦♠♣❛r❡❞ t♦ ❡st✐♠❛t❡s ✉s✐♥❣ t❤❡ st❛♥❞❛r❞ ♠❡t❤♦❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ r❡❝♦r❞s ✭✐♥ r❡❞✮✳ ❘✐❣❤t✿ r❛t✐♦ ❜❡t✇❡❡♥ ♥❡✇ ❛♥❞ ♦❧❞ ❡st✐♠❛t❡s✳ ❚♦♣✿ ❯♣♣❡r tr✐❛♥❣❧❡✳ ❇♦tt♦♠✿ ▲♦✇❡r tr✐❛♥❣❧❡✳ ✶✽✴✷✷

(19)

19400.04 1960 1980 2000

0.08

0.12

0.16

UT mortality rate at age 80

Year Monthly based Annual based 1940 1960 1980 2000 0.90 1.00 1.10 1.20

UT mortality rate at age 80 − Ratio

Year

1940 1960 1980 2000

0.04

0.08

0.12

LT mortality rate at age 80

Year Monthly based Annual based 1940 1960 1980 2000 0.85 0.95 1.05 1.15

LT mortality rate at age 80 − Ratio

Year ❋✐❣✉r❡ ✽✿ ▲❡❢t✿ ❞❡❛t❤ r❛t❡s ❡st✐♠❛t❡❞ ❜❛s❡❞ ♦♥ t❤❡ ♥❡✇ ✐♥❢❡r❡♥❝❡ ♠❡t❤♦❞ ✭✐♥ ❜❧❛❝❦✮✱ ❛♥❞ ❝♦♠♣❛r❡❞ t♦ ❡st✐♠❛t❡s ✉s✐♥❣ t❤❡ st❛♥❞❛r❞ ♠❡t❤♦❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ r❡❝♦r❞s ✭✐♥ r❡❞✮✳ ❘✐❣❤t✿ r❛t✐♦ ❜❡t✇❡❡♥ ♥❡✇ ❛♥❞ ♦❧❞ ❡st✐♠❛t❡s✳ ❚♦♣✿ ❯♣♣❡r tr✐❛♥❣❧❡✳ ❇♦tt♦♠✿ ▲♦✇❡r tr✐❛♥❣❧❡✳ ✶✾✴✷✷

(20)

Mortality improvements UT (France) Year Age 40 60 80 1970 1980 1990 2000 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3

Mortality improvements UT (France)

Year Age 40 60 80 1970 1980 1990 2000 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3

Mortality improvements LT (France)

Year Age 40 60 80 1970 1980 1990 2000 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3

Mortality improvements LT (France)

Year Age 40 60 80 1970 1980 1990 2000 −0.3 −0.2 −0.1 0.0 0.1 0.2 0.3 ❋✐❣✉r❡ ✾✿ ▲❡❢t✿ ♠♦rt❛❧✐t② ✐♠♣r♦✈❡♠❡♥t r❛t❡s ✉s✐♥❣ t❤❡ st❛♥❞❛r❞ ♠❡t❤♦❞ ❜❛s❡❞ ♦♥ ❛♥♥✉❛❧ ♣♦♣✉❧❛t✐♦♥ r❡❝♦r❞s✳ ❘✐❣❤t✿ ♠♦rt❛❧✐t② ✐♠♣r♦✈❡♠❡♥t r❛t❡s ✉s✐♥❣ t❤❡ ♥❡✇ ✐♥✲ ❢❡r❡♥❝❡ ♠❡t❤♦❞✳ ❚♦♣✿ ✉♣♣❡r tr✐❛♥❣❧❡s✳ ❇♦tt♦♠✿ ❧♦✇❡r tr✐❛♥❣❧❡s✳

✹ ❈♦♥❝❧✉❞✐♥❣ r❡♠❛r❦s

■♥ t❤✐s ♣❛♣❡r✱ ✇❡ ♣r♦♣♦s❡❞ ❛♥ ✐♥❢❡r❡♥❝❡ str❛t❡❣② ❢♦r ❣❡♥❡r❛❧ ♣♦♣✉❧❛t✐♦♥ ♠♦rt❛❧✐t② t❛❜❧❡s ❜❛s❡❞ ♦♥ t❤❡ ❞❡r✐✈❛t✐♦♥ ♦❢ ❢♦r♠✉❧❛s ✐♥ t❤❡ ▲❡①✐s ❞✐❛❣r❛♠✱ ✇❤✐❝❤ r❡❧❛t❡ t❤❡ ❞❡❛t❤ r❛t❡ ✇✐t❤ ❛♥♥✉❛❧ ♦❜s❡r✈❛❜❧❡s ❛♥❞ t❤❡ ✐♥tr❛✲②❡❛r ❞✐str✐❜✉t✐♦♥ ♦❢ ❜✐rt❤❞❛②s ♦✈❡r ❛❣❡s✳ ❚❤❡ ♠❡t❤♦❞ t❤❡r❡❢♦r❡ ✉s❡s ♠♦♥t❤❧② ❜✐rt❤ ❝♦✉♥ts t♦ r❡✜♥❡ ❝❧❛ss✐❝❛❧ ♠♦rt❛❧✐t② ❡st✐♠❛t❡s✳ ❚❤❡ ♥❡✇ ♠♦rt❛❧✐t② t❛❜❧❡s s❤♦✇ ❜❡tt❡r ❢❡❛t✉r❡s✱ ✐♥❝❧✉❞✐♥❣ t❤❡ ❢❛❝t t❤❛t ♣r❡✈✐♦✉s ❛♥♦♠❛❧✐❡s ✐♥ t❤❡ ❢♦r♠ ♦❢ ✐s♦❧❛t❡❞ ❝♦❤♦rt ❡✛❡❝ts ❞✐s❛♣♣❡❛r✱ ✇❤✐❝❤ ❝♦♥✜r♠s ❢r♦♠ ❛ ♠❛t❤❡♠❛t✐❝❛❧ ♣❡rs♣❡❝t✐✈❡ t❤❡ ♣r❡✈✐♦✉s ❝♦♥tr✐❜✉t✐♦♥s ❜② ❘✐❝❤❛r❞s ✭✷✵✵✽✮✱ ❈❛✐r♥s ❡t ❛❧✳ ✭✷✵✶✻✮ ❛♥❞ ❇♦✉♠❡③♦✉❡❞ ✭✷✵✶✻✮✳ ❙❡✈❡r❛❧ t♦♣✐❝s r❡♠❛✐♥ t♦ ❜❡ ❛❞❞r❡ss❡❞ t♦ str❡♥❣t❤❡♥ t❤❡ ♠❡t❤♦❞♦❧♦❣②✳ ❋✐rst✱ ✐t ✷✵✴✷✷

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