2020
DOI: 10.1007/s13524-020-00898-0
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Twins Support the Absence of Parity-Dependent Fertility Control in Pretransition Populations

Abstract: A conclusion of the European Fertility Project in 1986 was that pretransition populations mostly displayed natural fertility, where parity-dependent birth control was absent. This conclusion has recently been challenged for England by new empirical results and has also been widely rejected by theorists of long-run economic growth, where pre-industrial fertility control is integral to most models. In this study, we use the accident of twin births to show that for three Western European-derived pre-industrial po… Show more

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Cited by 11 publications
(2 citation statements)
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“…A drop in parity progression after a twinning event is expected since such an event may increase the risk of maternal death and reduce reproductive health 3 , 5 , 40 . Furthermore, mothers may show a reduced inclination to continue reproducing after the birth of twins, as suggested for some modern populations 41 , but see 42 . Fitting a GLMM to our parity progression data (see “Methods”) confirmed that mothers were indeed less likely to keep reproducing following the delivery of twins versus a singleton (Fig.…”
Section: Resultsmentioning
confidence: 96%
“…A drop in parity progression after a twinning event is expected since such an event may increase the risk of maternal death and reduce reproductive health 3 , 5 , 40 . Furthermore, mothers may show a reduced inclination to continue reproducing after the birth of twins, as suggested for some modern populations 41 , but see 42 . Fitting a GLMM to our parity progression data (see “Methods”) confirmed that mothers were indeed less likely to keep reproducing following the delivery of twins versus a singleton (Fig.…”
Section: Resultsmentioning
confidence: 96%
“…Some selection criteria have very little impact on results, but others can bias results in important ways. Unfortunately, some recent publications do not follow important rules for analyzing family reconstitutions, and they include results that are biased and incorrect (see critiques found in Alter, 2019;Clark, Cummins, & Curtis, 2019).…”
Section: Data Quality Testsmentioning
confidence: 99%