Epilogue: Needed Research in Demography

Poston, Dudley L.; Baumle, Amanda K.; Micklin, Michael

doi:10.1007/0-387-23106-4_30

Cited by 8 publications

(7 citation statements)

References 36 publications

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“…Generally, it can be observed that the age-specific fertility rates of men quickly decline to very low levels above age 45, at least in high-income countries (see also Nisén 2014, Nordfalk et al 2015. Thus, while a share of male fertility occurs at higher ages, it appears that male fertility is mostly concentrated over an age range of roughly 25 years (age 20 to age 45) despite claims to the contrary sometimes made in the literature (see Poston et al 2006 for a discussion). This observation can be explained by decreasing male fecundity and the declining fecundity of the female partner (who is, on average, two to four years younger than her male partner), as well as age norms regarding childbearing (Billari et al 2011).…”

Section: Differences In the Timing Of Male And Female Fertilitymentioning

confidence: 96%

“…Several potential explanations for the limited research on male fertility have been offered, including a lack of data and data quality issues (Poston et al 2006). For instance, survey data on the fertility of males is generally considered to be less reliable, as males are prone to underreport their number of children (e.g., Rendall et al 1999, Vere 2008.…”

Section: Toward a Comparative Assessment Of Male Fertility With Birthmentioning

confidence: 99%

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New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers

Dudel

Klüsener

2019

Preprint

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Obtaining cross-country comparative perspectives on male fertility has long been difficult, as male fertility is usually less well registered than female fertility. This paper presents analyses based on a new male fertility database providing data on more than 330 million live births. This new resource, made available in the Human Fertility Collection, allows for the first time a comparative perspective on male fertility in high-income countries using high-quality birth register data. Contrasting male and female fertility trends across 17 countries, we show that trends in disparities between male and female period fertility rates are driven to a large degree by the interplay of parental age and cohort size differences. For parental age differences at childbirth, we observe a tendency toward smaller disparities, except in Eastern Europe. This observation fits with expectations based on gender theories. However, variation across countries also seems to be driven by factors other than gender equality.

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Section: Differences In the Timing Of Male And Female Fertilitymentioning

confidence: 96%

Section: Toward a Comparative Assessment Of Male Fertility With Birthmentioning

confidence: 99%

New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers

Dudel

Klüsener

2019

Preprint

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“…Much of the fertility literature has focused on women's reproduction, while research on men's reproduction has remained rare (Coleman 2000;Poston et al 2006). However, interest in men's fertility has been growing due to an increasing involvement of men in fertility decision-making and parenting (Lappegård et al 2011), and in response to concerns that have been raised about possible links between paternal age and the health outcomes of children (Paavilainen et al 2016;Khandwala et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Estimating men’s fertility from vital registration data with missing values

Dudel

Klüsener

2018

Population Studies

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Comparative perspectives on men's fertility are still rare, in part because vital registration data are often missing paternal age information for a substantial number of births. We compare two imputation approaches that attempt to estimate men's age-speciﬁc fertility rates and related measures for data in which paternal age information is missing for a non-negligible number of cases. Taking births with paternal age information as a reference, the ﬁrst approach uses the unconditional paternal age distribution, while the second approach considers the paternal age distribution conditional on the maternal age. To assess the performance of these two methods, we conduct simulations that mimic vital registration data for Sweden, the United States, Spain, and Estonia. In these simulations, we vary the overall proportion and the age selectivity of missing values. We find that the conditional approach outperforms the unconditional approach in the majority of simulations and therefore should be generally preferred.

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“…Much of the fertility literature has focused on female reproduction, while research on male reproduction has remained rare (Coleman 2000;Poston et al 2006). However, interest in male fertility has been growing in response to the increasing involvement of men in fertility decision-making and parenting (Lappegård et al 2011), and to concerns that have been raised about possible links between paternal ages and the health outcomes of children (Khandwala et al 2017, Paavilainen et al 2016.…”

Section: Introductionmentioning

confidence: 99%

Estimating male fertility from vital registration data with missing values

Dudel¹,

Klüsener²

2017

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Comparative perspectives on male fertility are still rare, in part because vital registration data often do not include paternal age information for a substantial number of births. We compare two imputation approaches that attempt to estimate male age-specific fertility rates and related measures for data in which the paternal age information is missing for a non-negligible number of cases. Taking births with paternal age information as a reference, the first approach uses the unconditional paternal age distribution, while the second approach considers the paternal age distribution conditional on the maternal age. To assess the performance of these two methods, we conduct simulations that mimic vital registration data for Sweden, the U.S., Spain, and Estonia. In these simulations, we vary the overall proportion and the age selectivity of missing values. We find that the conditional approach outperforms the unconditional approach in the majority of simulations, and should therefore generally be preferred.

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Epilogue: Needed Research in Demography

Cited by 8 publications

References 36 publications

New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers

New opportunities for comparative male fertility research: Insights from a new data resource based on high-quality birth registers

Estimating men’s fertility from vital registration data with missing values

Estimating male fertility from vital registration data with missing values

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