Beyond Boom and Bust: Heterogeneous Fertility Effects of the COVID-19 Pandemic

超越繁荣与萧条：COVID-19 大流行对生育率的异质性影响

基本信息

批准号：
10575256
负责人：
Leslie Root
金额：
$ 7.82万
依托单位：
UNIVERSITY OF COLORADO
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-05-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10575256
关键词：
Accounting Address Adolescent Affect Age Attention Baby Booms Birth Birth History Birth Order Birth Rate Black race COVID-19 COVID-19 impact COVID-19 pandemic COVID-19 pandemic effects Censuses Characteristics Child Completed Family Sizes Complex Contraceptive methods Data Data Security Data Set Data Sources Ethnic Origin Family Planning Female Fertility Fertility Rates Fertility Study Funding Geography Goals Grain Health Health Insurance Heterogeneity Hispanic Household Income Individual Inequality Knowledge Link Location Low Income Population Medical Methods Modeling Morbidity - disease rate National Institute of Child Health and Human Development Nature Pattern Persons Policies Population Positioning Attribute Race Records Reproduction Research Design Research Personnel Schedule Services Shock Social Security Socioeconomic Status Source Subgroup Taxes Time Translating Variant Woman Work age group aged child bearing coronavirus disease improved mortality novel pandemic disease pandemic impact parity pre-pandemic prevent programs sociodemographics stem theories trend

项目摘要

PROJECT SUMMARY The COVID-19 pandemic arrived at a time when U.S. birth rates had been declining for several years. Contrary to initial predictions of a “COVID baby boom,” early evidence shows that the pandemic coincided with a steeper decline in birth rates. But fertility patterns vary dramatically across the U.S., and the mortality and health effects of COVID-19 have also varied by location, race/ethnicity, and socioeconomic status. Therefore, we expect significant variation in the pandemic’s effect on fertility. However, currently available data make this difficult to study - fertility rates by household income are not available in the U.S., even at the national level, nor are rate schedules by combinations of race/ethnicity and income or parity. This project seeks to leverage a new restricted data source, which our team has produced under the NICHD-funded "Increased access to contraception: an opportunity dividend?" project (R01-HD101480-01, 2020-2024), to assess the effect of the COVID-19 pandemic on fertility. In partnership with the U.S. Census Bureau, we will use a dataset we created, Reproduction in People’s Lives (RIPL), which provides the full count individual-level longitudinal data needed to study how changes in fertility during the COVID-19 pandemic have varied by age, state, race and ethnicity, household income, and birth order. Using this dataset, we will link multiple U.S. administrative data sources, including individual tax filings microdata, the 2010 decennial Census, and social security data, to (Aim 1) calculate age-specific fertility rates for all U.S. women by state and demographic subgroup for the years 2015 through 2021. These rates - calculated by race/ethnicity, household income, parity, and most combinations of these characteristics - represent a significant improvement in level of detail over current publicly available rates. Using the rates calculated for the pre-pandemic period (2015-2019) we will (Aim 2) use demographic forecasting to generate counterfactual rates that represent estimated 2020-2021 fertility levels by state and demographic subgroup in the absence of the COVID-19 pandemic. We use a forecasting method that is demonstrated to perform well over the short- to medium-term in fertility contexts like the contemporary U.S. and which is based on the Lee-Carter method, a cornerstone of demographic forecasting. We will (Aim 3) assess heterogeneity in the COVID-19 pandemic’s effect on fertility by comparing these counterfactuals to the observed rates constructed under Aim 1 during the years 2020-2021. The forecast counterfactuals allow us to estimate the portion of fertility change over the pandemic period that is the result of the pandemic, and to compare this portion across different age groups, sociodemographic subgroups, parities, and states. We anticipate that we will also be able to publicly release a subset of the rate schedules and forecasts we generate, allowing other researchers access to this important new data source.

项目概要相反，COVID-19 大流行发生时，美国出生率多年来一直在下降。与“新冠婴儿潮”的初步预测相比，早期证据表明，这场大流行恰逢更陡峭的时期出生率下降。但美国各地的生育模式差异很大，并且 COVID-19 的死亡率和健康影响已经也因地点、种族/民族和社会经济地位而异，因此，我们预计会有显着差异。然而，目前可用的数据使得研究生育率变得困难。在美国，即使在全国范围内，也无法获得家庭收入，也无法获得按组合划分的费率表该项目旨在利用我们的新的受限数据源。团队在 NICHD 资助下制作了《增加避孕的机会：机会红利？》项目（R01-HD101480-01，2020-2024），评估 COVID-19 大流行对生育力的影响。我们将与美国人口普查局合作，使用我们创建的数据集“人们生活中的繁殖” （RIPL），它提供了研究生育率变化所需的完整计数个人水平纵向数据在 COVID-19 大流行期间，人们因年龄、州、种族和族裔、家庭收入和出生顺序而异。使用此数据集，我们将链接多个美国行政数据源，包括个人纳税申报微观数据， 2010 年十年一次的人口普查和社会保障数据，以（目标 1）计算所有美国人口的特定年龄生育率 2015 年至 2021 年按州和人口亚组划分的女性。这些比率 - 计算如下种族/族裔、家庭收入、平等以及这些特征的大多数组合 - 代表了重要的因素与当前公开的费率相比，详细程度有所提高。使用大流行前计算期间（2015-2019）的比率，我们将（目标 2）使用人口预测生成代表各州和人口统计的 2020-2021 年估计生育水平的反事实比率我们使用的预测方法已被证明可以在没有 COVID-19 大流行的情况下进行分组。在像当代美国这样的生育环境中，短期到中期表现良好，这是基于李卡特方法，人口预测的基石。我们将（目标 3）通过比较这些因素来评估 COVID-19 大流行对生育力影响的异质性 2020-2021 年期间根据目标 1 构建的观察到的比率的反事实。反事实使我们能够估计大流行期间生育率变化的部分是由于流行病，并比较不同年龄组、社会人口亚组、胎次的这一部分，我们预计我们还将能够公开发布部分费率表和预测。我们生成，允许其他研究人员访问这个重要的新数据源。