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COVID-19 and the Future of US Fertility: What Can We Learn from Google?

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  • Wilde, Joshua
  • Chen, Wei
  • Lohmann, Sophie

Abstract

We use data from Google Trends to predict the effect of the COVID-19 pandemic on future births in the United States. First, we show that periods of above-normal search volume for Google keywords relating to conception and pregnancy in US states are associated with higher numbers of births in the following months. Excess searches for unemployment keywords have the opposite effect. Second, by employing simple statistical learning techniques, we demonstrate that including information on keyword search volumes in prediction models significantly improves forecast accuracy over a number of cross-validation criteria. Third, we use data on Google searches during the COVID-19 pandemic to predict changes in aggregate fertility rates in the United States at the state level through February 2021. Our analysis suggests that between November 2020 and February 2021, monthly US births will drop sharply by approximately 15%. For context, this would be a 50% larger decline than that following the Great Recession of 2008-2009, and similar in magnitude to the declines following the Spanish Flu pandemic of 1918-1919 and the Great Depression. Finally, we find heterogeneous effects of the COVID-19 pandemic across different types of mothers. Women with less than a college education, as well as Black or African American women, are predicted to have larger declines in fertility due to COVID-19. This finding is consistent with elevated caseloads of COVID-19 in low-income and minority neighborhoods, as well as with evidence suggesting larger economic impacts of the crisis among such households.

Suggested Citation

  • Wilde, Joshua & Chen, Wei & Lohmann, Sophie, 2020. "COVID-19 and the Future of US Fertility: What Can We Learn from Google?," SocArXiv 2bgqs, Center for Open Science.
  • Handle: RePEc:osf:socarx:2bgqs
    DOI: 10.31219/osf.io/2bgqs
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    References listed on IDEAS

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    1. Quamrul H. Ashraf & David N. Weil & Joshua Wilde, 2013. "The Effect of Fertility Reduction on Economic Growth," Population and Development Review, The Population Council, Inc., vol. 39(1), pages 97-130, March.
    2. Wilde, Joshua & Apouey, Bénédicte H. & Jung, Toni, 2017. "The effect of ambient temperature shocks during conception and early pregnancy on later life outcomes," European Economic Review, Elsevier, vol. 97(C), pages 87-107.
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    5. Finlay, Jocelyn E., 2009. "Fertility response to natural disasters : the case of three high mortality earthquakes," Policy Research Working Paper Series 4883, The World Bank.
    6. Siliverstovs, Boriss & Wochner, Daniel S., 2018. "Google Trends and reality: Do the proportions match?," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 1-23.
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    8. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    9. John B. Casterline & John Bongaarts & Mahesh Karra & David Canning & Joshua Wilde, 2017. "The Effect of Fertility Decline on Economic Growth in Africa: A Macrosimulation Model," Population and Development Review, The Population Council, Inc., vol. 43, pages 237-263, May.
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    More about this item

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
    • I10 - Health, Education, and Welfare - - Health - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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