COVID-19 and the Future of US Fertility: What Can We Learn from Google?
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- Joshua Wilde & Wei Chen & Sophie Lohmann, 2020. "COVID-19 and the future of US fertility: what can we learn from Google?," MPIDR Working Papers WP-2020-034, Max Planck Institute for Demographic Research, Rostock, Germany.
- 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.
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Cited by:- Jurić Tado, 2022. "Forecasting Migration and Integration Trends Using Digital Demography – A Case Study of Emigration Flows from Croatia to Austria and Germany," Comparative Southeast European Studies, De Gruyter, vol. 70(1), pages 125-152, March.
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Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(4), pages 1-20, August.
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More about this item
Keywords
prediction; fertility; google; COVID-19; statistical learning;
All these keywords.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
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-11-02 (Big Data)
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