Evidence map›Paper›PMID 34580226›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

China's low fertility may not hinder future prosperity.

Guillaume Marois, Stuart Gietel-Basten, Wolfgang Lutz

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Article
  2. China's demographic dividend has moved from age-based labor supply to skill-based productivity.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  13. Contemporary demographic challenges and population policies.Bulletin of the World Health Organization · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Guillaume MaroisAsian Demographic Research Institute, Shanghai University, Shanghai, China.ORCID 0000-0002-2701-6286
Stuart Gietel-BastenDivision of Social Science, The Hong Kong University of Science and Technology, Hong Kong SAR, China sgb@ust.hk.ORCID 0000-0002-5818-8283
Wolfgang LutzWittgenstein Centre for Demography and Global Human Capital, University of Vienna-VID/ÖAW-International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria.ORCID 0000-0001-7975-8145

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's low fertility is often presented as a major factor which will hinder its prosperity in the medium to long term. This is based on the assumed negative consequences of an increasing old-age dependency ratio: a simplistic measure of relative changing age structures. Based on this view, policies to increase fertility are being proposed after decades of birth restriction policies. Here, we argue that a purely age structure-based reasoning which disregards labor force participation and education attainment may be highly misleading. While fertility has indeed fallen to low levels, human capital accumulation has been very strong-especially among younger cohorts. Factoring in the effects of labor force participation and educational attainment on productivity, a measure called "productivity-weighted labor force dependency ratio" can more accurately capture the economic implications of demographic change. When using this ratio, a much more optimistic picture of the economic (and social) future of China can be envisaged.

Indexed as

AdolescentAdultAgedAged, 80 and overBirth RateChildChild, PreschoolChinaDemographyEducational StatusFemaleFertilityForecastingHumansInfantInfant, NewbornagingChinadependency ratiofertilityhuman capital

Identifiers

PMID34580226
PMCPMC8501780

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.