Crowd-sourced Chinese genealogies as data for demographic and economic history

Xue, Melanie ORCID: 0000-0002-2112-4884 (2025) Crowd-sourced Chinese genealogies as data for demographic and economic history. Explorations in Economic History. ISSN 0014-4983 (In Press)

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Abstract

This paper evaluates the usefulness of crowd-sourced Chinese genealogical data for quantitative research in demography and economic history. I first examine whether genealogies—despite well-known selection biases—produce demographic patterns consistent with established historical knowledge of China. Comparisons with existing studies show that aggregate population-growth trends and sex ratios over time align reasonably well with established demographic and historical findings, suggesting that genealogies, though selective, capture coherent and interpretable patterns. Building on these plausibility checks, the paper argues that the main value of genealogical data lies in their scalability and temporal depth, particularly as crowd-sourced digitization vastly expands the number of available records. These features make genealogies well suited to analyses that leverage variation across regions and over time, an approach that is central in modern economic history.

Item Type:	Article
Additional Information:	© 2025 The Author
Divisions:	Economic History
Subjects:	H Social Sciences > HC Economic History and Conditions
JEL classification:	J - Labor and Demographic Economics > J1 - Demographic Economics > J11 - Demographic Trends and Forecasts J - Labor and Demographic Economics > J1 - Demographic Economics > J13 - Fertility; Family Planning; Child Care; Children; Youth N - Economic History > N1 - Macroeconomics and Monetary Economics; Growth and Fluctuations > N10 - General, International, or Comparative N - Economic History > N3 - Labor and Consumers, Demography, Education, Health, Income, and Wealth > N35 - Economic History: Labor and Consumers, Demography, Education, Health, Income and Wealth: Asia including Middle East
Date Deposited:	21 Nov 2025 10:27
Last Modified:	01 Dec 2025 09:51
URI:	http://eprints.lse.ac.uk/id/eprint/130282

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