Factors Influencing Birth Rate and Forecasting in the Yangtze River Delta Based on Pearson Correlation Coefficients
DOI:
https://doi.org/10.63313/crispp.0901Keywords:
Birth Rate, Grey Relational Analysis, Pearson Correlation, Generalized Linear Regression Model, Time-Series Analysis, Grey Forecasting Model, Economic and Social FactorsAbstract
This study investigates declining birth rates in the Yangtze River Delta region and forecasts Shanghai’s birth rate from 2023 to 2032. Using data from 2001 to 2022, Grey Relational Analysis and Pearson correlation analysis identify key factors influencing birth rates and validate relevant hypotheses. A generalized linear regression model further examines complex relationships between multi-ple factors and birth rates.Results indicate that the number of secondary schools promotes birth rates, while graduate admissions suppress them, suggesting higher education might reduce fertility intentions. Long-term labor migration significantly impacts birth rate changes, while the relationship between urban built-up area and birth rates is complex.
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