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新农保何以影响老年农民农业生产率

孙琳琳 周睿 刘聪

山西农业大学学报(社会科学版)2026,Vol.25Issue(3):66-74,9.
山西农业大学学报(社会科学版)2026,Vol.25Issue(3):66-74,9.DOI:10.13842/j.cnki.issn1671-816X.2026.03.006

新农保何以影响老年农民农业生产率

How does the new"rural pension scheme"affect the agricultural productivity of elderly farmers

孙琳琳 1周睿 1刘聪1

作者信息

  • 1. 北京航空航天大学 公共管理学院,北京 100191
  • 折叠

摘要

Abstract

As the aging of the workforce continues to deepen,elderly farming has become a fundenmental form and important characteristic of China's agricultural development.In classical utility-maximization models,pension funds ease the budget con-straints faced by farmers in their agricultural production,thereby influencing their decitions regarding the allocation of production factors.This,in turn,has indirect effects on the agricultural productivity of elderly farmers.Based on data from the China Fami-ly Panel Studies(CHPS)from 2010 to 2020,a fuzzy breakpoint regression method was used to identify the policy effectiveness of the New Rural Pension Scheme(NRPS)on the agricultural productivity of elderly farm workers.The results show that the im-plementation of the NRPS has significantly improved both the labor productivity and total factor productivity of elderly farmers.Further analysis reveals that NRPS influences agricultural production through two pathways:increasing investment in machinery and boosting healthcare expenditures.Additionally,heterogeneity is observed across household economic levels and regional agri-cultural resource endowments.Therefore,it is essential not only to raise the overall pension benefits of the NRPS to keep pace with price changes but also to increase attention to those who are not yet enrolled,striving to extend coverage to more people.

关键词

新农保/农业生产率/老年农民/模糊断点回归

Key words

New rural pension scheme/Agricultural productivity/Elderly farmers/Fuzzy regression discontinuity

分类

管理科学

引用本文复制引用

孙琳琳,周睿,刘聪..新农保何以影响老年农民农业生产率[J].山西农业大学学报(社会科学版),2026,25(3):66-74,9.

基金项目

北京市社科基金项目"北京农地制度改革和农民增收研究"(22JJB013) (22JJB013)

山西农业大学学报(社会科学版)

OACHSSCD

1671-816X

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