Impacts of Aging Agricultural Labor Force on Land Transfer: An Empirical Analysis Based on the China Family Panel Studies

Abstract

Aging is an important trend in the global demographic, with rural population aging becoming a significant challenge due to its faster pace and profound implications. Although the most significant impact of the aging agricultural labor force occurs in agricultural production and land use, little is known about their relationship. Based on the 2010–2018 data from the Chinese Family Panel Studies, this study uses the panel probit model to analyze the impact of the aging agricultural labor force on land transfer and tests its influence mechanism from the aspects of health effect and pension insurance effect. The results show the following: (1) there is an inverted U-shaped relationship between the aging of the agricultural labor force and land rent-in—with the deepening of the aging of the agricultural labor force, the aging of the agricultural labor force shifts from promoting land rent-in to inhibiting it; (2) there is a U-shaped relationship between the aging of the agricultural labor force and land rent-out—with the deepening of the aging of the agricultural labor force, the aging of the agricultural labor force shifts from inhibiting land rent-out to promoting it; and (3) the impact of the aging agricultural labor force on land rent-in and rent-out is significantly affected by farmers’ health levels, however pension insurance does not play a significant moderating role. Therefore, the government should strengthen the land transfer market and improve the level of pension insurance for the elderly rural agricultural labor force.

The Impact of Rural Population Aging on Agricultural Cropping Structure: Evidence from China’s Provinces

“…China, as a country with a small farming economy with many people and little land, experiences land fragmentation, which increases the cost of agricultural cultivation. With the aging of the rural population, people will shift to planting grain crops that are easy to replace by machinery and produced on a large scale, and the planting area of cash crops that are more labor-demanding will be reduced, i.e., the aging of the rural population will lead to the tendency of "grain-convergence", which is consistent with the findings of related studies [46,[67][68][69]. Secondly, in terms of the heterogeneity of varieties and regions affected by rural population aging, as different grain crops are easy to replace labor with machinery, under tightening labor factor constraints, rural population aging has no significant impact on the structure of different varieties of grain crops.…”

“…Data from the seventh national census show that the proportion of the Chinese population aged 60 and above has increased from 5.44% in 2010 to 18.70% in 2020. In addition, as a large number of young and strong rural laborers flock to cities and non-agricultural sectors, the age structure of the agricultural labor force is aging [17], the level of human capital is low, and there is an increasing lack of effective labor force [18], resulting in the problem of population aging in China's rural areas and agricultural sectors becoming even more pronounced [19][20][21][22][23]. The 2015 National 1% Population Sampling Survey found that from 1982 to 2015, China's rural population over 60 years old increased by 2.37 times [24].…”

Environmental regulation, land use efficiency and industrial structure upgrading: Test analysis based on spatial durbin model and threshold effect

“…In the evaluation of land input [ 88 ], indicators such as built-up area of municipal districts, fixed asset investment, and electricity supply are used[ 89 ]. Land use input levels are measured based on land structure[ 90 ], labor[ 91 ], and resource aspects[ 92 ], while also examining the level of resource-intensive utilization in cities. In the evaluation of social benefits, indicators such as population density, per capita road area in municipal districts, and infrastructure convenience are used, focusing mainly on residential, transportation, and public space aspects to assess the comfort levels for people in the cities.…”

Profit analysis of native chicken farming business in Kakas District, Regency of Minahasa, Indonesia

“…The population according to age was divided into two, which were the non-productive age population, consisting of the population aged 0-14 years, and the productive age population, including the population aged 15-65 years. This classification could be used to calculate the dependency ratio [8].…”