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Understanding the Effects of China’s Agro-Environmental Policies on Rural Households’ Labor and Land Allocation with a Spatially Explicit Agent-Based Model

Citation

Wang, Ying; Zhang, Qi; Sannigrahi, Srikanta; Li, Qirui; Tao, Shiqi; Bilsborrow, Richard E.; Li, Jiangfeng; & Song, Conghe (2021). Understanding the Effects of China’s Agro-Environmental Policies on Rural Households’ Labor and Land Allocation with a Spatially Explicit Agent-Based Model. Journal of Artificial Societies and Social Simulation, 24(3), 7.

Abstract

Understanding household labor and land allocation decisions under agro-environmental policies is challenging due to complex human-environment interactions. Here, we developed a spatially explicit agent-based model based on spatial and socioeconomic data to simulate households’ land and labor allocation decisions and investigated the impacts of two forest restoration and conservation programs and one agricultural subsidy program in rural China. Simulation outputs revealed that the forest restoration program accelerates labor out-migration and cropland shrink, while the forest conservation program promotes livelihood diversification via increasing non-farm employment. Meanwhile, the agricultural subsidy program keeps labor for cultivation on land parcels with good quality, but appears less effective for preventing marginal croplands from being abandoned. The policy effects on labor allocation substantially differ between rules based on bounded rational and empirical knowledge of defining household decisions, particularly on sending labor out-migrants and engaging in local off-farm jobs. Land use patterns showed that the extent to which households pursue economic benefits through shrinking cultivated land is generally greater under bounded rationality than empirical knowledge. Findings demonstrate nonlinear social-ecological impacts of the agro-environmental policies through time, which can deviate from expectations due to complex interplays between households and land. This study also suggests that the spatial agent-based model can represent adaptive decision-making and interactions of human agents and their interactions in dynamic social and physical environments.

URL

http://dx.doi.org/10.18564/jasss.4589

Reference Type

Journal Article

Year Published

2021

Journal Title

Journal of Artificial Societies and Social Simulation

Author(s)

Wang, Ying
Zhang, Qi
Sannigrahi, Srikanta
Li, Qirui
Tao, Shiqi
Bilsborrow, Richard E.
Li, Jiangfeng
Song, Conghe

Article Type

Regular

Continent/Country

China

Race/Ethnicity

Asian/Pacific Islander

ORCiD

Bilsborrow - 0000-0002-0053-7356
Song, C - 0000-0002-4099-4906