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Abstract: This paper assesses the impact of climate change on China''s agricultural production at a cross-provincial level using the Ricardian approach, incorporating a multilevel model with farm-level group data. The farm-level group data includes 13,379 farm households, across 316 villages, distributed in 31 provinces. The empirical results show that, firstly, the marginal effects and elasticities of net crop revenue per hectare with respect to climate factors indicated that the annual impact of temperature on net crop revenue per hectare was positive, and the effect of increased precipitation was negative when looking at the national totals; secondly, the total impact of simulated climate change scenarios on net crop revenues per hectare at a Chinese national total level, was an increase of between 79 USD per hectare and 207 USD per hectare for the 2050s, and an increase from 140 USD per hectare to 355 USD per hectare for the 2080s. As a result, climate change may create a potential advantage for the development of Chinese agriculture, rather than a risk, especially for agriculture in the provinces of the Northeast, Northwest and North regions. However, the increased precipitation can lead to a loss of net crop revenue per hectare, especially for the provinces of the Southwest, Northwest, North and Northeast regions. [Copyright &y& Elsevier]

This paper presents an agent-based simulation (ABS) and cellular automata (CA) coupled model to simulate the spatial evolution of the population of China over the past 2000 years. In the model, agents are used to simulate individuals who live in a geographic environment represented by the CA. The choice to migrate is influenced by climate change, potential agricultural productivity change, and waves of mass migrations. Using the simulation, we can observe the spatial evolution of the population, as well as the shift of the population center of gravity, and we can analyze the driving forces of these changing spatial patterns. [ABSTRACT FROM AUTHOR]