Abstract

There is often a vicious cycle that occurs in China encompassing ecological vulnerability, low productivity, and poverty. Existing research has not applied multiagent modelling and simulation (MAMS), which is a method suitable for analysing such complex systems. Therefore, the MAMS is here used to explore potential strategies for breaking this cycle. The MAMS method is based on complex adaptive systems and computer programs, and it includes both theoretical and simulation models, which can be used to simulate different scenarios and obtain visualized results. To sample representative poverty-stricken areas in China, the authors designed five breakthrough policy scenarios. The simulation results of these scenarios indicate that increasing the amount of arable land decreases the number of poor people. However, increasing the direct interventions of government does not reduce the number of the poor, nor does it change the Gini coefficient. On the other hand, increasing the number and variety of poverty alleviation opportunities available to the poor leads to a decrease in both the number of poor people and the Gini coefficient. These results of our five scenarios indicate that the optimal policy portfolio could be obtained by increasing the amount of arable land and providing more varied opportunities to help the poor participate in market activities while reducing direct government intervention. The combined design of these policies is conducive to breaking the vicious cycle of poverty.

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