The influencing factors underlying the vicious ecological vulnerability-low productivity-poverty cycle in China and overcoming its related policies.

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 e...

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Publicado en:Humanities & Social Sciences Communications Vol. 10; no. 1; pp. 1 - 11
Autores principales: Liu, Yong, Long, Cuihong
Formato: Artículo
Publicado: Springer Nature 9/19/2023
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        10.1057/s41599-023-02068-0
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        atl: The influencing factors underlying the vicious ecological vulnerability-low productivity-poverty cycle in China and overcoming its related policies.
      aug:
        au:
          Liu, Yong
          Long, Cuihong
        affil:
          https://ror.org/011ashp19 School of Economics, Sichuan University, Chengdu, China
          https://ror.org/02n96ep67 School of Economics, East China Normal University, Shanghai, China
      su:
        Poor people
        Gini coefficient
        Intervention (Federal government)
        Arable land
        Poverty reduction
        Computer software
        Poverty
        China
      sug:
        subj:
          China
          Poor people
          Gini coefficient
          Intervention (Federal government)
          Arable land
          Poverty reduction
          Computer software
          Poverty
      ab: 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.
      pubtype: Academic Journal
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    language: English
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