Optimizing agricultural land-use portfolios with scarce data—A non-stochastic model

Optimizing agricultural land-use portfolios with scarce data—A non-stochastic model
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DOI:
10.1016/j.ecolecon.2015.10.021
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发表时间:
2015-12
影响因子:
7
通讯作者:
T. Knoke;C. Paul;F. Härtl;L. M. Castro;Baltazar Calvas;P. Hildebrandt
T. Knoke;C. Paul;F. Härtl;L. M. Castro;Baltazar Calvas;P. Hildebrandt
中科院分区:
经济学2区
文献类型:
--
作者:
T. Knoke;C. Paul;F. Härtl;L. M. Castro;Baltazar Calvas;P. Hildebrandt

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投资组合选择理论经常被用来帮助改善有关环境的经济决策。应用这一理论需要关于所有经济期权组合之间的不确定收益的协方差的信息,并且还假设收益是正态分布的。由于通常很难满足所有的数据要求和假设,本文提出了一种变体的鲁棒投资组合优化作为替代,需要较少的先验信息。该方法考虑了未来的不确定性,在一个非随机的方式,通过可能的偏离名义回报的土地使用的替代品。最大限度地提高土地使用组合的经济回报取决于满足一系列包容性的限制。这些要求,一个预定义的回报阈值是实现了强大的解决方案,为每个不确定性的情况下考虑。基于数据的8种常见的农业作物在厄瓜多尔低地,与经典的随机均值-方差优化产生的投资组合的比较显示更大的土地利用多样化(通过增加香农指数),但只有温和的预期经济损失的非随机强大的土地利用组合。我们的结论是,非随机推导的土地利用组合是一个很好的替代经典的随机模型,在经济投入参数的信息是稀缺的情况下。
The theory of portfolio selection has often been applied to help improve economic decisions about the environment. Applying this theory requires information on the covariance of uncertain returns between all combinations of the economic options and also assumes that returns are normally distributed. As it is usually difficult to fulfill all data requirements and assumptions, this paper proposes a variant of robust portfolio optimization as an alternative that needs less pre-information. The approach considers future uncertainties in a non-stochastic fashion through possible deviations from the nominal return of land-use alternatives. Maximizing the economic return of the land-use portfolio is conditional on meeting an inclusive set of constraints. These demand that a pre-defined return threshold is achieved by the robust solution for each uncertainty scenario considered. Based on data for eight agricultural crops common in the Ecuadorian lowlands, a comparison with portfolios generated by classical stochastic mean-variance optimization shows greater land-use diversification (through increased Shannon indices), but only moderate expected economic loss of non-stochastic robust land-use portfolios. We conclude that non-stochastic derivation of land-use portfolios is a good alternative to the classical stochastic model, in situations where information on economic input parameters is scarce.