Analysing the resilience of the European commodity production system with PyResPro, the Python Production Resilience package

Matteo Zampieri, Andrea Toreti, Andrej Ceglar, Pierluca De Palma and Thomas Chatzopoulos

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Abstract: This paper presents a Python object-oriented software and code to compute the annual production resilience indicator. The annual production resilience indicator can be applied to different anthropic and natural systems such as agricultural production, natural vegetation and water resources. Here, we show an example of resilience analysis of the economic values of the agricultural production in Europe. The analysis is conducted for individual time-series in order to estimate the resilience of a single commodity and to groups of time-series in order to estimate the overall resilience of diversified production systems composed of different crops and/or different countries. The proposed software is powerful and easy to use with publicly available datasets such as the one used in this study.

Date: 2020-06, Revised 2020-06
New Economics Papers: this item is included in nep-agr
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