Climate and environmental changes are argued to increase the occurrence of conflict. In particular, two types of conflict seem to be driven by underlying environmental processes: food and fuel riots. Although research focussed on understanding the dynamics that cause food riots exists, the evidence is mixed and a solid quantitative analysis on the factors that cause these type of events is missing. Research on fuel riots is currently non-existent. The aim of this research was hence to identify, quantify and simulate the interconnections between scarcity of natural resources, international prices, political fragility and the occurrence of food and fuel riots. The approach implemented was mainly quantitative, with use of statistics, econometrics and Agent-Based Modelling (ABM). These methods allowed a parameterisation of these relationships and inclusion of the results in three different version of an ABM: Food, Fuel and Food and Fuel ABMs. The findings show that national availability of resources does not significantly impact the occurrence of food and fuel riots, while international prices and national political fragility do. Thresholds above which riots are more likely to happen were identified for both the price of food and fuel. For food, volatility was found to have a bigger impact than absolute prices, while for fuel the evidence was mixed and more research is required. In addition, food and fuel riots increase the likelihood of one another. Although the introduction of these parameters in the ABMs did not add to the predictive power of the underlying statistical models, the ABMs form the basis for further developments, in particular as regards the evolution of shocks to the production of resources and consequences in terms of food and fuel riots. This is evidenced by the scenarios developed and implemented in this thesis.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:715194 |
| Date | January 2016 |
| Creators | Natalini, Davide |
| Publisher | Anglia Ruskin University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://arro.anglia.ac.uk/701893/ |
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