图尔基耶的农业生产关联性和网络

Türker Açikgöz
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引用次数: 0

摘要

世界人口一直在快速增长,自 2006-2008 年全球粮食危机以来,人们多次质疑如何妥善喂养不断增长的世界人口。根据著名国际机构的预测,在不久的将来,世界可能无法提供足够的粮食,而这一事实可能会导致许多经济、社会和政府问题。在土耳其,由于某些原因,这些问题将比其他国家更为严重。土耳其是世界上人口增长率最高的国家之一,同时也是世界上收容难民人数最多的国家。此外,土尔其的农业部门最近经历了严重的衰退,该国一直依赖进口粮食和农产品。因此,在本文中,我采用 Diebold 和 Yilmaz(2012,2014)的关联性方法,即基于广义向量自回归模型的预测误差方差分解方法,研究土尔其农业生产的关联性和网络。我使用了土耳其产量最高的农产品数据,包括大麦、小麦、黑麦、水稻、扁豆、鹰嘴豆和燕麦。材料包括从 1938 年到 2019 年的年度生产数据。分析结果表明,土尔其农业生产具有高度关联性。我们的研究结果表明,小麦和大麦产生的生产冲击已蔓延到其他商品。农业生产网络和成对溢出效应也显示出类似的结果,即大多数商品与小麦和大麦生产高度关联。此外,成对连通性结果表明,存在一些强连通性关系和弱连通性关系,这些关系可用于决策过程、风险规避和风险寻求目的。我们的研究结果对生产商、供应商和贸易商的制度、多样化和风险管理政策制定具有重要意义。
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Agricultural Production Connectedness and Networks in Türkiye
The world’s population has been growing rapidly and since the 2006–2008 global food crisis, it has been questioned many times that how the world’s growing population will be fed properly. According to reputable international institutions, the world may be insufficient to supply enough food in the near future, and this fact may cause many economic, social, and government problems. In Türkiye, these problems will be realized more harshly than in peer countries for some reasons. Türkiye has one of the highest population growth rates in the world, while it hosts the highest number of refugees in the world. In addition, Türkiye’s agriculture sector has been experiencing a harsh downfall recently and the country has been dependent on importing food and agricultural commodities. Therefore, in this paper, I investigate the connectedness and networks of agricultural production in Türkiye by using the connectedness approach of Diebold and Yilmaz (2012, 2014), which is based on the forecast error variance decomposition methodology of generalized vector autoregressive models. I use Türkiye’s most produced agricultural commodity data, which are barley, wheat, rye, paddy, lentil, chickpea, and oat. The material consists of annual production data from 1938 to 2019. According to the analysis results, Türkiye’s agricultural production has been highly connected. Our findings show that production shocks arising from wheat and barley have spilled over to other commodities. Agricultural production networks and pairwise spillovers also exhibit a similar result that most of the commodities are highly interconnected to wheat and barley production. Besides, pairwise connectedness results show that there are some strong and weak connectivity relations, and these can be used for the decision-making process, risk aversion, and risk-seeking purposes. Our findings have important implications for policymaking for institutions, diversification, and risk management for producers, suppliers, and traders.
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