Given the extreme dependence of agriculture on weather conditions, this paper analyses the effect of climatic variations on this economic sector, by considering both a huge data set and a flexible spatiotemporal model specification. In particular, we study the response of N-fertilizer application to abnormal weather conditions, while accounting for other relevant control variables. The data set consists of gridded data spanning over 21 years (1993–2013), while the methodological strategy makes use of a spatial dynamic panel data (SDPD) model that accounts for both space and time fixed effects, besides dealing with both space and time dependences. Time-invariant short- and long-term effects, as well as time-varying marginal effects are also properly defined, revealing interesting results on the impact of both GDP and weather conditions on fertilizer utilizations. The analysis considers four macroregions—Europe, South America, Southeast Asia and Africa—to allow for comparisons among different socio-economic societies. In addition to finding both spatial (in the form of knowledge spillover effects) and temporal dependences as well as a good support for the existence of an environmental Kuznets curve for fertilizer application, the paper shows peculiar responses of N-fertilization to deviations from normal weather conditions of moisture for each selected region, calling for ad hoc policy interventions.

中文翻译：

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天气条件对施肥的影响：空间动态面板数据分析

鉴于农业对天气条件的极端依赖，本文通过考虑庞大的数据集和灵活的时空模型规范，分析了气候变化对该经济部门的影响。特别是，我们研究了氮肥施用对异常天气条件的响应，同时考虑了其他相关控制变量。数据集由跨越 21 年（1993-2013 年）的网格数据组成，而方法策略使用空间动态面板数据 (SDPD) 模型，该模型除了处理空间和时间外，还考虑了空间和时间固定效应依赖。随时间变化的短期和长期效应以及随时间变化的边际效应也得到了适当的定义，揭示了关于 GDP 和天气条件对肥料利用的影响的有趣结果。该分析考虑了四个宏观区域——欧洲、南美洲、东南亚和非洲——以便在不同的社会经济社会之间进行比较。除了找到空间（以知识溢出效应）和时间依赖性以及对施肥环境库兹涅茨曲线存在的良好支持，该论文显示了 N 施肥对每个选定区域的水分正常天气条件偏差的特殊响应，呼吁广告临时性政策干预。