Pei Qing, Zhang David D, Lee Harry F, Li Guodong
Department of Geography, The University of Hong Kong, Hong Kong ; International Centre for China Development Study, The University of Hong Kong, Hong Kong.
Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong.
PLoS One. 2014 Feb 7;9(2):e88155. doi: 10.1371/journal.pone.0088155. eCollection 2014.
Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.
气候变化已被证明是前工业化时期欧洲大规模社会危机的根本原因。然而,对前工业化时代气候变化和宏观经济周期的详细分析仍然缺乏,尤其是在不同的时间尺度内。因此,利用细粒度的古气候和经济数据以及统计方法,对公元1500年至1800年欧洲气候变化与农业经济之间的关系进行了定量评估。在该研究中,采用巴特沃斯滤波器将数据序列过滤为长期趋势(低频)和短期波动(高频)。进行格兰杰因果分析以审视不同频段气候变化与宏观经济周期之间的关联。基于定量结果,气候变化仅在长期内对宏观经济周期显示出显著影响。就短期影响而言,社会可以通过社会适应方法和自我调整机制减轻气候变化的影响。在大空间尺度上,温度对欧洲农业经济的重要性高于降水。通过考察粮食市场的供需机制,研究期间的人口在长期内是生产者,而在短期内是消费者。这些发现仅反映了在长期研究期间大空间区域内气候变化与宏观经济周期之间的一般相互作用。这些发现既未说明可能暂时扭曲农业经济的个别事件,也未解释一些具体案例。在该研究中,首次提出分析中的尺度思维作为一个基本方法问题,以解释过去农业社会不同时间尺度内气候影响与宏观经济之间的关联。