论文标题
人类财富的演变：趋势和波动
Human wealth evolution: trends and fluctuations
论文作者
论文摘要
对人类财富历史的因果描述是否可以想象？为了调查此事，我们引入了一个简单的因果关系，尽管汇总的模型强烈，但假设观察到的财富增长主要是由人类协作努力驱动的，人类的协作努力本身随着财富的增加而增加。作为经验参考，我们使用的时间序列描述了三个欧洲国家，英国，法国和瑞典的八个世纪的人均国内产品（GDP）。该模型需要足够大的人口来进行破坏性事件，例如饥荒，流行病和战争，不要破坏社会的基本运作。然后可以通过具有三个自由参数的普通微分方程来描述财富演化趋势。该解决方案具有有限的时间奇点，这表明缺乏长期可持续性。从一个国家到另一个国家，奇点发生的一年在公元2020年的公元相近略有差异。 GDP时间序列在1900年后减少了，为奇异性的出现产生了相似的值，因此可以预测数百年前。从早期到1700年，将GDP系列限制在奇异时间时也会产生稳定且一致的预测。 {跨越八个世纪以及同一时期的第一个和过去四个世纪的偏向偏见数据获得了功率谱。所有光谱都有一个总体签名，随着反向频率平方，功率衰减。嵌入式峰让人联想到经济文献中描述的周期，但也存在于工业化之前的时间序列中。 GDP系列中的背景波动暂时解释为对破坏性随机事件的社会反应。例如划界以及战争和流行病之后的新经济活动
Is a causal description of human wealth history conceivable? To investigate the matter we introduce a simple causal albeit strongly aggregated model, assuming that the observed wealth growth is mainly driven by human collaborative efforts whose intensity itself increases with increasing wealth. As an empirical reference we use time series describing eight centuries of per capita annual gross domestic products (GDP) of three European countries, the UK, France and Sweden. The model requires a population large enough for disruptive events, e.g. famine, epidemics and wars, not to destroy the fundamental workings of society. The wealth evolution trend can then be described by an ordinary differential equation with three free parameters. The solution features a finite time singularity, which suggests a lack of long term sustainability. The year at which the singularity occurs has a slight variation near 2020 AD from one country to another. GDP time series curtailed after 1900 AD produce similar values for the occurrence of the singularity, which thus could be predicted more than hundred years ago. Curtailing the GDP series from the early years up to 1700 AD also produces stable and consistent predictions for the singularity time. {Power spectra are obtained for de-trended data spanning eight centuries, as well as for the first and last four centuries of the same period. All spectra have an overall signature where the power decays as the inverse frequency squared. The embedded peaks are reminiscent of the cycles described in the economic literature, but are also present in time series far predating industrialization. The background fluctuations in the GDP series is tentatively interpreted as societal response to disruptive stochastic events. e.g. new economic activities following epochal discoveries, as well as wars and epidemics
