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论世界经济的结构:一种吸收马尔可夫链方法。

On the Structure of the World Economy: An Absorbing Markov Chain Approach.

作者信息

Kostoska Olivera, Stojkoski Viktor, Kocarev Ljupco

机构信息

Faculty of Economics-Prilep, "St. Kliment Ohridski" University, 7000 Bitola, Macedonia.

Macedonian Academy of Sciences and Arts, 1000 Skopje, Macedonia.

出版信息

Entropy (Basel). 2020 Apr 23;22(4):482. doi: 10.3390/e22040482.

DOI:10.3390/e22040482
PMID:33286256
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7516966/
Abstract

The expansion of global production networks has raised many important questions about the interdependence among countries and how future changes in the world economy are likely to affect the countries' positioning in global value chains. We are approaching the structure and lengths of value chains from a completely different perspective than has been available so far. By assigning a random endogenous variable to a network linkage representing the number of intermediate sales/purchases before absorption (final use or value added), the discrete-time absorbing Markov chains proposed here shed new light on the world input/output networks. The variance of this variable can help assess the risk when shaping the chain length and optimize the level of production. Contrary to what might be expected simply on the basis of comparative advantage, the results reveal that both the input and output chains exhibit the same quasi-stationary product distribution. Put differently, the expected proportion of time spent in a state before absorption is invariant to changes of the network type. Finally, the several global metrics proposed here, including the probability distribution of global value added/final output, provide guidance for policy makers when estimating the resilience of world trading system and forecasting the macroeconomic developments.

摘要

全球生产网络的扩张引发了许多关于国家间相互依存关系的重要问题,以及世界经济未来的变化可能如何影响各国在全球价值链中的定位。我们正在从一个与迄今为止所采用的视角截然不同的角度来探讨价值链的结构和长度。通过将一个随机内生变量赋予一个代表吸收前(最终使用或增值)中间销售/采购数量的网络联系,本文提出的离散时间吸收马尔可夫链为世界投入产出网络带来了新的见解。这个变量的方差有助于在确定链长时评估风险,并优化生产水平。与仅基于比较优势可能预期的情况相反,结果显示投入链和产出链都呈现出相同的准平稳产品分布。换言之,在吸收前处于某一状态所花费时间的预期比例对于网络类型的变化是不变的。最后,本文提出的几个全球指标,包括全球增加值/最终产出的概率分布,在估计世界贸易体系的韧性和预测宏观经济发展时为政策制定者提供了指导。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6858/7516966/ee1195303394/entropy-22-00482-g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6858/7516966/8fe1574eb5b0/entropy-22-00482-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6858/7516966/ee1195303394/entropy-22-00482-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6858/7516966/17ebebd43818/entropy-22-00482-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6858/7516966/b63624346756/entropy-22-00482-g002.jpg
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本文引用的文献

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How production networks amplify economic growth.生产网络如何放大经济增长。
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3
World Input-Output Network.世界投入产出网络
将社会核算矩阵(SAM)解读为一种信息渠道。
Entropy (Basel). 2020 Nov 28;22(12):1346. doi: 10.3390/e22121346.
PLoS One. 2015 Jul 29;10(7):e0134025. doi: 10.1371/journal.pone.0134025. eCollection 2015.
4
Growth in emission transfers via international trade from 1990 to 2008.1990 年至 2008 年国际贸易中排放转移的增长。
Proc Natl Acad Sci U S A. 2011 May 24;108(21):8903-8. doi: 10.1073/pnas.1006388108. Epub 2011 Apr 25.