Sector Similarity in Input-Output Networks

Input-Ouput Model;network theory;missing links prediction;similarity;Natural Resources and Environment

Zhao, XiaoyueLiang, Sai ;

University of Michigan

关键词: Input-Ouput Model;    network theory;    missing links prediction;    similarity;    Natural Resources and Environment;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/110981/Sector%20Similarity%20in%20Input-Output%20Networks%20%28Xiaoyue%20Zhao%29_2015.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Input-Output (IO) model is a macroeconomic model describing the inter-sectoralinterdependence of economies. It is widely used to analyze environmental impacts fromeconomic activities. The conventional method to build up the IO table is largely basedon onerous data collection but simple linear approximation. In order to more accuratelyconstruct IO tables and efficiently capture outliers among the dataset, we introducenetwork theories to investigate the underlying relationships between economic sectors.By probing into similarity between economic sectors, we could conclude correlationsand connection patterns between individual economic flows. In this way, even withpartial data of one IO table available, it will still be possible to restore the completemap of an IO table by referencing their inherited relationships. The achievement of suchprediction will further advance our environmental analysis that based upon IO modelvia more accurate and up-to-data data. This study focuses on similarity explorationbetween economic sectors in IO model and constructing a theoretical framework forestablishing IO table using network theories of link prediction.