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The Corruption Footprints of Nations
Author(s) -
Xiao Yanyan,
Lenzen Manfred,
BenoîtNorris Catherine,
Norris Gregory A.,
Murray Joy,
Malik Arunima
Publication year - 2018
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/jiec.12537
Subject(s) - language change , china , business , supply chain , developing country , economics , clothing , development economics , international trade , economic growth , political science , art , literature , marketing , law
Summary In this study, we innovatively apply multiregional input‐output analysis to calculate corruption footprints of nations and show the details of commodities that use the most employment affected by corruption (EAC), as they flow between countries. Every country's corruption footprint includes its domestic corruption and the corruption imported by global supply chains to meet final demand. Our results show that, generally, the net corruption exporters are developing countries, with the exception of Italy where corruption is likely to be more affected by political and cultural factors than economic factors. China is the largest gross corruption exporter, and India follows close behind, with clothing as one of the industries in which the most people are affected by corruption. This is because: (1) China and India are major clothing exporters, thus many workers are employed in the clothing industry within the country as well as in countries providing intermediate commodities by supply chains, and (2) corruption is high in China and India. Our results can be useful to identify where regulations to combat corruption can have the greatest impact. More important, the method we use can be applied to link corruption to other economic and social aspects of trade, such as working conditions, thus making it possible to find avenues for tackling the problem that are not usually considered in anticorruption strategies.