Input–output networks offer new insights of economic structure

Abstract An input–output (IO) model can be regarded as a network in which nodes represent sectors and directional, weighted links stand for IO transactions between sectors. The integration of IO models with modern network analysis can potentially provide additional insights for better understanding the structure of economies. We introduce the framework of IO network analysis including several popular metrics and tools. We also demonstrate the framework using a hypothesized six-sector economy. The World Input–Output Database (WIOD) 2009 model is used as well for a real-world demonstration. This research shows the potential of IO network analysis in understanding the structure of economies using IO models and data. Our work lays the ground for future studies in developing new methods for IO network analysis and real-world case studies.

[1]  Edward M. Bergman,et al.  National Industry Cluster Templates: A Framework for Applied Regional Cluster Analysis , 2000 .

[2]  Michael Mitzenmacher,et al.  A Brief History of Generative Models for Power Law and Lognormal Distributions , 2004, Internet Math..

[3]  G. Peters Opportunities and challenges for environmental MRIO modelling : Illustrations with the GTAP database , 2007 .

[4]  Thomas J. Misa,et al.  An interview with Edsger W. Dijkstra , 2010, Commun. ACM.

[5]  Judson Caskey,et al.  Inter-industry network structure and the cross-predictability of earnings and stock returns , 2014, Review of Accounting Studies.

[6]  Wei Zhang,et al.  Trans-provincial health impacts of atmospheric mercury emissions in China , 2019, Nature Communications.

[7]  P. Slater The network structure of the United States input-output table , 1978 .

[8]  Marián Boguñá,et al.  Extracting the multiscale backbone of complex weighted networks , 2009, Proceedings of the National Academy of Sciences.

[9]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[10]  Bin Chen,et al.  Unfolding the interplay between carbon flows and socioeconomic development in a city: What can network analysis offer? , 2018 .

[11]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[12]  D. Defays,et al.  An Efficient Algorithm for a Complete Link Method , 1977, Comput. J..

[13]  Manfred Lenzen,et al.  An Application of a Modified Ecological Footprint Method and Structural Path Analysis in a Comparative Institutional Study , 2003 .

[14]  Manfred Lenzen,et al.  Structural path analysis of ecosystem networks , 2007 .

[15]  Ming Xu,et al.  Interconnectedness and Resilience of the U.S. Economy , 2011, Adv. Complex Syst..

[16]  Michael Sonis,et al.  Economic complexity as network complication: Multiregional input-output structural path analysis , 1998 .

[17]  Z. Mi,et al.  China's “Exported Carbon” Peak: Patterns, Drivers, and Implications , 2018 .

[18]  W. Duan Modelling the Evolution of National Economies Based on Input–Output Networks , 2012 .

[19]  Tianzhu Zhang,et al.  Clustering economic sectors in China on a life cycle basis to achieve environmental sustainability , 2013, Frontiers of Environmental Science & Engineering.

[20]  D. Mason,et al.  Compartments revealed in food-web structure , 2003, Nature.

[21]  S. Strogatz Exploring complex networks , 2001, Nature.

[22]  Yi-Ming Wei,et al.  Chinese CO2 emission flows have reversed since the global financial crisis , 2017, Nature Communications.

[23]  Andreas Klaus,et al.  Statistical Analyses Support Power Law Distributions Found in Neuronal Avalanches , 2011, PloS one.

[24]  Bin Chen,et al.  Tracking Inter-Regional Carbon Flows: A Hybrid Network Model. , 2016, Environmental science & technology.

[25]  Matthias Schroder,et al.  Input–Output Analysis , 2011 .

[26]  Sangwon Suh,et al.  Functions, commodities and environmental impacts in an ecological–economic model , 2004 .

[27]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[28]  M. E. J. Newman,et al.  Power laws, Pareto distributions and Zipf's law , 2005 .

[29]  Vasco M. Carvalho,et al.  The Network Origins of Aggregate Fluctuations , 2011 .

[30]  Manfred Lenzen,et al.  BUILDING EORA: A GLOBAL MULTI-REGION INPUT–OUTPUT DATABASE AT HIGH COUNTRY AND SECTOR RESOLUTION , 2013 .

[31]  Mark E. J. Newman,et al.  The Structure and Function of Complex Networks , 2003, SIAM Rev..

[32]  Shigemi Kagawa,et al.  Identifying environmentally important supply chain clusters in the automobile industry , 2013 .

[33]  Jacques Defourny,et al.  STRUCTURAL PATH ANALYSIS AND MULTIPLIER DECOMPOSITION WITHIN A SOCIAL ACCOUNTING MATRIX FRAMEWORK , 1984 .

[34]  Michael L. Fredman,et al.  Trans-Dichotomous Algorithms for Minimum Spanning Trees and Shortest Paths , 1994, J. Comput. Syst. Sci..

[35]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[36]  Fei-Yue Wang,et al.  Parallel Control and Management for Intelligent Transportation Systems: Concepts, Architectures, and Applications , 2010, IEEE Transactions on Intelligent Transportation Systems.

[37]  Leon D. Segal,et al.  Functions , 1995 .

[38]  Roger Guimerà,et al.  Robust patterns in food web structure. , 2001, Physical review letters.

[39]  Florian Blöchl,et al.  Vertex centralities in input-output networks reveal the structure of modern economies. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[40]  Hongmei Zheng,et al.  Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China , 2015 .

[41]  Brian D. Fath,et al.  Network structure of inter-industry flows , 2012, ArXiv.

[42]  Gueorgi Kossinets,et al.  Empirical Analysis of an Evolving Social Network , 2006, Science.

[43]  Edsger W. Dijkstra,et al.  A note on two problems in connexion with graphs , 1959, Numerische Mathematik.

[44]  Bin Chen,et al.  Network environ perspective for urban metabolism and carbon emissions: a case study of Vienna, Austria. , 2012, Environmental science & technology.

[45]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[46]  Bart Los,et al.  Structural decomposition techniques : sense and sensitivity , 1998 .

[47]  S. Allesina,et al.  Secondary extinctions in ecological networks: Bottlenecks unveiled , 2006 .

[48]  G. Cecchi,et al.  Scale-free brain functional networks. , 2003, Physical review letters.

[49]  José M. Rueda-Cantuche,et al.  THE CHOICE OF MODEL IN THE CONSTRUCTION OF INDUSTRY COEFFICIENTS MATRICES , 2009, Efficiency and Input-Output Analyses.

[50]  Sangwon Suh,et al.  Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization , 2013, Soc. Networks.

[51]  H. Kitano Systems Biology: A Brief Overview , 2002, Science.

[52]  Bin Chen,et al.  Multiregional input–output and ecological network analyses for regional energy–water nexus within China , 2017, Applied Energy.

[53]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[54]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[55]  Klaus Hubacek,et al.  A new and integrated hydro-economic accounting and analytical framework for water resources: a case study for North China. , 2008, Journal of environmental management.