Sector Similarity in Input-Output Networks
dc.contributor.author | Zhao, Xiaoyue | |
dc.contributor.advisor | Xu, Ming | |
dc.date.accessioned | 2015-04-20T15:58:05Z | |
dc.date.available | NO_RESTRICTION | en_US |
dc.date.available | 2015-04-20T15:58:05Z | |
dc.date.issued | 2015-05 | |
dc.date.submitted | 2015-04 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/110981 | |
dc.description.abstract | Input-Output (IO) model is a macroeconomic model describing the inter-sectoral interdependence of economies. It is widely used to analyze environmental impacts from economic activities. The conventional method to build up the IO table is largely based on onerous data collection but simple linear approximation. In order to more accurately construct IO tables and efficiently capture outliers among the dataset, we introduce network theories to investigate the underlying relationships between economic sectors. By probing into similarity between economic sectors, we could conclude correlations and connection patterns between individual economic flows. In this way, even with partial data of one IO table available, it will still be possible to restore the complete map of an IO table by referencing their inherited relationships. The achievement of such prediction will further advance our environmental analysis that based upon IO model via more accurate and up-to-data data. This study focuses on similarity exploration between economic sectors in IO model and constructing a theoretical framework for establishing IO table using network theories of link prediction. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Input-Ouput Model | en_US |
dc.subject | network theory | en_US |
dc.subject | missing links prediction | en_US |
dc.subject | similarity | en_US |
dc.title | Sector Similarity in Input-Output Networks | en_US |
dc.type | Thesis | en_US |
dc.description.thesisdegreename | Master of Science (MS) | en_US |
dc.description.thesisdegreediscipline | Natural Resources and Environment | en_US |
dc.description.thesisdegreegrantor | University of Michigan | en_US |
dc.contributor.committeemember | Liang, Sai | |
dc.identifier.uniqname | xiaoyuez | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/110981/1/Sector Similarity in Input-Output Networks (Xiaoyue Zhao)_2015.pdf | |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.