{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/122874"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/122874","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Propagation of credit freezes in financial lending networks","abstract":"We consider a network model of financial intermediation where banks (financial intermediaries) lend to and borrow from each other and supply funds to clients. A key decision for a bank is whether to extend credit to other banks, which may then default on those loans. In contrast to much of the previous literature on financial networks, the focus is on how \"fear of future default\" can lead to \"credit freezes\" before the realization of these uncertainties. Specifically, we show that increases in the riskiness of one or few banks can lead to systemic credit freeze throughout the financial network. Notably, credit freezes can happen in parts of the network that are not directly affected by increased uncertainty, both because the potential consequences of uncertainty travel throughout the network and also because such changes affect profitability of loans between different parties. We then use this framework to analyze the effects of policy interventions on systemic credit freezes.","abstract_html":"We consider a network model of financial intermediation where banks (financial intermediaries) lend to and borrow from each other and supply funds to clients. A key decision for a bank is whether to extend credit to other banks, which may then default on those loans. In contrast to much of the previous literature on financial networks, the focus is on how "fear of future default" can lead to "credit freezes" before the realization of these uncertainties. Specifically, we show that increases in the riskiness of one or few banks can lead to systemic credit freeze throughout the financial network. Notably, credit freezes can happen in parts of the network that are not directly affected by increased uncertainty, both because the potential consequences of uncertainty travel throughout the network and also because such changes affect profitability of loans between different parties. We then use this framework to analyze the effects of policy interventions on systemic credit freezes.","abstract_has_math":false,"creators":["Siderius, James."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Asu Ozdaglar."],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018","date_published":"2018","updated_at":"2026-07-22T22:21:16Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/122874","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Asu Ozdaglar."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Siderius, James."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-11-12T17:40:47Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-11-12T17:40:47Z"]},{"key":"dc:date.issued","label":"Date","values":["2018"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering and Computer Science."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/122874"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 131-134)."]},{"key":"dc:description.abstract","label":"Abstract","values":["We consider a network model of financial intermediation where banks (financial intermediaries) lend to and borrow from each other and supply funds to clients. A key decision for a bank is whether to extend credit to other banks, which may then default on those loans. In contrast to much of the previous literature on financial networks, the focus is on how \"fear of future default\" can lead to \"credit freezes\" before the realization of these uncertainties. Specifically, we show that increases in the riskiness of one or few banks can lead to systemic credit freeze throughout the financial network. Notably, credit freezes can happen in parts of the network that are not directly affected by increased uncertainty, both because the potential consequences of uncertainty travel throughout the network and also because such changes affect profitability of loans between different parties. We then use this framework to analyze the effects of policy interventions on systemic credit freezes."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Propagation of credit freezes in financial lending networks"]}]}],"canonical_facts":{"dc:contributor.advisor":["Asu Ozdaglar."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Siderius, James."],"dc:date.accessioned":["2019-11-12T17:40:47Z"],"dc:date.available":["2019-11-12T17:40:47Z"],"dc:date.issued":["2018"],"dc:description":["Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 131-134)."],"dc:description.abstract":["We consider a network model of financial intermediation where banks (financial intermediaries) lend to and borrow from each other and supply funds to clients. A key decision for a bank is whether to extend credit to other banks, which may then default on those loans. In contrast to much of the previous literature on financial networks, the focus is on how \"fear of future default\" can lead to \"credit freezes\" before the realization of these uncertainties. Specifically, we show that increases in the riskiness of one or few banks can lead to systemic credit freeze throughout the financial network. Notably, credit freezes can happen in parts of the network that are not directly affected by increased uncertainty, both because the potential consequences of uncertainty travel throughout the network and also because such changes affect profitability of loans between different parties. We then use this framework to analyze the effects of policy interventions on systemic credit freezes."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/122874"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Propagation of credit freezes in financial lending networks"],"dc:type":["Thesis"],"thesis:degree_name":["Master"]},"updated_at":"2026-07-22T22:21:16Z"}