{"id":{"repo_id":"claremont","oai_identifier":"oai:scholarship.claremont.edu:cgu_etd-1328"},"canonical_url":"https://search.dev.ndltd.org/etd/claremont/oai:scholarship.claremont.edu:cgu_etd-1328","repository":{"repo_id":"claremont","name":"Claremont Graduate University","base_url":"https://scholarship.claremont.edu/do/oai/"},"display":{"title":"The Effects of Mandated Stress-Testing on Bank Risk","abstract":"<p>In the aftermath of the Financial Crisis, The United States Congress passed the Dodd- Frank Wall Street Reform and Consumer Protection Act in 2010 (12 USC 5365(i)(1)) with particular rules on how Bank Holding Companies (BHC’s) are to be supervised. If a BHC has total consolidated assets greater than $50bn then they are required to undergo the Comprehensive Capital Asset Review (CCAR) exercise. If a BHC has total consolidated assets between $10bn and $50, they are required to undergo Dodd-Frank Act Stress-Testing (DFAST). The purpose of stress-testing and classifications are to ensure that BHCs have sufficient capital and planning processes in place to withstand future crises. However, the classifications were seemingly set arbitrarily and there is a need to investigate whether the regulation has the intended purpose of BHC risk reduction. By using a novel quasi-experimental design strategy, this research investigates and estimates whether the regulation had the intended effect of reducing bank risk. First, two unique measures of bank risk (Z-score) are developed and estimated for 220 banks in a sample from The Banker’s Database. These measures are used to develop an Regression Discontinuity Design (RDD) empirical strategy to test the DFAST and CCAR thresholds, $10bn and $50bn, respectively. The thresholds are tested as an overall period from 2012 - 2018 and by year. Additionally, extensive use of a McCrary Test for manipulation of the running variable is used as a robustness check. It is a statistical method that allows for detection of whether BHC’s or a regulatory agency adjusted total assets in order to be categorized differently. There is no evidence for partial or complete manipulation. BHCs that participated in CCAR stress-tests, experienced a near doubling of their Z-score score, interpreted as a major decrease in bank risk. The results indicate a 106% increase in Zscore at the $50bn CCAR threshold for the overall period of 2012 - 2018. So, at the threshold of $50bn, comparing the average bank above the threshold to below, the bank that was CCAR stress-tested had a 106% increase in Z-score compared to the bank that was not CCAR stresstested. This also implies a dramatic decrease in the probability of default. Additionally, the by year testing indicates a positive magnitude of risk reduction. Particularly strong results are found for risk reduction effects for CCAR stress-tested banks in 2015 and 2016 (332% and 208%, respectively compared to a base year of 2012) . The results indicate a similar magnitude for the $10bn DFAST threshold for the overall period of 2012 - 2018, but are not statistically significant. Similarly, the by year testing indicates a positive magnitude of risk reduction for small/medium sized banks.</p>","abstract_html":"&lt;p&gt;In the aftermath of the Financial Crisis, The United States Congress passed the Dodd- Frank Wall Street Reform and Consumer Protection Act in 2010 (12 USC 5365(i)(1)) with particular rules on how Bank Holding Companies (BHC’s) are to be supervised. If a BHC has total consolidated assets greater than $50bn then they are required to undergo the Comprehensive Capital Asset Review (CCAR) exercise. If a BHC has total consolidated assets between $10bn and $50, they are required to undergo Dodd-Frank Act Stress-Testing (DFAST). The purpose of stress-testing and classifications are to ensure that BHCs have sufficient capital and planning processes in place to withstand future crises. However, the classifications were seemingly set arbitrarily and there is a need to investigate whether the regulation has the intended purpose of BHC risk reduction. By using a novel quasi-experimental design strategy, this research investigates and estimates whether the regulation had the intended effect of reducing bank risk. First, two unique measures of bank risk (Z-score) are developed and estimated for 220 banks in a sample from The Banker’s Database. These measures are used to develop an Regression Discontinuity Design (RDD) empirical strategy to test the DFAST and CCAR thresholds, $10bn and $50bn, respectively. The thresholds are tested as an overall period from 2012 - 2018 and by year. Additionally, extensive use of a McCrary Test for manipulation of the running variable is used as a robustness check. It is a statistical method that allows for detection of whether BHC’s or a regulatory agency adjusted total assets in order to be categorized differently. There is no evidence for partial or complete manipulation. BHCs that participated in CCAR stress-tests, experienced a near doubling of their Z-score score, interpreted as a major decrease in bank risk. The results indicate a 106% increase in Zscore at the $50bn CCAR threshold for the overall period of 2012 - 2018. So, at the threshold of $50bn, comparing the average bank above the threshold to below, the bank that was CCAR stress-tested had a 106% increase in Z-score compared to the bank that was not CCAR stresstested. This also implies a dramatic decrease in the probability of default. Additionally, the by year testing indicates a positive magnitude of risk reduction. Particularly strong results are found for risk reduction effects for CCAR stress-tested banks in 2015 and 2016 (332% and 208%, respectively compared to a base year of 2012) . The results indicate a similar magnitude for the $10bn DFAST threshold for the overall period of 2012 - 2018, but are not statistically significant. Similarly, the by year testing indicates a positive magnitude of risk reduction for small/medium sized banks.&lt;/p&gt;","abstract_has_math":true,"creators":["Mathur, Nikhil"],"institution":null,"degree_name":"Economics, PhD","degree_level":"Restricted to Claremont Colleges Dissertation","degree_discipline":"School of Social Science, Politics, and Evaluation","degree_department":null,"school":null,"contributors":["Hisam Sabouni","Clas Wihlborg","Pierangelo De Pace"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-01T08:00:00Z","date_published":"2020-01-01T08:00:00Z","updated_at":"2026-07-24T01:39:50Z","subjects":["Banking","Financial Crisis","Financial Intermediation","Financial Policy","Government Policy and Regulation","Risk Management","Economics","Finance"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarship.claremont.edu/cgu_etd/248","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hisam Sabouni","Clas Wihlborg","Pierangelo De Pace"]},{"key":"dc:creator","label":"Author","values":["Mathur, Nikhil"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2022-03-02T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["School of Social Science, Politics, and Evaluation"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Restricted to Claremont Colleges Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Economics, PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Banking","Financial Crisis","Financial Intermediation","Financial Policy","Government Policy and Regulation","Risk Management","Economics","Finance"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarship.claremont.edu/cgu_etd/248"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>In the aftermath of the Financial Crisis, The United States Congress passed the Dodd- Frank Wall Street Reform and Consumer Protection Act in 2010 (12 USC 5365(i)(1)) with particular rules on how Bank Holding Companies (BHC’s) are to be supervised. If a BHC has total consolidated assets greater than $50bn then they are required to undergo the Comprehensive Capital Asset Review (CCAR) exercise. If a BHC has total consolidated assets between $10bn and $50, they are required to undergo Dodd-Frank Act Stress-Testing (DFAST). The purpose of stress-testing and classifications are to ensure that BHCs have sufficient capital and planning processes in place to withstand future crises. However, the classifications were seemingly set arbitrarily and there is a need to investigate whether the regulation has the intended purpose of BHC risk reduction. By using a novel quasi-experimental design strategy, this research investigates and estimates whether the regulation had the intended effect of reducing bank risk. First, two unique measures of bank risk (Z-score) are developed and estimated for 220 banks in a sample from The Banker’s Database. These measures are used to develop an Regression Discontinuity Design (RDD) empirical strategy to test the DFAST and CCAR thresholds, $10bn and $50bn, respectively. The thresholds are tested as an overall period from 2012 - 2018 and by year. Additionally, extensive use of a McCrary Test for manipulation of the running variable is used as a robustness check. It is a statistical method that allows for detection of whether BHC’s or a regulatory agency adjusted total assets in order to be categorized differently. There is no evidence for partial or complete manipulation. BHCs that participated in CCAR stress-tests, experienced a near doubling of their Z-score score, interpreted as a major decrease in bank risk. The results indicate a 106% increase in Zscore at the $50bn CCAR threshold for the overall period of 2012 - 2018. So, at the threshold of $50bn, comparing the average bank above the threshold to below, the bank that was CCAR stress-tested had a 106% increase in Z-score compared to the bank that was not CCAR stresstested. This also implies a dramatic decrease in the probability of default. Additionally, the by year testing indicates a positive magnitude of risk reduction. Particularly strong results are found for risk reduction effects for CCAR stress-tested banks in 2015 and 2016 (332% and 208%, respectively compared to a base year of 2012) . The results indicate a similar magnitude for the $10bn DFAST threshold for the overall period of 2012 - 2018, but are not statistically significant. Similarly, the by year testing indicates a positive magnitude of risk reduction for small/medium sized banks.</p>"]},{"key":"dc:title","label":"Title","values":["The Effects of Mandated Stress-Testing on Bank Risk"]}]}],"canonical_facts":{"dc:contributor":["Hisam Sabouni","Clas Wihlborg","Pierangelo De Pace"],"dc:creator":["Mathur, Nikhil"],"dc:date.available":["2022-03-02T08:00:00Z"],"dc:description.abstract":["<p>In the aftermath of the Financial Crisis, The United States Congress passed the Dodd- Frank Wall Street Reform and Consumer Protection Act in 2010 (12 USC 5365(i)(1)) with particular rules on how Bank Holding Companies (BHC’s) are to be supervised. If a BHC has total consolidated assets greater than $50bn then they are required to undergo the Comprehensive Capital Asset Review (CCAR) exercise. If a BHC has total consolidated assets between $10bn and $50, they are required to undergo Dodd-Frank Act Stress-Testing (DFAST). The purpose of stress-testing and classifications are to ensure that BHCs have sufficient capital and planning processes in place to withstand future crises. However, the classifications were seemingly set arbitrarily and there is a need to investigate whether the regulation has the intended purpose of BHC risk reduction. By using a novel quasi-experimental design strategy, this research investigates and estimates whether the regulation had the intended effect of reducing bank risk. First, two unique measures of bank risk (Z-score) are developed and estimated for 220 banks in a sample from The Banker’s Database. These measures are used to develop an Regression Discontinuity Design (RDD) empirical strategy to test the DFAST and CCAR thresholds, $10bn and $50bn, respectively. The thresholds are tested as an overall period from 2012 - 2018 and by year. Additionally, extensive use of a McCrary Test for manipulation of the running variable is used as a robustness check. It is a statistical method that allows for detection of whether BHC’s or a regulatory agency adjusted total assets in order to be categorized differently. There is no evidence for partial or complete manipulation. BHCs that participated in CCAR stress-tests, experienced a near doubling of their Z-score score, interpreted as a major decrease in bank risk. The results indicate a 106% increase in Zscore at the $50bn CCAR threshold for the overall period of 2012 - 2018. So, at the threshold of $50bn, comparing the average bank above the threshold to below, the bank that was CCAR stress-tested had a 106% increase in Z-score compared to the bank that was not CCAR stresstested. This also implies a dramatic decrease in the probability of default. Additionally, the by year testing indicates a positive magnitude of risk reduction. Particularly strong results are found for risk reduction effects for CCAR stress-tested banks in 2015 and 2016 (332% and 208%, respectively compared to a base year of 2012) . The results indicate a similar magnitude for the $10bn DFAST threshold for the overall period of 2012 - 2018, but are not statistically significant. Similarly, the by year testing indicates a positive magnitude of risk reduction for small/medium sized banks.</p>"],"dc:identifier":["https://scholarship.claremont.edu/cgu_etd/248"],"dc:subject":["Banking","Financial Crisis","Financial Intermediation","Financial Policy","Government Policy and Regulation","Risk Management","Economics","Finance"],"dc:title":["The Effects of Mandated Stress-Testing on Bank Risk"],"thesis:degree_discipline":["School of Social Science, Politics, and Evaluation"],"thesis:degree_level":["Restricted to Claremont Colleges Dissertation"],"thesis:degree_name":["Economics, PhD"]},"updated_at":"2026-07-24T01:39:50Z"}