[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-210054-en":3,"doc-seo-210054-105":31,"detail-sidebar-cat-0-en-105":97},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},210054,7971474921005,"Grenda","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Unemployment Insurance as a Financial Stabilizer - Evidence from Large Benefit Expansions","Unemployment insurance (UI) is assessed as an automatic stabilizer of household and aggregate finances during unemployment shocks. The study uses administrative credit bureau records and exploits the COVID-19 period’s unprecedented changes in unemployment and UI generosity. Results show aggregate sensitivity to the unemployment rate fell sharply for auto loans and credit cards, and state-level withdrawals identify UI as the primary driver. Robustness checks support the findings, while a back-of-the-envelope calculation links UI expansions to preventing about 59% of potential delinquency-months.","Unemployment Insurance as a Financial Stabilizer:  \nEvidence from Large Benefit Expansions ∗  \nNiklas Flamang† Sreeraahul Kancherla‡  \nFirst version: August 2022  \nThis version: September 2023  \nAbstract  \nTo what extent does unemployment insurance (UI) attenuate aggregate financial responses to unemployment shocks? We answer this question using administrative credit bureau records and the unprecedented changes in unemployment and UI generosity during the Covid-19 pandemic. We first find that aggregate sensitivity to the unemployment rate decreased by 50% for auto loans and 66% for credit cards between January 2017 and March 2021 . To isolate the effect of UI from other contemporaneous policies shifting unemployment shock responsiveness, we employ a staggered event study design around state-level withdrawals from federal UI programs in late 2021 . We find that almost all of the pandemic sensitivity drop is attributable to UI expansions. Our two designs are qualitatively robust to placebo tests on plausibly unaffected credit types, potential demand-side responses for increased credit, and alternate estimation specifications. In a back-of-the-envelope calculation, we calculate that UI expansions prevented about 59% of total potential delinquency-months. Taken together, these results imply that federal UI expansions have had a substantially stabilizing effect during the Covid-19 pandemic. Our findings thus provide powerful empirical support for a largely theoretical body of research on the role of UI as an automatic stabilizer of aggregate economic conditions.  \nJEL Classification: E2, J6, G5  \n∗We thank Amir Kermani, Chen Lian, Emi Nakamura, Jesse Rothstein, Benjamin Schoefer, Emmanuel Saez, Jn Steinsson, Danny Yagan, and seminar audiences at UC Berkeley GEMS for helpful comments and conversations. We thank Evan White and the California Policy Lab for administrative data access and computing support for our work. We thank Geoff Schnorr for sharing code to calculate potential unemployment benefit durations over time. We thank the Center for Equitable Growth, the UC Berkeley Opportunity Lab’s Initiative on Inequality and Place, and the Smith Richardson Foundation for research funding. Kancherla additionally gratefully acknowledges support from the National Science Foundation’s Graduate Fellowship Research Program, under Grant No. 1752814. This project uses confidential credit record microdata provided through a California Policy Lab agreement with Experian, which has reviewed all results in this paper for inadvertent disclosure. All findings and opinions are those of the authors alone and do not necessarily represent the opinions of the California Policy Lab or Experian.  \n†Nova School of Economics. Email: [nick.flamang@novasbe.pt](nick.flamang@novasbe.pt)  \n‡UC Berkeley Department of Economics. Email: [skancherla@berkeley.edu](skancherla@berkeley.edu)  \n1 Introduction  \nJob loss induces substantial financial stress: Households experiencing temporary unemployment spells are more likely to default on their loans (Braxton et al., 2020; Hurd and Rohwedder, 2010) or to file for bankruptcy (Keys, 2018) . Liquidity—as opposed to wealth—seems to be a crucial determinant of consumption smoothing behavior, with liquidity-constrained households appearing much more sensitive to adverse shocks (Gerardi et al., 2017; Ganong and Noel, 2020; Ganong et al., 2020a) . An important policy question is the extent to which targeted liquidity provision from unemployment insurance (UI) benefits insulate households from these adverse financial effects of job loss. Empirical evidence in this area has primarily focused on the micro-level impacts of the UI system. Using survey data, Hsu et al. (2018) leverage heterogeneity in UI generosity across states and over time to show that workers’ job loss translates into less financial distress during more generous benefit regimes.  \nAt the macroeconomic level, Kekre (2021) shows that UI can stabilize aggregate econ","cbCaiiQpCn87icpK","https://ap.wps.com/l/cbCaiiQpCn87icpK","pdf",6040477,2,1,42,"English","en",105,"# Abstract\n## Introduction\n## Policy question and prior evidence\n## Empirical strategy and identification\n## Findings and robustness checks","[{\"question\":\"How does the study measure whether unemployment insurance stabilizes financial outcomes?\",\"answer\":\"It analyzes how aggregate financial responses to unemployment shocks change over time using administrative credit bureau records during major UI and unemployment shifts in the COVID-19 period.\"},{\"question\":\"What major effect sizes are reported for auto loans and credit cards?\",\"answer\":\"The study finds aggregate sensitivity to the unemployment rate decreases by about 50% for auto loans and 66% for credit cards between January 2017 and March 2021.\"},{\"question\":\"How do the authors identify the impact of UI expansions separately from other policies?\",\"answer\":\"They use a staggered event study design around late-2021 state-level withdrawals from federal UI programs, isolating UI changes from contemporaneous policy effects.\"}]","Unemployment Insurance as a Financial Stabilizer - Evidence from Large Benefit Expansions | PDF",1788642580,106,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":92,"head_meta":94,"extra_data":96,"updated_unix":29},"unemployment-insurance-as-a-financial-stabilizer-evidence-from-large-benefit-expansions","",{"@graph":37,"@context":91},[38,54,74],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/unemployment-insurance-as-a-financial-stabilizer-evidence-from-large-benefit-expansions/210054/",4,{"url":52,"name":13,"@type":55,"image":56,"author":61,"headline":13,"publisher":63,"fileFormat":66,"inLanguage":24,"description":14,"dateModified":67,"datePublished":68,"encodingFormat":66,"isAccessibleForFree":69,"interactionStatistic":70},"DigitalDocument",{"url":57,"@type":58,"width":59,"height":60},"https://docshare.wps.com/thumbnails/unemployment-insurance-as-a-financial-stabilizer-evidence-from-large-benefit-expansions/210054.png","ImageObject",300,407,{"name":9,"@type":62},"Person",{"url":42,"name":64,"@type":65},"DocShare","Organization","application/pdf","2026-09-11","2026-09-05",true,{"@type":71,"interactionType":72,"userInteractionCount":20},"InteractionCounter",{"@type":73},"ViewAction",{"@type":75,"mainEntity":76},"FAQPage",[77,83,87],{"name":78,"@type":79,"acceptedAnswer":80},"How does the study measure whether unemployment insurance stabilizes financial outcomes?","Question",{"text":81,"@type":82},"It analyzes how aggregate financial responses to unemployment shocks change over time using administrative credit bureau records during major UI and unemployment shifts in the COVID-19 period.","Answer",{"name":84,"@type":79,"acceptedAnswer":85},"What major effect sizes are reported for auto loans and credit cards?",{"text":86,"@type":82},"The study finds aggregate sensitivity to the unemployment rate decreases by about 50% for auto loans and 66% for credit cards between January 2017 and March 2021.",{"name":88,"@type":79,"acceptedAnswer":89},"How do the authors identify the impact of UI expansions separately from other policies?",{"text":90,"@type":82},"They use a staggered event study design around late-2021 state-level withdrawals from federal UI programs, isolating UI changes from contemporaneous policy effects.","https://schema.org",{"og:url":52,"og:type":93,"og:title":13,"og:site_name":64,"og:description":14},"article",{"robots":95,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":98},[99,103,107,111,116,121,126,129,134,137,141],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},"Exam",70,"exam",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},5,"Comic",60,"comic",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},6,"Technology",50,"technology",{"id":122,"doc_module":4,"doc_module_name":47,"category_name":123,"show_sort_weight":124,"slug":125},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":127,"slug":128},30,"research-report",{"id":130,"doc_module":4,"doc_module_name":47,"category_name":131,"show_sort_weight":132,"slug":133},9,"Religion & Spirituality",20,"religion-spirituality",{"id":132,"doc_module":4,"doc_module_name":47,"category_name":135,"show_sort_weight":132,"slug":136},"World Cup","world-cup",{"id":138,"doc_module":4,"doc_module_name":47,"category_name":139,"show_sort_weight":138,"slug":140},10,"Lifestyle","lifestyle",{"id":142,"doc_module":4,"doc_module_name":47,"category_name":143,"show_sort_weight":112,"slug":144},19,"General","general"]