Federal Reserve Bank of Atlanta, Working Paper最新文献

{"title":"Credit Card Debt Puzzle: Liquid Assets to Pay Bills","authors":"C. Greene, J. Stavins","doi":"10.29338/wp2022-9","DOIUrl":"https://doi.org/10.29338/wp2022-9","url":null,"abstract":": Using transaction data from a US consumer payments diary, we revisit the credit card debt puzzle—a scenario in which consumers revolve credit card debt while also keeping liquid assets as bank account deposits. This scenario is very common: 42 percent of consumers in our sample were borrower-savers in 2019 (those who carry $100 or more in credit card debt and $100 or more in liquid assets). We explain the puzzle by showing that consumers need their liquid assets to pay monthly bills and other necessary expenses, including mortgage or rent. More than 80 percent of bills by value were paid out of bank accounts and could not be charged to credit cards, so bank account balances were needed to cover those basic expenses. On average, borrower-savers’ credit card debt exceeded their liquid assets. The average borrower-saver carried almost $6,400 in unpaid credit card debt and had $5,400 in liquid assets, including checking and savings accounts, cash, and general-purpose prepaid cards. Only 40 percent of borrower-savers had liquid assets greater than their unpaid credit card balance. In addition, borrower-savers’ monthly expenses (bills and purchases) averaged 77 percent of their liquid assets, not leaving enough to repay their credit card debt. On average, the value of their liquid assets could cover only about 60 percent of their unpaid debt plus monthly bills. In almost every category of assets or debts, both housing and non-housing related, borrower-savers were significantly worse off financially than savers. Thus, the differences between borrower-savers and savers are much broader than just their credit card debt and bank account balances; they extend to mortgage debt and home equity. Even when we control for income and demographics in a regression, we find that carrying a mortgage or other debt (such as auto or educational loans) is associated with a higher probability of revolving on a credit card, suggesting that various types of household debt are complements rather than substitutes. During the COVID-19 pandemic in 2020, consumers’ unpaid credit card debt decreased and their liquid assets increased, so the fraction of borrower-savers dropped to 35 percent of the sample. variable instead of the probability of being a bor-sav yields similar estimated coefficients. The results are available from","PeriodicalId":132105,"journal":{"name":"Federal Reserve Bank of Atlanta, Working Paper","volume":"26 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130970079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monetary Policy over the Life Cycle","authors":"R. Braun, Daisuke Ikeda","doi":"10.29338/wp2021-20a","DOIUrl":"https://doi.org/10.29338/wp2021-20a","url":null,"abstract":"A tighter monetary policy is associated with higher nominal and real interest rates on deposits and loans, weaker performance of equities, lower aggregate investment and consumption, and slower growth in employment and wages. We propose a quantitative lifecycle model that reproduces these responses and find that an asset substitution, or Tobin effect, plays a central role in understanding the responses of stock prices and aggregate investment. We use the model to analyze how a household’s exposure to monetary policy varies with its age and find that monetary policy has important distributional effects. The sign, magnitude, and persistence of household consumption responses depend on age, and the pattern of these responses implies that a tighter monetary policy increases inequality in net worth and consumption. JEL classification: E52, E62, G51, D15","PeriodicalId":132105,"journal":{"name":"Federal Reserve Bank of Atlanta, Working Paper","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115068130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}