Committee (FOMC) has raised the federal funds target rate from near zero to around 5%. This has driven up other rates—mortgages, US Treasuries, bank loans, etc. Given the high speed at which rates have risen, there are concerns about the cost of rolling over the existing debt for firms, households, and governments. Specifically, when debt matures, issuers must decide whether to “roll over” their debt—by issuing new debt at the current rate—or find other resources to repay the debt. Take for example a small business owner who, in 2020, at the beginning of the COVID-19 crisis, borrowed at a 3% interest rate with a three-year maturity. This year, when the owner returns to the bank to discuss the rollover of the loan, they will likely be quoted a rate that is double to triple their existing rate. This creates a difficult choice for the business owner: maintain the same amount of debt and pay double or triple in interest or reduce their level of debt and cut costs. This trade-off applies to any debt issuers, e.g., the US government. In the fourth quarter of 2022, the total public debt, according to the US Treasury Department, was just over $31.4 trillion.1 Below, we show a breakdown of this debt: Assessing the Costs of Rolling Over Government Debt
{"title":"Assessing the Costs of Rolling Over Government Debt","authors":"J. Kozlowski, Samuel Jordan-Wood","doi":"10.20955/es.2023.13","DOIUrl":"https://doi.org/10.20955/es.2023.13","url":null,"abstract":"Committee (FOMC) has raised the federal funds target rate from near zero to around 5%. This has driven up other rates—mortgages, US Treasuries, bank loans, etc. Given the high speed at which rates have risen, there are concerns about the cost of rolling over the existing debt for firms, households, and governments. Specifically, when debt matures, issuers must decide whether to “roll over” their debt—by issuing new debt at the current rate—or find other resources to repay the debt. Take for example a small business owner who, in 2020, at the beginning of the COVID-19 crisis, borrowed at a 3% interest rate with a three-year maturity. This year, when the owner returns to the bank to discuss the rollover of the loan, they will likely be quoted a rate that is double to triple their existing rate. This creates a difficult choice for the business owner: maintain the same amount of debt and pay double or triple in interest or reduce their level of debt and cut costs. This trade-off applies to any debt issuers, e.g., the US government. In the fourth quarter of 2022, the total public debt, according to the US Treasury Department, was just over $31.4 trillion.1 Below, we show a breakdown of this debt: Assessing the Costs of Rolling Over Government Debt","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"121 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89475808","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":"Statistics on Federal Reserve System Employment, 1915 to 2022","authors":"Genevieve Podleski, J. Rose, J. Whipple","doi":"10.20955/es.2023.16","DOIUrl":"https://doi.org/10.20955/es.2023.16","url":null,"abstract":"","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"302 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88443719","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}
have been increasingly exposed to unexpected events or shocks originating from abroad. For instance, the COVID-19 pandemic and resulting supply-chain disruptions, including bottlenecks and increased costs for shipping goods internationally, have significantly affected firms that rely on global markets for production inputs or product sales. The risk of trade disruptions has also increased with heightened geopolitical conflicts, such as the war in Ukraine and the growing tensions between the US and China. Inventories are critical for smoothing the impact of shocks.1 For instance, firms with high inventories of International Trade Dependence and Inventory Dynamics
{"title":"International Trade Dependence and Inventory Dynamics","authors":"Fernando Leibovici, Jason Dunn","doi":"10.20955/es.2023.17","DOIUrl":"https://doi.org/10.20955/es.2023.17","url":null,"abstract":"have been increasingly exposed to unexpected events or shocks originating from abroad. For instance, the COVID-19 pandemic and resulting supply-chain disruptions, including bottlenecks and increased costs for shipping goods internationally, have significantly affected firms that rely on global markets for production inputs or product sales. The risk of trade disruptions has also increased with heightened geopolitical conflicts, such as the war in Ukraine and the growing tensions between the US and China. Inventories are critical for smoothing the impact of shocks.1 For instance, firms with high inventories of International Trade Dependence and Inventory Dynamics","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90508239","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}
(FOMC) adopted a 2% inflation target. The inflation target they chose was based on the percentage change in the all-items (headline) personal consumption expenditures price index (PCEPI). The FOMC noted that deviations from the 2% target rate were likely in response to economic and financial developments, but that under appropriate monetary policy, inflation would average 2% over the longer run. In conventional models of inflation, the 2% inflation target rate—if credible—becomes a reasonable proxy for trend inflation and helps anchor long-run inflation expectations. Over time, then, under a credible monetary policy, headline inflation should converge to its long-run trend rate, which is primarily determined by the monetary authority. Thus, the FOMC attempts to measure trend inflation because it is a potentially useful guideline for predicting future inflation over the time horizon the FOMC cares about (typically 1 to 3 years). Many FOMC members view core PCEPI as an acceptable measure of trend inflation, as it excludes food and energy prices from the all-items PCEPI. Measures of “Trend” Inflation
{"title":"Measures of “Trend” Inflation","authors":"Kevin L. Kliesen","doi":"10.20955/es.2023.7","DOIUrl":"https://doi.org/10.20955/es.2023.7","url":null,"abstract":"(FOMC) adopted a 2% inflation target. The inflation target they chose was based on the percentage change in the all-items (headline) personal consumption expenditures price index (PCEPI). The FOMC noted that deviations from the 2% target rate were likely in response to economic and financial developments, but that under appropriate monetary policy, inflation would average 2% over the longer run. In conventional models of inflation, the 2% inflation target rate—if credible—becomes a reasonable proxy for trend inflation and helps anchor long-run inflation expectations. Over time, then, under a credible monetary policy, headline inflation should converge to its long-run trend rate, which is primarily determined by the monetary authority. Thus, the FOMC attempts to measure trend inflation because it is a potentially useful guideline for predicting future inflation over the time horizon the FOMC cares about (typically 1 to 3 years). Many FOMC members view core PCEPI as an acceptable measure of trend inflation, as it excludes food and energy prices from the all-items PCEPI. Measures of “Trend” Inflation","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"148 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88650428","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}
economic well-being of an individual or household. Although the likelihood of receiving a high income or owning a home increases throughout a person’s life, there has been a fair deal of anecdotal evidence suggesting that Millennials and Generation Z (those born after 1980) are already struggling economically compared with their parents’ generations. In this essay, I examine the life-cycle patterns of income and homeownership for different generations. Along the way, I find that comparing the experiences of non-college-educated and college-educated workers helps shed light onto these different generational patterns and how incomes and homeownership are linked. I use data from the American Community Survey (ACS), which the Census Bureau has run annually since 2000 and every 10 years prior to that. Importantly, the ACS has information on income, employment status, homeownership status, and demographics for a representative sample of the population. I focus on individuals whose incomes reflect full-time earnings over an entire year,1 from 1950 through 2021. All incomes are converted to 2019 dollars. I consider someone a homeowner if they own the housing unit they live in and are the head of household or spouse of the head of household. Finally, I categorize people by Generational Gaps in Income and Homeownership
{"title":"Generational Gaps in Income and Homeownership","authors":"Victoria Gregory","doi":"10.20955/es.2023.15","DOIUrl":"https://doi.org/10.20955/es.2023.15","url":null,"abstract":"economic well-being of an individual or household. Although the likelihood of receiving a high income or owning a home increases throughout a person’s life, there has been a fair deal of anecdotal evidence suggesting that Millennials and Generation Z (those born after 1980) are already struggling economically compared with their parents’ generations. In this essay, I examine the life-cycle patterns of income and homeownership for different generations. Along the way, I find that comparing the experiences of non-college-educated and college-educated workers helps shed light onto these different generational patterns and how incomes and homeownership are linked. I use data from the American Community Survey (ACS), which the Census Bureau has run annually since 2000 and every 10 years prior to that. Importantly, the ACS has information on income, employment status, homeownership status, and demographics for a representative sample of the population. I focus on individuals whose incomes reflect full-time earnings over an entire year,1 from 1950 through 2021. All incomes are converted to 2019 dollars. I consider someone a homeowner if they own the housing unit they live in and are the head of household or spouse of the head of household. Finally, I categorize people by Generational Gaps in Income and Homeownership","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"289 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79435450","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}
ments on their credit cards become delinquent. And companies routinely use credit scores to predict a borrower’s likelihood of delinquency or default. American borrowers maintained unusually low default rates throughout the COVID-19 recession and subsequent recovery likely because of several factors, including forbearance programs, limited spending during lockdowns, and substantial government subsidies. As a result, credit scores increased considerably in 2020 and 2021. Credit card delinquencies, on the other hand, began to rise at the end of 2021. This essay sheds light on the relationship between rising credit scores and subsequent increases in credit card delinquencies. We use data from the Federal Reserve Bank of New York/ Equifax Consumer Credit Panel to compute, for every quarter, the share of the US population 20 to 64 years of age whose credit score was below 600 three years ago but was above 600 one year ago. We refer to this group as “people who have recently improved their credit score.” We focus on this group because it allows us to investigate, for example, the delinquency status in 2022 of individuals who improved their credit scores between 2019 and 2021. We next use information from Athreya, Mather, Mustredel-Río, and Sánchez (2019) to categorize US zip codes based on how frequently households experience financial distress.1 The 20% of the population living in US zip codes with the greatest percentage of credit card delinquency is the group we refer to as the “most financially distressed zip codes.” We focus on this sample of zip codes because the authors found that residents in regions of greater financial distress are more adversely affected by economic downturns and react more by reducing their consumption. Figure 1 shows that the most significant increase in the share of people who have recently improved their credit score occurs between the second quarter of 2021 and the fourth quarter of 2022. Because we’re comparing scores from three years ago with those from one year ago, this rise corresponds to people who achieved a score of 600 or higher between the second quarter of 2020 and the fourth The Role of Credit Scores in the Recent Rise in Credit Card Delinquency
{"title":"The Role of Credit Scores in the Recent Rise in Credit Card Delinquency","authors":"Juan M. Sánchez, Masataka Mori","doi":"10.20955/es.2023.20","DOIUrl":"https://doi.org/10.20955/es.2023.20","url":null,"abstract":"ments on their credit cards become delinquent. And companies routinely use credit scores to predict a borrower’s likelihood of delinquency or default. American borrowers maintained unusually low default rates throughout the COVID-19 recession and subsequent recovery likely because of several factors, including forbearance programs, limited spending during lockdowns, and substantial government subsidies. As a result, credit scores increased considerably in 2020 and 2021. Credit card delinquencies, on the other hand, began to rise at the end of 2021. This essay sheds light on the relationship between rising credit scores and subsequent increases in credit card delinquencies. We use data from the Federal Reserve Bank of New York/ Equifax Consumer Credit Panel to compute, for every quarter, the share of the US population 20 to 64 years of age whose credit score was below 600 three years ago but was above 600 one year ago. We refer to this group as “people who have recently improved their credit score.” We focus on this group because it allows us to investigate, for example, the delinquency status in 2022 of individuals who improved their credit scores between 2019 and 2021. We next use information from Athreya, Mather, Mustredel-Río, and Sánchez (2019) to categorize US zip codes based on how frequently households experience financial distress.1 The 20% of the population living in US zip codes with the greatest percentage of credit card delinquency is the group we refer to as the “most financially distressed zip codes.” We focus on this sample of zip codes because the authors found that residents in regions of greater financial distress are more adversely affected by economic downturns and react more by reducing their consumption. Figure 1 shows that the most significant increase in the share of people who have recently improved their credit score occurs between the second quarter of 2021 and the fourth quarter of 2022. Because we’re comparing scores from three years ago with those from one year ago, this rise corresponds to people who achieved a score of 600 or higher between the second quarter of 2020 and the fourth The Role of Credit Scores in the Recent Rise in Credit Card Delinquency","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135501521","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}
over in the US was 8.2%. By 2019, that proportion had increased to 15.8%. In 2017, the US Census projected that by 2034 the population of people 65+ will be larger than the population of people under 18.1 US Commerce Secretary Gina Raimondo commented that aging demographics were going to hit the country “like a ton of bricks.”2 Vespa (2018) predicts greater demand for healthcare, in-home caregiving, and assisted living facilities, as well as problems for social security. The age distribution of the population is affected by the birth rate, death rate, and net migration rate. If the inflow of immigrants exceeds the outflow, and if immigrants are on average younger than citizens, then the population would get younger. Similarly, higher birth rates imply that the population will get younger. Much of the discussion on US population aging has been on birth rates and immigration (Howard, 2019; Murray, 2021; and Williams, 2020). We focus on the effect of death rates on the increased average age of the US population. From 1950 to 2019, the death rate, calculated as the number of people per 1,000 who die each year divided by How the Death Rate Affects the Aging of the US Population
{"title":"How the Death Rate Affects the Aging of the US Population","authors":"B. Ravikumar, Iris Arbogast","doi":"10.20955/es.2023.8","DOIUrl":"https://doi.org/10.20955/es.2023.8","url":null,"abstract":"over in the US was 8.2%. By 2019, that proportion had increased to 15.8%. In 2017, the US Census projected that by 2034 the population of people 65+ will be larger than the population of people under 18.1 US Commerce Secretary Gina Raimondo commented that aging demographics were going to hit the country “like a ton of bricks.”2 Vespa (2018) predicts greater demand for healthcare, in-home caregiving, and assisted living facilities, as well as problems for social security. The age distribution of the population is affected by the birth rate, death rate, and net migration rate. If the inflow of immigrants exceeds the outflow, and if immigrants are on average younger than citizens, then the population would get younger. Similarly, higher birth rates imply that the population will get younger. Much of the discussion on US population aging has been on birth rates and immigration (Howard, 2019; Murray, 2021; and Williams, 2020). We focus on the effect of death rates on the increased average age of the US population. From 1950 to 2019, the death rate, calculated as the number of people per 1,000 who die each year divided by How the Death Rate Affects the Aging of the US Population","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78401912","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":"From Ye Olde Stagnation to Modern Growth in England","authors":"Guillaume Vandenbroucke","doi":"10.20955/es.2023.3","DOIUrl":"https://doi.org/10.20955/es.2023.3","url":null,"abstract":"","PeriodicalId":11402,"journal":{"name":"Economic Synopses","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87492463","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}
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