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<title>Federal Reserve Bank of Cleveland publications</title>
<description>Economic research and commentary from Federal Reserve Bank of Cleveland</description>
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<pubDate>Thu, 16 Jul 2026 11:08:51 +0000</pubDate>
<item>
<title>What Share of Unemployed People in Fourth District States Receive Unemployment Insurance?</title>
<link>https://fedinprint.org/item/c00034/103500</link>
<description>
<![CDATA[Unemployment insurance recipiency rates vary considerably across Fourth District states, namely Ohio, Kentucky, Pennsylvania, and West Virginia. This article examines these recipiency rates and the factors that may influence them.]]>
</description>
<guid>https://fedinprint.org/item/c00034/103500</guid>
<dc:creator>Fee, Kyle</dc:creator>
<dc:date>2026-07-01</dc:date>
<identifiers:doi>10.26509/frbc-cd-20260701</identifiers:doi>
<bibo:series>Community Development Publications</bibo:series>
</item>
<item>
<title>Changes in Wage Gaps over Forty Years in the United States</title>
<link>https://fedinprint.org/item/fedcec/103471</link>
<description>
<![CDATA[This Economic Commentary explores the evolution of wage gaps between white and Black and white and Hispanic workers in the United States from 1980 to 2022. It analyzes wage gaps at various percentiles of the wage distribution and decomposes them to identify the factors driving changes over time. The findings reveal that while the gap between wages for white individuals and for Black men has narrowed at the 20th and 50th percentiles, it has expanded elsewhere, with the most significant widening occurring at the 80th percentile, particularly for Hispanic workers.&nbsp;Differences in educational attainment and occupations are the key factors that explain the observed wage gap trends.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103471</guid>
<dc:creator>Dicandia, Vittoria</dc:creator>
<dc:date>2026-06-29</dc:date>
<identifiers:doi>10.26509/frbc-ec-202614</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>SORCE Insights: The Relationship between Costs and Prices</title>
<link>https://fedinprint.org/item/c00003/103417</link>
<description>
<![CDATA[Based on responses to the Cleveland Fed's Survey of Regional Conditions and Expectations (SORCE), this District Data Brief analyzes the relationship between expected changes in costs and prices among firms in the Fourth District, which covers Ohio, western Pennsylvania, eastern Kentucky, and the northern panhandle of West Virginia.]]>
</description>
<guid>https://fedinprint.org/item/c00003/103417</guid>
<dc:creator>Dunn, Julianne E.; Huettner, Brett</dc:creator>
<dc:date>2026-06-23</dc:date>
<identifiers:doi>10.26509/frbc-ddb-20260623</identifiers:doi>
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</item>
<item>
<title>How Much Nonbank Business Lending Is Indirectly Funded by Banks? Some Evidence from a New Data Set</title>
<link>https://fedinprint.org/item/fedcec/103411</link>
<description>
<![CDATA[Bank lending to the nonfinancial business sector in the United States has declined in recent decades, accompanied by an increase in credit provision by nonbank financial institutions (NBFIs). At the same time, banks are important providers of funding to the NBFI sector, raising concerns over their exposure to the risk in loans made by NBFIs. This Economic Commentary uses the Federal Reserve’s novel issuer-to-holder data, part of the enhanced financial accounts of the United States, to provide a conservative estimate of the share of lending by NBFIs to nonfinancial businesses that is indirectly financed by the banking sector. Using this method, I find that the additional indirect exposure of banks to business loans through this specific channel has been stable at about 5 percent to 6 percent of all business sector loans over the past 20 years. This share is small when compared to the share of business lending that banks provide directly and does not fully compensate for the decline since 1980 in the share of business lending that banks do directly.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103411</guid>
<dc:creator>Siedlarek, Jan-Peter</dc:creator>
<dc:date>2026-06-22</dc:date>
<rdau:hasExtent>10</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>13</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202613</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>It Takes Two to Make an Economy Go Right</title>
<link>https://fedinprint.org/item/fedcsp/103374</link>
<description>
<![CDATA[A conversation with President Beth Hammack held at the City Club of Cleveland, Cleveland, Ohio on Tuesday, June 2, 2026. ]]>
</description>
<guid>https://fedinprint.org/item/fedcsp/103374</guid>
<dc:creator>Hammack, Beth</dc:creator>
<dc:date>2026-06-02</dc:date>
<rdau:hasExtent>7</rdau:hasExtent>
<bibo:series>Speech</bibo:series>
</item>
<item>
<title>BLS Benchmark Revisions: Is This Time Different?</title>
<link>https://fedinprint.org/item/fedcec/103357</link>
<description>
<![CDATA[In this Economic Commentary, we discuss the Bureau of Labor Statistics’ (BLS) payroll benchmark revisions, the role of these revisions, BLS methodology, and recent time series. While we do see some large benchmark revisions in recent years, these revisions are not big enough to indicate that something structural about the series has changed. Finally, considering a time series from 2010 through 2025, we find that past benchmark revisions have information that may help predict future revisions.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103357</guid>
<dc:creator>Pinheiro, Roberto; Quinlan, Rory G.</dc:creator>
<dc:date>2026-06-03</dc:date>
<rdau:hasExtent>11</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>12</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202612</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>A Nonparametric Approach to Augmenting a Bayesian VAR with Nonlinear Factors</title>
<link>https://fedinprint.org/item/fedcwq/103355/original</link>
<description>
<![CDATA[This paper proposes a vector autoregression augmented with nonlinear factors that are modeled nonparametrically using regression trees. There are four main advantages of our model. First, modeling potential nonlinearities nonparametrically lessens the risk of misspecification. Second, the use of factor methods ensures that departures from linearity are modeled parsimoniously. In particular, they exhibit functional pooling where a small number of nonlinear factors are used to model common nonlinearities across variables. Third, Bayesian computation using MCMC is straightforward even in very high-dimensional models, allowing for efficient, equation-by-equation estimation, thus avoiding computational bottlenecks that arise in popular alternatives such as the time-varying parameter VAR. Fourth, existing methods for identifying structural economic shocks in linear factor models can be adapted for the nonlinear case in a straightforward fashion using our model. Exercises involving artificial and macroeconomic data illustrate the properties of our model and its usefulness for forecasting and structural economic analysis.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/103355/original</guid>
<dc:creator>Huber, Florian; Clark, Todd E.; Koop, Gary</dc:creator>
<dc:date>2026-06-02</dc:date>
<rdau:hasExtent>40</rdau:hasExtent>
<dc:subject>Nonparametric VAR; nonlinear factor model; regression trees; macroeconomic forecasting; scenario analysis</dc:subject>
<swpo:hasNumber>26-14</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202614</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>SORCE Insights: Realized Tariff Impacts on Fourth District Firms</title>
<link>https://fedinprint.org/item/c00003/103345</link>
<description>
<![CDATA[The Cleveland Fed’s Survey of Regional Conditions and Expectations (SORCE) fielded from May 7 through May 14, 2026, included a set of special questions focused mainly on the impacts of tariffs imposed under the International Emergency Economic Powers Act (IEEPA) from February 4, 2025, through February 20, 2026. This District Data Brief discusses the top-line results from these questions.]]>
</description>
<guid>https://fedinprint.org/item/c00003/103345</guid>
<dc:creator>Huettner, Brett; Isler, Mitchell</dc:creator>
<dc:date>2026-06-01</dc:date>
<identifiers:doi>10.26509/frbc-ddb-20260601</identifiers:doi>
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</ebucore:publicationChannel>
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<item>
<title>Nonresponse Imputations and Related Measurement Issues in the CPI for Shelter</title>
<link>https://fedinprint.org/item/fedcwq/103314/original</link>
<description>
<![CDATA[Shelter is the largest component of US consumer price index (CPI) inflation; therefore, the accuracy of shelter inflation is critical for the accuracy of overall CPI inflation. Nonresponse in the BLS Housing Survey, which underpins the measurement of CPI shelter inflation, has increased since 2000 and now represents roughly 40 percent of total observations. Missing rent data are currently imputed using a class-mean approach based on rent tier, potentially resulting in biased imputations, as we find that nonresponse is correlated with factors beyond rent tier. We study alternative simple imputation methods based on variables correlated with both nonresponse and rent growth, including structure type and tenure length. A simple model demonstrates that alternative methods could yield sharply different index biases. However, in practice, we find that these alternative methods yield similar shelter inflation indexes, suggesting that any index bias may be modest.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/103314/original</guid>
<dc:creator>Verbrugge, Randal J.; Loewenstein, Lara; Montag, Hugh</dc:creator>
<dc:date>2026-05-28</dc:date>
<rdau:hasExtent>43</rdau:hasExtent>
<dc:subject>inflation measurement; survey methodology; missing data; imputations</dc:subject>
<swpo:hasNumber>26-13</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202613</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>Sticky Rents: A Simple Implicit-Contracts Theory</title>
<link>https://fedinprint.org/item/fedcwq/103313/original</link>
<description>
<![CDATA[Shelter inflation, driven by continuing-tenant rents, accounts for one-third of the consumer price index (CPI). Yet continuing-tenant rent inflation, notoriously sticky, has attracted almost no theoretical attention. Standard sticky price theories cannot explain the basic facts. We provide a simple theory yielding implicit contracts as an equilibrium. The landlord will wish to renege when costs rise; reputation is unavailable to enforce the contract. A well-established mechanism serves: landlord off-equilibrium-path play might result in renter frustration and endogenous breakup. Our implicit-contracts theory gracefully explains nominal (rather than real) rigidity, and provides a microfounded explanation of key rental market facts.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/103313/original</guid>
<dc:creator>Verbrugge, Randal J.; Montag, Hugh</dc:creator>
<dc:date>2026-05-27</dc:date>
<rdau:hasExtent>35</rdau:hasExtent>
<dc:subject>continuing-tenant rent; inflation; frustration; customer anger; costly punishment</dc:subject>
<swpo:hasNumber>26-12</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202612</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>The (Re)Anchoring of US Firms’ Inflation Expectations</title>
<link>https://fedinprint.org/item/fedcec/103301</link>
<description>
<![CDATA[This Economic Commentary studies the degree of anchoring of US firms’ inflation expectations from 2018 to 2025 by leveraging a novel survey of firms’ medium-term inflation expectations and their subjective perceptions of the Federal Open Market Committee’s (FOMC) inflation objective. We capture unanchoring by measuring disagreement across firms’ expectations and the misalignment between the mean of firms’ expectations and the FOMC’s inflation objective. Based on our measure, the anchoring of firms’ medium-term inflation expectations weakened significantly during the pandemic inflation surge, driven largely by an increase in disagreement but also by firms’ subjective perceptions of the FOMC’s inflation objective’s temporarily deviating from 2 percent. While we find anchoring has significantly strengthened since 2022, it remained somewhat weaker during 2025 than the prepandemic average.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103301</guid>
<dc:creator>Reinelt, Timo; Cline, Alexander; Garciga, Christian; Hajdini, Ina; Rich, Robert W.</dc:creator>
<dc:date>2026-05-26</dc:date>
<rdau:hasExtent>7</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>11</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202611</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Unemployment Insurance Generosity and Wage Determination</title>
<link>https://fedinprint.org/item/fedcwq/103300/original</link>
<description>
<![CDATA[Using public-use data from the Current Population Survey, we estimate the effects of changes in unemployment insurance (UI) generosity on the wages of new hires from unemployment, job changers, and continuously employed workers. We find similar, modestly positive elasticities across all groups of workers. Posted wages respond similarly on average, but differences in distributional effects suggest that changes in wage posting are unlikely to fully explain the effects on realized wages. More generous UI also reduces hiring from unemployment and job-to-job transitions, reduces labor force exit, and increases the hiring of new labor force entrants and labor force non-participants.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/103300/original</guid>
<dc:creator>Wasser, David; Rinz, Kevin</dc:creator>
<dc:date>2026-05-26</dc:date>
<rdau:hasExtent>60</rdau:hasExtent>
<dc:subject>unemployment insurance; wages; wage posting; labor search</dc:subject>
<swpo:hasNumber>26-11</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202611</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>Fixing the Phillips Curve: Implications of Firms' Monopsonistic Wage-setting for Inflation Dynamics</title>
<link>https://fedinprint.org/item/fedcwq/103287/original</link>
<description>
<![CDATA[Motivated by evidence documented in labor economics, we introduce firms' monopsonistic wage-setting in an otherwise standard DSGE model. Our model identifies shocks to the wage markdown as labor demand shocks—a feature absent from standard models. With both labor demand and supply shocks, our model empirically outperforms its standard counterpart model. Firms' monopsonistic wage-setting allows real unit labor cost to be decomposed into not only real marginal cost but also the wage markdown. This refined measure of real marginal cost enhances the Phillips curve's ability to describe inflation dynamics while obviating the need for price markup shocks.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/103287/original</guid>
<dc:creator>Van Zandweghe, Willem; Kurozumi, Takushi</dc:creator>
<dc:date>2026-05-21</dc:date>
<rdau:hasExtent>43</rdau:hasExtent>
<dc:subject>DSGE model; Labor market monopsony; Wage markdown; Labor demand shock; Real marginal cost</dc:subject>
<swpo:hasNumber>26-10</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202610</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>Community Issues and Insights 2026: Housing Affordability and Inflation Remain Top Concerns</title>
<link>https://fedinprint.org/item/c00034/103267</link>
<description>
<![CDATA[The Federal Reserve Bank of Cleveland’s Community Issues Survey (CIS) collects information semiannually from direct service providers to monitor economic conditions and identify issues impacting low- and moderate-income (LMI) households in the Federal Reserve’s Fourth District, a region that includes Ohio, western Pennsylvania, eastern Kentucky, and the northern panhandle of West Virginia. From March 2 through 13, 2026, we surveyed more than 550 organizations that directly serve LMI individuals and communities across our District and received 108 responses (19 percent response rate). The results of this survey are summarized here and provide insights into how organizations and the households they serve are faring in today’s economy.]]>
</description>
<guid>https://fedinprint.org/item/c00034/103267</guid>
<dc:creator>Klesta, Matthew</dc:creator>
<dc:date>2026-05-19</dc:date>
<rdau:hasExtent>9</rdau:hasExtent>
<identifiers:doi>10.26509/frbc-cd-20260519</identifiers:doi>
<bibo:series>Community Development Publications</bibo:series>
</item>
<item>
<title>Do Group Unemployment Rates Send Warning Signs about the Broader Labor Market?</title>
<link>https://fedinprint.org/item/fedcec/103266</link>
<description>
<![CDATA[Labor market commentary often discusses unemployment rates for certain groups as potential leading indicators for the overall unemployment rate. I test that idea for several commonly mentioned groups, finding that increases in the unemployment rates for Black workers and workers who did not complete high school do predict higher overall unemployment in subsequent months. Though not commonly discussed in this context, increases in the unemployment rate for workers aged 35–44 also predict higher subsequent overall unemployment.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103266</guid>
<dc:creator>Rinz, Kevin</dc:creator>
<dc:date>2026-05-18</dc:date>
<rdau:hasExtent>5</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>10</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202610</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Expanding the Survey of Firms’ Inflation Expectations</title>
<link>https://fedinprint.org/item/fedcec/103189</link>
<description>
<![CDATA[The Survey of Firms’ Inflation Expectations (SoFIE) is a quarterly survey of chief executive officers and other top business executives in the United States that collects information about their inflation expectations. This Economic Commentary presents questions newly introduced to SoFIE—some related to inflation and others examining expectations for prices, costs, employment, and wages—and provides initial analysis of the collected responses. The expanded set of survey results will be updated on a quarterly basis on the Federal Reserve Bank of Cleveland’s website at clefed.org/SoFIE.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103189</guid>
<dc:creator>Pfajfar, Damjan; Candia, Bernardo; Hajdini, Ina; Knotek, Edward S.; Rich, Robert W.</dc:creator>
<dc:date>2026-05-11</dc:date>
<rdau:hasExtent>16</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>09</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202609</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Covered Savings Associations: A New Type of Depository Institution</title>
<link>https://fedinprint.org/item/fedcec/103116</link>
<description>
<![CDATA[The Economic Growth, Regulatory Relief, and Consumer Protection Act of 2018 allowed most federally chartered savings associations to elect to operate with the powers of a national bank, expanding their ability to engage in commercial banking activities and no longer requiring them to concentrate their activities in residential mortgage lending. This Economic Commentary describes which associations have made the election, their reasons for doing so, and how the election has changed their asset mix. Both mutual and stock savings associations have made this election, and among mutuals, large institutions are especially likely to have done so. Institutions that have made this election have altered their asset mix away from residential lending and toward that of similarly sized national banks.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103116</guid>
<dc:creator>Prescott, Edward Simpson; Rosenberger, Grant</dc:creator>
<dc:date>2026-05-04</dc:date>
<rdau:hasExtent>13</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>08</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202608</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>SORCE Insights: How Fourth District Firms Are Using AI</title>
<link>https://fedinprint.org/item/c00003/103088</link>
<description>
<![CDATA[The Cleveland Fed’s latest edition of the Survey of Regional Conditions and Expectations (SORCE), administered from March 19 to 26, 2026, included a set of special questions focused on the use of artificial intelligence among Fourth District firms. This District Data Brief discusses the top-line results from these questions.]]>
</description>
<guid>https://fedinprint.org/item/c00003/103088</guid>
<dc:creator>Isler, Mitchell; Huettner, Brett</dc:creator>
<dc:date>2026-04-15</dc:date>
<identifiers:doi>10.26509/frbc-ddb-20260415</identifiers:doi>
<ebucore:publicationChannel>
</ebucore:publicationChannel>
</item>
<item>
<title>Beyond Investment: How CDFIs Support Community and Economic Development in Low- and Moderate-Income Areas</title>
<link>https://fedinprint.org/item/c00034/103087</link>
<description>
<![CDATA[Community development financial institutions (CDFIs) support low- and moderate-income areas by providing not only investment, but also technical assistance, capacity building, financial coaching, and more. Drawing on transaction-level investment data and interviews with CDFI loan funds from across the Fourth Federal Reserve District, this report examines how these mission-driven organizations play a key role in community and economic development.]]>
</description>
<guid>https://fedinprint.org/item/c00034/103087</guid>
<dc:creator>Piazza, Merissa</dc:creator>
<dc:date>2026-04-14</dc:date>
<rdau:hasExtent>11</rdau:hasExtent>
<identifiers:doi>10.26509/frbc-cd-20260414</identifiers:doi>
<bibo:series>Community Development Publications</bibo:series>
</item>
<item>
<title>The Effect of Size Thresholds on Large Banks under the 2019 Tailoring Framework</title>
<link>https://fedinprint.org/item/fedcec/103024</link>
<description>
<![CDATA[Federal bank regulators finalized a tailoring framework for large-bank regulation in 2019. Among other provisions, the 2019 tailoring framework replaced a single category of large banks above $50 billion in total assets with four new categories for prudential regulation separated by size thresholds. Compared to the 2010 Dodd–Frank Act, the 2019 tailoring framework phased in large-bank regulations incrementally, adding a smaller set of changes at each threshold instead of all at once at $50 billion. This Economic Commentary analyzes the effect of this change in banking regulation during the 2016 through 2023 period. It finds that the new framework reduced bunching of banks just below the $50 billion in total assets threshold, which was removed from the regulation. At the same time, there is evidence of banks’ bunching just below $100 billion and $250 billion in total assets, two of the newly introduced thresholds under the new framework. Such bunching suggests that the 2019 tailoring framework imposed some regulatory costs on banks at each threshold as regulations became incrementally stricter, as intended by the framework. It does not, however, appear to have prevented bank growth outright. Indeed, the data show that multiple banks grew beyond their applicable size threshold after the new framework was implemented.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/103024</guid>
<dc:creator>Siedlarek, Jan-Peter; Wang, Isabella</dc:creator>
<dc:date>2026-04-13</dc:date>
<rdau:hasExtent>11</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>07</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202607</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Reconciling Recent Strong Output Growth with Rising Unemployment</title>
<link>https://fedinprint.org/item/fedcec/102953</link>
<description>
<![CDATA[Over the last three years, robust GDP growth alongside comparatively weak labor market data on jobs and unemployment has presented a puzzle to policymakers and analysts. This disconnect shows up as elevated labor productivity growth and an unemployment rate that has risen despite robust GDP growth, violating the usual inverse relationship known as Okun’s law. We show that these data may be less puzzling than they appear. Historical revision patterns provide no evidence that recent productivity gains will be revised away. And once we account for lagged effects, the comovements of recent GDP and unemployment rate data are consistent with historical patterns.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/102953</guid>
<dc:creator>Jacobs, Dylan C.; Krolikowski, Pawel</dc:creator>
<dc:date>2026-03-30</dc:date>
<rdau:hasExtent>9</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>06</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202606</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Immigration and the Unemployment Rate in 2023–2024</title>
<link>https://fedinprint.org/item/fedcec/102935</link>
<description>
<![CDATA[The increase in the US unemployment rate observed from early 2023 until late 2024 primarily reflected a decline in the job-finding rate. Using the share of noncitizens in the US labor market as a measure of immigration, this Economic Commentary evaluates two mechanisms through which a higher share of noncitizens coming from post-pandemic immigration could hypothetically affect the job-finding rate. First, noncitizens may have systematically lower job-finding rates than citizens. Second, during slowdowns, noncitizens’ job-finding and other transition rates may deteriorate more rapidly and extensively than those of US citizens. Evaluating both mechanisms, we find no evidence that the higher share of noncitizens in the labor market contributed to the rise in the unemployment rate during 2023 and 2024.]]>
</description>
<guid>https://fedinprint.org/item/fedcec/102935</guid>
<dc:creator>Panzitta, Geena; Hernandez Martinez, Victor</dc:creator>
<dc:date>2026-03-25</dc:date>
<rdau:hasExtent>8</rdau:hasExtent>
<bibo:volume>2026</bibo:volume>
<bibo:issue>05</bibo:issue>
<identifiers:doi>10.26509/frbc-ec-202605</identifiers:doi>
<bibo:series>Economic Commentary</bibo:series>
</item>
<item>
<title>Technological Change and Racial Wage Gaps</title>
<link>https://fedinprint.org/item/fedcwq/102932/original</link>
<description>
<![CDATA[The wage gap between Black and white Americans narrowed in the 1960s-1970s but stagnated after 1980. This study argues that routine-biased technological change (RBTC) contributed to this stagnation by affecting Black and white male workers differently across the wage distribution. Using new empirical evidence on occupational patterns and wage determinants for these workers, I rationalize these patterns with a novel RBTC theoretical framework. Contrary to expectations, Black workers' employment in routine-intensive occupations increased, while white workers experienced a significant decline. Applying the Oaxaca-RIF decomposition, I show that occupational sorting amplifies wage gaps, particularly at the lower end of the wage distribution. These findings, interpreted through the novel theoretical framework, offer new insights into the mechanisms driving racial wage gaps at the close of the twentieth century.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/102932/original</guid>
<dc:creator>Dicandia, Vittoria</dc:creator>
<dc:date>2026-03-25</dc:date>
<rdau:hasExtent>47</rdau:hasExtent>
<dc:subject>technological change; wage differentials</dc:subject>
<swpo:hasNumber>26-09</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202609</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>A New Model of Trend Inflation Using Disaggregates, Survey Expectations, and Uncertainty</title>
<link>https://fedinprint.org/item/fedcwq/102922/original</link>
<description>
<![CDATA[This paper develops a new empirical model that estimates trend inflation by combining modeling features that have advanced the literature on trend inflation over the past two decades. These features include incorporating information about long-term inflation expectations from surveys in a flexible way, modeling aggregate inflation via sectoral data (goods and services), allowing for stochastic volatility (SV) in the shocks to the trend and transitory components of inflation, allowing for a time-varying price Phillips curve, and allowing for time-varying uncertainty effects on the level of inflation. We estimate the model using state-of-the-art Bayesian methods. We document the competitive properties of the new model compared to variants that include only a subset of the above features. The new model provides a more interpretable historical decomposition of inflation data than the models it extends. The decomposition suggests that uncertainty effects play a greater role than cyclical effects in explaining inflation fluctuations.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/102922/original</guid>
<dc:creator>Tallman, Ellis W.; Zaman, Saeed</dc:creator>
<dc:date>2026-03-24</dc:date>
<rdau:hasExtent>47</rdau:hasExtent>
<dc:subject>disaggregates of inflation; inflation uncertainty; trend inflation; inflation expectations; nonlinear state space; Bayesian methods</dc:subject>
<swpo:hasNumber>26-08</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202608</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
<item>
<title>Optimal Short-Time Work Policy in Recessions</title>
<link>https://fedinprint.org/item/fedcwq/102917/original</link>
<description>
<![CDATA[Short-time work (STW) is a subsidy program linked to a reduction in working hours that has been widely used across Europe and partly used in some US states to combat job losses in the Great Recession and the COVID-19 pandemic. Although typically used alongside an unemployment insurance (UI) system, the interaction between STW and UI remains conceptually unclear. To close this gap in the literature, I develop a search and matching model of the labor market with risk-averse workers, flexible hours choice, endogenous separations, and generalized Nash bargaining. Deriving closed-form expressions for the optimal policy mix, I demonstrate that while the UI system provides income insurance to workers, the STW system mitigates the fiscal externality of UI-induced separations. Notably, STW only exists due to the UI system. Consistent with often observed policy practice, I allow the STW system to adjust over the business cycle while keeping the UI system constant. In line with the actual policy, my findings indicate that optimal STW benefits have to increase in recessions, while in contrast to the actual policy, optimal eligibility criteria have to be tightened. Using UI with an optimal STW system is fiscally less expensive than the UI system on its own.]]>
</description>
<guid>https://fedinprint.org/item/fedcwq/102917/original</guid>
<dc:creator>Stiepelmann, Gero</dc:creator>
<dc:date>2026-03-23</dc:date>
<rdau:hasExtent>126</rdau:hasExtent>
<dc:subject>Short-time work; unemployment insurance; optimal policy; labor markets; search and matching; business cycles</dc:subject>
<swpo:hasNumber>26-07</swpo:hasNumber>
<identifiers:doi>10.26509/frbc-wp-202607</identifiers:doi>
<bibo:series>Working Papers</bibo:series>
</item>
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</rss>