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<title>Federal Reserve Bank of Atlanta publications</title>
<description>Economic research and commentary from Federal Reserve Bank of Atlanta</description>
<link>https://fedinprint.org/search?facets[]=provider_literal_array:Federal+Reserve+Bank+of+Atlanta</link>
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<pubDate>Fri, 10 Jul 2026 13:50:35 +0000</pubDate>
<item>
<title>Innovation Booms, Easy Financing, and Human Capital Accumulation</title>
<link>https://fedinprint.org/item/fedawp/103489/original</link>
<description>
<![CDATA[Innovation booms are often fueled by easy financing, allowing new technology firms to pay high wages that attract skilled labor. Studying the information and communication technology (ICT) boom in the late 1990s, we show that high-skill workers who joined the ICT sector during the boom experienced sizeable long-term earnings losses. These earnings patterns stem from accelerated skill obsolescence rather than worker selection or the subsequent bust in the ICT sector. Moreover, during the boom, financing disproportionately flowed to firms whose workers would later experience the largest productivity declines, amplifying the negative effect of labor reallocation on aggregate human capital accumulation.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/103489/original</guid>
<dc:creator>Hombert, Johan; Matray, Adrien</dc:creator>
<dc:date>2026-07-06</dc:date>
<rdau:hasExtent>85</rdau:hasExtent>
<dc:subject>innovation; human capital; financing</dc:subject>
<swpo:hasNumber>2026-8</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-08</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Patents to Products: Product Innovation and Firm Dynamics</title>
<link>https://fedinprint.org/item/fedawp/101775/original</link>
<description>
<![CDATA[We combine NielsenIQ scanner data with USPTO patent records and apply natural language processing to match detailed product descriptions to patent texts for the consumer goods sector. We show that while more than half of product innovations originate from non-patenting firms, patent filings are on average followed by subsequent product introductions. Yet this relationship weakens with firm size. Patents held by market leaders also yield revenue premiums beyond what can be explained by their own product introductions and are associated with stronger deterrence of competitors’ innovations. To interpret these findings, we develop a simple growth model in which larger firms have stronger incentives to engage in strategic patenting—filing for protection rather than market innovation—which dampens innovation and slows creative destruction.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101775/original</guid>
<dc:creator>Hanley, Douglas; Moreira, Sara; Argente, David; Baslandze, Salomé</dc:creator>
<dc:date>2020-04-17</dc:date>
<rdau:hasExtent>105</rdau:hasExtent>
<dc:subject>innovation; products; strategic patents; creative destruction; competition; growth</dc:subject>
<swpo:hasNumber>2020-4a</swpo:hasNumber>
<identifiers:doi>10.29338/wp2020-04</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>The Anatomy of Polarization: Evidence from Worker Flows</title>
<link>https://fedinprint.org/item/fedawp/103416/original</link>
<description>
<![CDATA[Using longitudinal French administrative data (1984–2021), we document that employment polarization after 1994 reflects major changes in labor-market entry rather than mass occupational downgrading or displacement of incumbents. Flows from routine to abstract occupations remain substantial throughout the period, and a large fraction of these upgrades is due to noncollege workers. The decisive shift that generates polarization occurs at the entry margin: the net flow from nonemployment into routine occupations reverses around 1994, while the net flow from nonemployment into manual work increases. These patterns motivate life-cycle models of occupational choice that explicitly incorporate cohort heterogeneity and separate entry and re-entry margins.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/103416/original</guid>
<dc:creator>Dienesch, Elisa; Monge-Naranjo, Alexander; Moro, Alessio; Cerina, Fabio</dc:creator>
<dc:date>2026-06-22</dc:date>
<rdau:hasExtent>58</rdau:hasExtent>
<dc:subject>labor market polarization; worker flows; occupational mobility; routine-based technological change; longitudinal data</dc:subject>
<swpo:hasNumber>2026-7</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-07</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Automation, Learning, and Career Dynamics</title>
<link>https://fedinprint.org/item/fedawp/103253/original</link>
<description>
<![CDATA[We study how an automating technology affects career dynamics, human capital, and welfare in an economy where workers acquire skill through the tasks they perform. In a continuous-time general equilibrium model, learning-by-doing is determined jointly with the share of tasks automated, the frontier of tasks managers maintain, and the worker-to-manager career transition. Economies with high learning capacity admit pairs of stationary equilibria strictly ranked by the aggregate learning rate. Cheaper technology has opposite effects across the two: in the high-learning equilibrium, it raises welfare through the learning channel itself; in the low-learning equilibrium, it tips the economy into a human-capital trap. The planner's first-best combines a tax on automation profits with a subsidy on frontier maintenance expenditures at a common rate.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/103253/original</guid>
<dc:creator>Drenik, Andres; Afrouzi, Hassan; Blanco, Andres; Hurst, Erik</dc:creator>
<dc:date>2026-05-14</dc:date>
<rdau:hasExtent>59</rdau:hasExtent>
<dc:subject>human capital; learning-by-doing; automation; AI</dc:subject>
<swpo:hasNumber>2026-6</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-06</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>What's Behind Declining Birth Rates in the U.S.?</title>
<link>https://fedinprint.org/item/fedawp/103252/original</link>
<description>
<![CDATA[Using the National Survey of Family Growth, this paper explores reasons behind the falling birth rate in the United States. The analysis confirms that newer generations of women are less likely to have any children than generations that came before. Comparing outcomes among women at the same age, two sources for this decline are identified: (1) a dramatic decrease in the desire to have children, but only among the youngest generation in the sample (Gen Z) and (2) an increase in the medical difficulty of having children among all generations of women since the Boomer generation. Various policies addressing both desire and difficulties are discussed in the context of a goal to arrest or reverse declining birth rates. The primary contribution of this paper is consideration of increasing medical difficulty in conceiving and bearing children (impaired fecundity) alongside the current dominant theory of shifting priorities and preferences of recent cohorts of women.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/103252/original</guid>
<dc:creator>Hotchkiss, Julie L.; Bradley, Allen; Bradley, Lila Newberry; Ostle, Clare; Partey, Deborah</dc:creator>
<dc:date>2026-05-13</dc:date>
<rdau:hasExtent>45</rdau:hasExtent>
<dc:subject>birth rates; total fertility rates; infertility; impaired fecundity; microplastic; IVF; family formation; Gen Z; cohorts</dc:subject>
<swpo:hasNumber>2026-5</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-05</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>What Enrollment Numbers Can (and Cannot) Tell Us About Access to Postsecondary Training Programs</title>
<link>https://fedinprint.org/item/a00034/103068</link>
<description>
<![CDATA[While there has been some debate over the value of college, workers and employers still perceive credentials as important for employability. 1 Postsecondary education, or "formal learning opportunities beyond high school,"2 is linked to greater labor force participation, higher employment rates, and increased individual economic success.3 Access to postsecondary training, however, remains an issue.

To better understand postsecondary access, in this Workforce Currents we analyze available enrollment data from the National Center for Education Statistics' (NCES) Integrated Postsecondary Education Data System (IPEDS). Enrollment data is one way to examine learners' access to various institutions. We review enrollment demographics of US postsecondary institutions of varying types, including two-year public (or community college) and not-for-profit private and public four-year, to better understand enrollment demographics.4 These institutional types represent roughly half of IPEDS' undergraduate enrollments. We also analyzed novel data from SkillUp Coalition, a nonprofit that serves as a career navigation platform for job training and career opportunities, that provides an illustration of specific learner subsets interested in or enrolled in non-degree postsecondary programs.]]>
</description>
<guid>https://fedinprint.org/item/a00034/103068</guid>
<dc:creator>Horton, Tiffani; Simpson, Elizabeth Bogue; Walker, Jacob</dc:creator>
<dc:date>2026-04-08</dc:date>
<rdau:hasExtent>14</rdau:hasExtent>
<swpo:hasNumber>2</swpo:hasNumber>
<identifiers:doi>10.29338/wc2026-02</identifiers:doi>
<bibo:series>Workforce Currents</bibo:series>
</item>
<item>
<title>How Long Will the Relief Check Last?</title>
<link>https://fedinprint.org/item/fedaes/103066</link>
<guid>https://fedinprint.org/item/fedaes/103066</guid>
<dc:creator>Chien, YiLi</dc:creator>
<dc:date>2020-04-06</dc:date>
<bibo:series>EconSouth</bibo:series>
</item>
<item>
<title>Atlanta Fed Analysis of Jacksonville Job Market Reveals Regional Conditions</title>
<link>https://fedinprint.org/item/a00034/102977</link>
<description>
<![CDATA[Fulfilling the Federal Reserve System's dual mandate of price stability and full employment requires a thorough understanding of the economy, both in the national and local context. At the Atlanta Fed, we closely monitor the labor market through both our Community and Economic Development (CED) team that focuses on research and engagement that aims to improve economic opportunity for low- and moderate-income individuals (LMI) and our Regional Economic Information Network (REIN) team that gathers economic intelligence from business leaders.1 Recently, we leveraged the complementary capabilities of CED and REIN to engage local businesses, workforce development professionals, social services system administrators, and individual workers and job seekers for a 360-degree labor market analysis in one of the most dynamic economies in the Southeast—Jacksonville, Florida.]]>
</description>
<guid>https://fedinprint.org/item/a00034/102977</guid>
<dc:creator>Dennard, Michelle; Miller, Sarah; Rees, John</dc:creator>
<dc:date>2026-03-31</dc:date>
<rdau:hasExtent>7</rdau:hasExtent>
<swpo:hasNumber>2026-1</swpo:hasNumber>
<identifiers:doi>10.29338/wc2026-01</identifiers:doi>
<bibo:series>Workforce Currents</bibo:series>
</item>
<item>
<title>Fiat-Backed Stablecoins and Narrow Banking</title>
<link>https://fedinprint.org/item/a00068/102974</link>
<description>
<![CDATA[Devastated by the misery of millions of people during the Great Depression caused by the collapse of the entire US financial system, a group of economists at the University of Chicago sought to reform the banking sector. The "Chicago plan" suggested a replacement of "fractional-reserve banks" with "full-reserve banks" (also called "narrow banks" and "limited-purpose banks"). Most economists dismiss this idea. However, the rising popularity of stablecoins and the 2025 GENIUS Act in the US introduce this form of banking to the general public. The goal of this note is to analyze the similarities and differences between the narrow banking proposal and the fast-growing fiat-backed stablecoins.]]>
</description>
<guid>https://fedinprint.org/item/a00068/102974</guid>
<dc:creator>Shy, Oz</dc:creator>
<dc:date>2026-03-31</dc:date>
<rdau:hasExtent>12</rdau:hasExtent>
<dc:subject>fiat-backed stablecoins; narrow banking; full-reserve banks; limited-purpose banks; GENIUS Act</dc:subject>
<bibo:volume>2026</bibo:volume>
<bibo:issue>2</bibo:issue>
<identifiers:doi>10.29338/ph2026-02</identifiers:doi>
<bibo:series>Policy Hub</bibo:series>
</item>
<item>
<title>Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives</title>
<link>https://fedinprint.org/item/fedawp/102936/original</link>
<description>
<![CDATA[We use novel data from a survey of nearly 750 corporate executives to study the effects of artificial intelligence (AI) on productivity and the workforce. We document substantial heterogeneity in AI adoption across firms, with more than half having already invested, though many smaller firms are only beginning to do so. Labor productivity gains are positive, vary across sectors, and are expected to strengthen in 2026, with the largest effects concentrated in high-skill services and finance. These gains are not primarily driven by firms' capital deepening but instead reflect increases in revenue-based total factor productivity, closely associated with innovation- and demand-oriented channels. We document a productivity paradox, in which perceived productivity gains are larger than measured productivity gains, likely reflecting a delay in revenue realizations. In labor markets, we find little evidence of near-term aggregate employment declines due to AI, though larger companies anticipate AI-driven workforce reductions, while smaller firms expect modest gains. We also find evidence of compositional reallocation of labor both within and across firms, with routine clerical roles declining and a relative demand for skilled technical roles increasing. We develop an index that ranks job functions most negatively affected by AI.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/102936/original</guid>
<dc:creator>Waddell, Sonya Ravindranath; Baslandze, Salomé; Edwards, Zach; Graham, John; McClure, Ty; Sparks, Michael; Meyer, Brent; Weitz, Daniel J.</dc:creator>
<dc:date>2026-03-25</dc:date>
<rdau:hasExtent>56</rdau:hasExtent>
<dc:subject>artificial intelligence; productivity; technological change; labor markets; occupations</dc:subject>
<swpo:hasNumber>2026-04</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-04</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Firm Data on AI</title>
<link>https://fedinprint.org/item/fedawp/102928/original</link>
<description>
<![CDATA[We present the first representative international data on firm-level AI use. We survey almost 6,000 CFOs, CEOs, and executives from stratified firm samples across the US, UK, Germany, and Australia. We find four key facts. First, around 70 percent of firms actively use AI, particularly younger, more productive firms. Second, while over two-thirds of top executives regularly use AI, their average use is only 1.5 hours a week, with one quarter reporting no AI use. Third, firms report little impact of AI over the last three years, with more than 80 percent of firms reporting no impact on either employment or productivity. Fourth, firms predict sizable impacts over the next three years, forecasting AI will boost productivity by 1.4 percent, increase output by 0.8 percent, and cut employment by 0.7 percent. We also survey individual employees who predict a 0.5 percent increase in employment in the next three years as a result of AI. This contrast implies a sizable gap in expectations, with senior executives predicting reductions in employment from AI and employees predicting net job creation.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/102928/original</guid>
<dc:creator>Wang, Ben; Bloom, Nicholas; Bunn, Philip; Jalca, Aaron; Davis, Steven J.; Barrero, Jose Maria; Yotzov, Ivan; Foster, Kevin; Meyer, Brent; Mizen, Paul; Navarrete, Michael; Smietanka, Pawel; Thwaites, Gregory</dc:creator>
<dc:date>2026-03-24</dc:date>
<rdau:hasExtent>68</rdau:hasExtent>
<dc:subject>artificial intelligence; productivity; employment</dc:subject>
<swpo:hasNumber>2026-3</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-03</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Assessing the Role of Global Demand and Supply Shocks in the Recent US Inflation Experience Using a Cross-Country Panel Dataset of Professional Forecasts</title>
<link>https://fedinprint.org/item/fedawp/101965/original</link>
<description>
<![CDATA[Although there have been a range of studies investigating the role and importance of global supply and demand shocks in US inflation developments during and since the pandemic, this study uses a heretofore unused dataset for this purpose: a quarterly panel of professional forecasts from Consensus Economics. We use real-time data with daily vintage snapshots since 2005 from the Federal Reserve Board of Governors FAME database to disentangle forecast errors from revisions and to exploit the monthly frequency and partial availability of CPI inflation and industrial production. Our measures of global demand and supply shocks account for nearly 60 percent, and 20 percent, respectively, of the total variability of the five global factors we identify. The global demand shock accounts for a greater share of unanticipated US economic activity growth and inflation than the global supply shock both prior to the pandemic and during and after 2020. Since 2020, however, global demand and global supply shocks have accounted for similar shares of the nowcast errors for US inflation.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101965/original</guid>
<dc:creator>Higgins, Patrick C.</dc:creator>
<dc:date>2025-10-06</dc:date>
<rdau:hasExtent>40</rdau:hasExtent>
<dc:subject>global shocks; professional forecasts; inflation</dc:subject>
<swpo:hasNumber>2025-10</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-10</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>A Uniformly Valid Test for Instrument Exogeneity</title>
<link>https://fedinprint.org/item/fedawp/101963/original</link>
<description>
<![CDATA[This paper studies the limiting behavior of the test for instrument exogeneity in linear models when there is uncertainty about the strength of the identification signal. We consider the test for conditional moment restrictions with an expanding set of constructed instruments. We establish the uniform validity of the standard normal asymptotic approximation, under the null, of this specification test over all possible degrees of model identification. As a result, this allows the researcher to use standard inference for testing instrument exogeneity without the need of any prior knowledge if the instruments are strong, semi-strong, weak, or completely irrelevant. Furthermore, we show that the test is consistent regardless of the instrument strength; i.e., even in cases (weak and completely irrelevant instruments) where the standard tests fail to exhibit asymptotic power. To obtain these results, we characterize the rate of the estimator under a drifting sequence for the identification signal. We illustrate the appealing properties of the test in simulations and an empirical application.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101963/original</guid>
<dc:creator>Gospodinov, Nikolay; Dovonon, Prosper</dc:creator>
<dc:date>2025-09-25</dc:date>
<rdau:hasExtent>71</rdau:hasExtent>
<dc:subject>linear instrumental variables (IV) model; conditional test for instrument exogeneity; uniform inference; instrument strength; generalized method of moments (GMM) estimator; drifting sequences; expanding set of basis functions</dc:subject>
<swpo:hasNumber>2025-9</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-09</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>The Price of Delay: Supply Chain Disruptions and Pricing Dynamics</title>
<link>https://fedinprint.org/item/fedawp/101962/original</link>
<description>
<![CDATA[We study the role of supply chain disruptions in shaping consumer prices, focusing on both firms' own import shocks and strategic responses to competitors' disruptions. Using a newly constructed microlevel dataset that links transaction-level US import data from bills of lading with high-frequency consumer prices and sales from a consumer panel, we develop a novel approach to estimate the price effects of cost shocks and product availability. Motivated by a model of delivery delays, cost shocks, and firm pricing, we implement a shift-share identification strategy based on delivery shortfalls, port congestion, and freight and import costs. We find sizable pass-through elasticities: firms raise prices in response to higher import costs and delivery delays, especially when disruptions persist. We also identify strategic pricing: firms—including non-importers—increase prices in response to competitors' supply chain disruptions. Using our estimates and back-of-the-envelope calculations from the model, we show that strategic interactions significantly amplified the direct effects of supply chain shocks on consumer prices during the pandemic.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101962/original</guid>
<dc:creator>Fuchs, Simon; Baslandze, Salomé</dc:creator>
<dc:date>2025-09-24</dc:date>
<rdau:hasExtent>61</rdau:hasExtent>
<dc:subject>supply chains; inflation; delivery delays; strategic interactions; pass-through; inventory</dc:subject>
<swpo:hasNumber>2025-8</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-08</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>From Skills to Occupations: Comparative Advantage and Cross-Country Income Differences</title>
<link>https://fedinprint.org/item/fedawp/101966/original</link>
<description>
<![CDATA[We revisit the role of human capital in cross-country income differences. We develop a general equilibrium model where workers of different skill groups sort into occupations by comparative advantage. Wages and employment depend on workers' skill quality, occupation-specific country-embedded productivity, and occupational distortions. Using harmonized microdata for 50 countries, we infer these components from the model's equilibrium conditions. Workers in rich countries exhibit higher skill quality and substantially greater productivity, especially in white-collar occupations. Human capital explains 52 percent of output-per-worker gaps, largely through the complementarity between skill composition and quality, and further amplified by technology choices biased toward skilled labor. Adopting the US distribution of skill groups yields limited gains for poor countries without higher quality. Occupational distortions are more severe in low-income countries, reducing white-collar employment and raising wage premia, but with modest aggregate effects.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101966/original</guid>
<dc:creator>Gottlieb, Charles; Monge-Naranjo, Alexander; Grobovsek, Jan</dc:creator>
<dc:date>2025-10-08</dc:date>
<rdau:hasExtent>74</rdau:hasExtent>
<dc:subject>human capital; development accounting; occupational sorting; country-embedded productivity; wage premia</dc:subject>
<swpo:hasNumber>2025-11</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-11</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>On Model Aggregation and Forecast Combination</title>
<link>https://fedinprint.org/item/fedawp/101967/original</link>
<description>
<![CDATA[Policy makers express their views and decisions via the lens of a particular model or theory. But since any model is a highly stylized representation of the unknowable object of interest, all these models are inherently misspecified, and the resulting ambiguity injects uncertainty in the decision-making process. We argue that entropy-based aggregation is a convenient device to confront this uncertainty and summarize relevant information from a set of candidate models and forecasts. The proposed aggregation tends to robustify the decision-making process to various sources of risks and uncertainty. We find compelling evidence for the advantages of entropy-based aggregation for forecasting inflation.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101967/original</guid>
<dc:creator>Massoumi, Esfandiar; Gospodinov, Nikolay</dc:creator>
<dc:date>2025-10-09</dc:date>
<rdau:hasExtent>15</rdau:hasExtent>
<dc:subject>model uncertainty; model aggregation; forecast combination; robust policy</dc:subject>
<swpo:hasNumber>2025-12</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-12</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Evaluating Transportation Improvements Quantitatively: A Primer</title>
<link>https://fedinprint.org/item/fedawp/101968/original</link>
<description>
<![CDATA[How do we evaluate the welfare gains from transportation infrastructure investment? We present a quantitative spatial framework that integrates both traffic and economic responses to infrastructure investment and derive the elasticity of aggregate welfare to improvements in the transportation network. This approach extends the traditional "social savings" method to incorporate agglomeration and dispersion externalities and endogenous traffic congestion. We calibrate the model to the US freight transport network and assess the welfare impact of upgrading segments of the US Interstate Highway System, quantifying the marginal gains from improvements in specific corridors and highlighting where the returns to investment are highest.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101968/original</guid>
<dc:creator>Fuchs, Simon; Allen, Treb; Foong Wong, Woan</dc:creator>
<dc:date>2025-10-14</dc:date>
<rdau:hasExtent>33</rdau:hasExtent>
<dc:subject>transportation networks; infrastructure; social savings; quantitative spatial models</dc:subject>
<swpo:hasNumber>2025-13</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-13</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>COBOLing Together UI Benefits: How Delays in Fiscal Stabilizers Affect Aggregate Consumption</title>
<link>https://fedinprint.org/item/fedawp/101969/original</link>
<description>
<![CDATA[The United States experienced an unprecedented increase in unemployment insurance (UI) claims beginning in March 2020. State UI-benefit systems were strained beyond their administrative capacity to process the dual challenge of an unprecedented increase in claims and changes to UI benefits. In states that used an antiquated programming language, COBOL, to process claims, potential claimants experienced a larger increase in administrative difficulties, resulting in longer delays in benefit disbursement. States that used an antiquated UI-benefit system experienced a 2.8 percentage point decline in total credit and debit card consumption relative to card consumption in states with more modern UI benefit systems. Furthermore, states that used these antiquated systems experienced at least a 2.1 percentage point increase in the share of claims that were delayed by more than 70 days.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/101969/original</guid>
<dc:creator>Navarrete, Michael</dc:creator>
<dc:date>2025-10-16</dc:date>
<rdau:hasExtent>57</rdau:hasExtent>
<dc:subject>unemployment insurance; administrative burdens; automatic stabilizers</dc:subject>
<swpo:hasNumber>2025-14</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-14</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Geospatial Heterogeneity in Inflation: A Market Concentration Story</title>
<link>https://fedinprint.org/item/fedawp/102337/original</link>
<description>
<![CDATA[We study how inflation varies across regions with different income levels and the role of retailer market structure. Using NielsenIQ Retail Scanner and Business Dynamics Statistics data, we document new stylized facts of spatial heterogeneity in food inflation and retailer market structure. From 2006 to 2020, poorer metropolitan statistical areas experienced annualized food inflation that was 0.46 percentage points higher than that of richer ones—amounting to a cumulative difference of 8.8 percentage points over the period. Poorer areas also had fewer goods, fewer retailers, and higher market concentration. Using a triple-difference estimator during the 2014–15 bird flu outbreak, we identify a causal link between market concentration and inflation.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/102337/original</guid>
<dc:creator>Navarrete, Michael; Kim, Seula</dc:creator>
<dc:date>2025-11-06</dc:date>
<rdau:hasExtent>61</rdau:hasExtent>
<dc:subject>inflation; retailer market structure; market concentration; spatial inequality</dc:subject>
<swpo:hasNumber>2025-15</swpo:hasNumber>
<identifiers:doi>10.29338/wp2025-15</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>The Evolution of U.S. Educational Mobility over the 20th Century and the Role of Public Education</title>
<link>https://fedinprint.org/item/fedawp/102338/original</link>
<description>
<![CDATA[We construct two new large-scale datasets to measure relative and upward educational mobility by sex, race, class, and childhood county of residence for cohorts born in 1910–1919 and 1982–1997. We show that both relative and upward educational mobility rose over the 20th century, with historically disadvantaged groups experiencing the largest gains. We also document substantial geographic convergence over the 20th century: both within and across regions, where children live matters much less for their educational mobility today than it did at midcentury. Using a state-border design, we show that greater public investments in primary and secondary education were an important driver of upward educational mobility in the early and late 20th century, but public investments in postsecondary education emerged as a similarly important determinant in the late 20th century.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/102338/original</guid>
<dc:creator>Shariq Mohammed, A.R.; Mohnen, Paul; Bailey, Martha</dc:creator>
<dc:date>2026-01-12</dc:date>
<rdau:hasExtent>81</rdau:hasExtent>
<dc:subject>education; inequality; intergenerational mobility</dc:subject>
<swpo:hasNumber>2026-1</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-01</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Merchant Steering of Consumer Payment Choice</title>
<link>https://fedinprint.org/item/fedawp/102535/original</link>
<description>
<![CDATA[This paper investigates the degree to which merchants influence consumers' choice of how they pay for transactions. Using data from the Survey and Diary of Consumer Payments Choice, we examine consumers' adherence to their preferred payment method when making in-person transactions. We also investigate whether merchants are able to steer consumers away from their preferred payment method. We characterize preferences for paying with cash or cards according to consumers' income, level of education, and employment status. We find that consumers make most payments with their preferred method. When consumers pay with a nonpreferred method, it is due only in small part to merchants' refusal to accept that payment method. If a merchant accepts card payments, consumers who prefer paying with cards are not likely to pay with cash for large-value transactions or for gas or groceries. Discounts on cash purchases do not affect the probability of consumers deviating from using cards and paying with cash. Finally, the paper identifies “inertia” effects, which lead consumers to use the same payment method for consecutive purchases.]]>
</description>
<guid>https://fedinprint.org/item/fedawp/102535/original</guid>
<dc:creator>Shy, Oz; Greene, Claire; Stavins, Joanna</dc:creator>
<dc:date>2026-02-17</dc:date>
<rdau:hasExtent>34</rdau:hasExtent>
<dc:subject>consumer payments; consumer payment preferences; merchant steering; discounts; surcharges</dc:subject>
<swpo:hasNumber>2026-2</swpo:hasNumber>
<identifiers:doi>10.29338/wp2026-02</identifiers:doi>
<bibo:series>FRB Atlanta Working Paper</bibo:series>
</item>
<item>
<title>Talent Finance: Exploring the Future of Workforce Partnerships</title>
<link>https://fedinprint.org/item/a00034/99359</link>
<description>
<![CDATA[In 2020, our economy competes on talent. The labor market is dynamic, with in-demand skills constantly changing. A dynamic economy can create opportunities for workers, but it also creates risk. Investing in talent development—or talent finance—is imperative for companies and workers to succeed, but with the evolving nature of our global economy, our old systems of talent finance do not always work. Talent finance refers to the development and use of public and private instruments for investing in talent development and in managing related downside employment and income risks.

As early as the 1950s, large employers provided in-house professional and technical training. During this era of talent development, employees and employers had direct communication about in-demand skills, but smaller employers were not able to compete with large ones, mostly due to a lack of resources. Large corporations mainly financed these programs, removing the risk from governments or education systems.]]>
</description>
<guid>https://fedinprint.org/item/a00034/99359</guid>
<dc:creator>Miller, Sarah; Townsend, Katherine; Andreason, Stuart</dc:creator>
<dc:date>2020-09-21</dc:date>
<rdau:hasExtent>3</rdau:hasExtent>
<swpo:hasNumber>2020-12</swpo:hasNumber>
<identifiers:doi>10.29338/wc2020-12</identifiers:doi>
<bibo:series>Workforce Currents</bibo:series>
</item>
<item>
<title>How Credible Is Hong Kong's Currency Peg? Insights from Financial Market Prices</title>
<link>https://fedinprint.org/item/a00068/102339</link>
<description>
<![CDATA[This article presents a structural asset-pricing model that quantifies financial market perceptions of the credibility of Hong Kong's Linked Exchange Rate System (LERS). Using data from the foreign exchange market, the authors estimate the probability that the Hong Kong dollar (HKD) remains pegged to the US dollar (USD) and the value the HKD would take if the peg were to break. The analysis reveals multiple episodes when market confidence in the peg declined, with particularly sharp stress in late 2022 and mid-2025. In these periods, capital flows, interest rate differentials, and liquidity shocks drove market expectations of peg instability. The model identifies option prices as key forward-looking indicators of regime risk. This framework provides a real-time, market-based tool for monitoring currency peg credibility. The findings also offer policy-relevant insights into how global monetary shifts and local liquidity conditions shape perceptions of exchange rate stability.]]>
</description>
<guid>https://fedinprint.org/item/a00068/102339</guid>
<dc:creator>Jermann, Urban J.; Wei, Bin; Yue, Vivian Z.</dc:creator>
<dc:date>2025-09-25</dc:date>
<rdau:hasExtent>10</rdau:hasExtent>
<dc:subject>Hong Kong dollar; currency board; peg; exchange rate model; option prices</dc:subject>
<bibo:volume>2025</bibo:volume>
<bibo:issue>5</bibo:issue>
<identifiers:doi>10.29338/ph2025-05</identifiers:doi>
<bibo:series>Policy Hub</bibo:series>
</item>
<item>
<title>Geographic Inequality in Food Inflation</title>
<link>https://fedinprint.org/item/a00068/102396</link>
<description>
<![CDATA[Using NielsenIQ Retail Scanner data, we study how food inflation varies across regions with different income levels and the role of retailer market structure. From 2006 to 2020, for the average consumer, food prices—as measured by the personal consumption expenditures (PCE) price index for food and beverages—rose by by about 1.8 percent per year. However, this aggregate increase masked substantial spatial heterogeneity. Poorer metropolitan statistical areas (MSAs) experienced annualized food inflation that was half a percentage point higher than that of richer ones—amounting to a cumulative difference of 8.8 percentage points over the period. We show that higher retailer concentration—that is, markets with less retailer competition—in poorer areas is one contributing factor to the higher food inflation that consumers in these locations faced.]]>
</description>
<guid>https://fedinprint.org/item/a00068/102396</guid>
<dc:creator>Navarrete, Michael; Kim, Seula</dc:creator>
<dc:date>2026-02-02</dc:date>
<rdau:hasExtent>7</rdau:hasExtent>
<dc:subject>inflation; spatial inequality</dc:subject>
<bibo:volume>2026</bibo:volume>
<bibo:issue>1</bibo:issue>
<identifiers:doi>10.29338/ph2026-01</identifiers:doi>
<bibo:series>Policy Hub</bibo:series>
</item>
<item>
<title>Will Tariffs Touch Off an Inflationary Impulse? Business Execs Think So.</title>
<link>https://fedinprint.org/item/a00068/101532</link>
<description>
<![CDATA[Following the inflationary surge from 2021 to 2023, which was touched off by supply chain constraints and shipping bottlenecks, we evaluate a new panel of own-firm price and unit cost growth expectations in the Atlanta Fed's Survey of Business Uncertainty for signs that the anticipated impact from tariffs is broadening beyond directly affected firms. We find evidence for the potential of tariffs to touch off another bout of high inflation. First, firms that are directly exposed to tariffs have increased their year-ahead price growth expectations sharply (by 0.7 percentage points). Second, firms that are not directly exposed to tariffs but are operating in industries that are highly exposed to tariffs anticipate a moderately higher trajectory for year-ahead price growth (0.3 percentage points). Third, this broadening of overall price pressures—a key feature of the pandemic-era inflationary impulse—is only partially offset by lower price increases from tariff-exposed firms that are operating largely in industries not exposed to tariffs.]]>
</description>
<guid>https://fedinprint.org/item/a00068/101532</guid>
<dc:creator>Sparks, Michael; Wiczer, David; Meyer, Brent; Jalca, Aaron</dc:creator>
<dc:date>2025-08-21</dc:date>
<rdau:hasExtent>20</rdau:hasExtent>
<dc:subject>business surveys; expectations; trade policy</dc:subject>
<bibo:volume>2025</bibo:volume>
<bibo:issue>4</bibo:issue>
<identifiers:doi>10.29338/ph2025-04</identifiers:doi>
<bibo:series>Policy Hub</bibo:series>
</item>
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