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data/wp_data.csv

@@ -2372,3 +2372,18 @@ Bootstrapping out-of-sample predictability tests with real-time data,"Silvia Gon
 Mismatch Unemployment During COVID-19 and the Post-Pandemic Labor Shortages,"Serdar Birinci, Yusuf Mercan, and Kurt See","We examine the extent to which mismatch unemployment—employment losses relative to an efficient allocation where the planner can costlessly reallocate unemployed workers across sectors to maximize output—shaped labor market dynamics during the COVID-19 pandemic and the subsequent recovery episode characterized by labor shortages. We find that, for the first time in our sample, mismatch unemployment turned negative at the onset of the pandemic. This result suggests that the efficient allocation of job seekers would involve reallocating workers toward longer-tenure and more-productive jobs, even at the expense of fewer hires. We show that sectoral differences in job separations were the main driver behind this result, while differences in vacancies caused positive mismatch unemployment during the recovery episode. We also establish an empirical link between mismatch unemployment and the surge in the labor cost during the recovery, documenting that sectors with larger mismatch unemployment experienced higher employment cost growth.",https://research.stlouisfed.org//wp/more/2024-025,2024-025A,September 2024,FED-STLOUIS,09/18/2024
 The Implications of Labor Market Heterogeneity on Unemployment Insurance Design,Serdar Birinci and Kurt See,"We digitize state-level and time-varying unemployment insurance (UI) laws on initial eligibility, payment amount, and payment duration and combine them with microdata on labor market outcomes to estimate UI eligibility, take-up, and replacement rates at the individual level. We document how levels of income and wealth affect unemployment risk, eligibility, take-up, and replacement rates both upon job loss and over the course of unemployment spells. We evaluate whether these empirical findings are important for shaping UI policy design using a general equilibrium incomplete markets model combined with a frictional labor market that matches our empirical findings. We show that a nested alternative model that fails to match these findings yields a substantially less generous optimal UI policy compared to the baseline model. Our empirical results are also relevant for researchers estimating the effects of UI policy changes on labor market outcomes.",https://research.stlouisfed.org//wp/more/2024-026,2024-026A,September 2024,FED-STLOUIS,09/20/2024
 Mismatch Unemployment During COVID-19 and the Post-Pandemic Labor Shortages,"Serdar Birinci, Yusuf Mercan, and Kurt See","We examine the extent to which mismatch unemployment—employment losses relative to an efficient allocation where the planner can costlessly reallocate unemployed workers across sectors to maximize output—shaped labor market dynamics during the COVID-19 pandemic and the subsequent recovery episode characterized by labor shortages. We find that, for the first time in our sample, mismatch unemployment turned negative at the onset of the pandemic. This result suggests that the efficient allocation of job seekers would involve reallocating workers toward longer-tenure and more-productive jobs, even at the expense of fewer hires. We show that sectoral differences in job separations were the main driver behind this result, while differences in vacancies caused positive mismatch unemployment during the recovery episode. We also establish an empirical link between mismatch unemployment and the surge in the labor cost during the recovery, documenting that sectors with larger mismatch unemployment experienced higher employment cost growth.",https://research.stlouisfed.org//wp/more/2024-025,2024-025B,September 2024,FED-STLOUIS,09/20/2024
+Real Estate Commissions and Homebuying (Revised September 2024),Borys Grochulski  and  Zhu Wang,"We construct a model of home search and buying in the U.S. housing market and evaluate the commission paid to homebuyers' agents. In the model, as in practice, homebuyers enjoy free house showings without having to pay their agents. A buyer's agent receives a 3% commission from the homeseller after the home is purchased. We show this compensation structure deviates from cost basis and leads to inefficient home searches and overused agent services. Our quantitative analysis finds that moving to a cost-based commission system increases consumer welfare by more than $30 billion a year and yields substantial social surplus gains.",https://www.richmondfed.org/publications/research/working_papers/2024/wp_24-01,24-01R,March 2024,FED-RICHMOND,09/21/2024
+Explaining Machine Learning by Bootstrapping Partial Marginal Effects and Shapley Values,"Thomas R. Cook, Zach D. Modig, Nathan M. Palmer","Machine learning and artificial intelligence are often described as ""black boxes."" Traditional linear regression is interpreted through its marginal relationships as captured by regression coefficients. We show that the same marginal relationship can be described rigorously for any machine learning model by calculating the slope of the partial dependence functions, which we call the partial marginal effect (PME). We prove that the PME of OLS is analytically equivalent to the OLS regression coefficient. Bootstrapping provides standard errors and confidence intervals around the point estimates of the PMEs. We apply the PME to a hedonic house pricing example and demonstrate that the PMEs of neural networks, support vector machines, random forests, and gradient boosting models reveal the non-linear relationships discovered by the machine learning models and allow direct comparison between those models and a traditional linear regression. Finally we extend PME to a Shapley value decomposition and explore how it can be used to further explain model outputs.",https://www.federalreserve.gov/econres/feds/explaining-machine-learning-by-bootstrapping-partial-marginal-effects-and-shapley-values.htm,2024-075,September 2024,FED-BOARD,09/21/2024
+The Inflation Accelerator,"Andres Blanco, Corina Boar, Callum Jones, Virgiliu Midrigan","We develop a tractable sticky price model in which the fraction of price changes evolves endogenously over time and, consistent with the evidence, increases with inflation. Because we assume that firms sell multiple products and choose how many, but not which, prices to adjust in any given period, our model admits exact aggregation and reduces to a one-equation extension of the Calvo model. This additional equation determines the fraction of price changes. The model features a powerful inflation accelerator – a feedback loop between inflation and the fraction of price changes – which significantly increases the slope of the Phillips curve during periods of high inflation. Applied to the U.S. time series, our model predicts that the slope of the Phillips curve ranges from 0.02 in the 1990s to 0.12 in the 1970s and 1980s.",https://www.federalreserve.gov/econres/feds/the-inflation-accelerator.htm,2024-078,September 2024,FED-BOARD,09/21/2024
+"Mortgage Design, Repayment Schedules, and Household Borrowing","Claes Bäckman, Patrick Moran, Peter van Santen","How does the design of debt repayment schedules affect household borrowing? To answer this question, we exploit a Swedish policy reform that eliminated interest-only mortgages for loan-to-value ratios above 50%. We document substantial bunching at the threshold, leading to 5% lower borrowing. Wealthy borrowers drive the results, challenging credit constraints as the primary explanation. We develop a model to evaluate the mechanisms driving household behavior and find that much of the effect comes from households experiencing ongoing flow disutility to amortization payments. Our results indicate that mortgage contracts with low initial payments substantially increase household borrowing and lifetime interest costs.",https://www.federalreserve.gov/econres/feds/mortgage-design-repayment-schedules-and-household-borrowing.htm,2024-077,September 2024,FED-BOARD,09/21/2024
+The Evolution of the Federal Reserve's Agency MBS Holdings,"Dave Na, Ellie Newman, and Bernd Schlusche","The Federal Reserve (Fed) utilized its balance sheet as a monetary policy tool in response to the Global Financial Crisis (GFC) and the COVID-19 pandemic, acquiring large quantities of Treasury and agency securities. In 2022, the Fed began to reduce the size of its securities portfolio held in the System Open Market Account (SOMA) by allowing securities to roll off its balance sheet in amounts up to specific monthly redemption caps for Treasury securities and agency securities.",https://www.federalreserve.gov//econres/notes/feds-notes/the-evolution-of-the-federal-reserves-agency-mbs-holdings-20240920.html,1017016238071723612,"September 20, 2024",FED-BOARD-NOTES,09/21/2024
+Who is Minding the Store? Order Routing and Competition in Retail Trade Execution,"Xing Huang, Philippe Jorion, Jeongmin Lee, and Christopher Schwarz","Using 150,000 actual trades, we study the U.S. equity retail broker-wholesaler market, focusing on brokers’ order routing and competition among wholesalers. We document substantial and persistent dispersion in execution costs across wholesalers within brokers. Despite this, many brokers hardly change their routing and even consistently send more orders to the more expensive wholesalers, although there is considerable variation among brokers. We also document a case where, after a new wholesaler enters, existing wholesalers significantly reduce their execution costs. Overall, our findings and theoretical framework highlight the heterogeneity across brokers and are inconsistent with perfect competition in this market.",https://www.federalreserve.gov/econres/feds/who-is-minding-the-store-order-routing-and-competition-in-retail-trade-execution.htm,2024-080,September 2024,FED-BOARD,09/21/2024
+Defining Households That Are Underserved in Digital Payment Services,"Claire Greene, Fumiko Hayashi, Oz Shy, Joanna Stavins","US households that lack digital means of making and receiving payments cannot participate fully in an increasingly digitized economy. Assessing the scope of this problem and addressing it requires a definition of households that are underserved in digital payments. Traditional definitions of households underserved in the banking system—those that are unbanked and those that are underbanked—do not account for the ownership of nonbank transaction accounts that can be used to make and receive digital payments. In this paper, we define households underserved in digital payments by considering four key elements—access, use, safety, and affordability—and discuss how researchers may assess these elements to quantify the share of households underserved in digital payments.",https://www.bostonfed.org//publications/research-department-working-paper/2024/defining-households-that-are-underserved-in-digital-payment-services,24-10,2024-09-20,FED-BOSTON,09/21/2024
+Optimal Financial Contracting and the Effects of Firm’s Size,"Sandro Brusco, Giuseppe Lopomo, Eva Ropero, Alessandro Villa","We consider the design of the optimal dynamic policy for a firm subject to moral hazard problems. With respect to the existing literature we enrich the model by introducing durable capital with partial irreversibility, which makes the size of the firm a state variable. This allows us to analyze the role of firm’s size, separately from age and financial structure. We show that a higher level of capital decreases the probability of liquidation and increases the future size of the firm. Although analytical results are not available, we show through simulations that, conditional on size, the rate of growth of the firm, its variability and the variability of the probability of liquidation decline with age.",https://www.chicagofed.org/publications/working-papers/2024/2024-18,2024-18,September 2024,FED-CHICAGO,09/21/2024
+What Does the Beveridge Curve Tell Us about the Likelihood of Soft Landings?,Andrew Figura and Chris Waller,"Any assessment of the likelihood and characteristics of a soft landing in the labor market should take into account the current state of the labor market and the likely dynamics in the labor market going forward. Modern labor market models centered around the Beveridge curve are a useful tool in this assessment. We use a simple model of the Beveridge curve to investigate what conditions are necessary for a soft landing in the labor market to occur and what the likelihood of these conditions was during the height of the pandemic-period inflation. We find that a soft landing was a plausible outcome at that time. Since then, the evolution of the labor market has borne out that prediction.",https://www.federalreserve.gov/econres/feds/what-does-the-beveridge-curve-tell-us-about-the-likelihood-of-soft-landings.htm,2024-073,September 2024,FED-BOARD,09/21/2024
+Nonlinear Dynamics in Menu Cost Economies? Evidence from U.S. Data,"Andres Blanco, Corina Boar, Callum Jones, Virgiliu Midrigan","We show that standard menu cost models cannot simultaneously reproduce the dispersion in the size of micro-price changes and the extent to which the fraction of price changes increases with inflation in the U.S. time-series. Though the Golosov and Lucas (2007) model generates fluctuations in the fraction of price changes, it predicts too little dispersion in the size of price changes and therefore little monetary non-neutrality. In contrast, versions of the model that reproduce the dispersion in the size of price changes and generate stronger monetary non-neutrality predict a nearly constant fraction of price changes.",https://www.federalreserve.gov/econres/feds/nonlinear-dynamics-in-menu-cost-economies-evidence-from-u-s-data.htm,2024-076,September 2024,FED-BOARD,09/21/2024
+High-Growth Firms in the United States: Key Trends and New Data Opportunities,"J. Daniel Kim, Joonkyu Choi, Nathan Goldschlag, John Haltiwanger","Using administrative data from the U.S. Census Bureau, we introduce a new public-use database that tracks activities across firm growth distributions over time. With these new data, we uncover several key trends for high-growth firms—critical engines of innovation and economic growth. First, the share of firms that are high-growth has steadily decreased over the past four decades, driven not only by falling rates of entrepreneurship but also languishing growth among existing firms. Second, this decline is particularly pronounced among young and small firms, while the share of high-growth firms has been relatively stable among large and old firms. We also find rich variation across states and sectors. To facilitate future research, we highlight how these data can be used to address various research questions.",https://www.federalreserve.gov/econres/feds/high-growth-firms-in-the-united-states-key-trends-and-new-data-opportunities.htm,2024-074,September 2024,FED-BOARD,09/21/2024
+Financial Conditions and Risks to the Economic Outlook,"Andrea Ajello, Giovanni Favara, Gregory Marchal, Balint Szoke","Financial conditions have swung considerably over the past two and half years. They moved from very accommodative levels in late 2021 to providing a significant drag on economic activity in 2022 and 2023. Since early this year, they eased moderately amid monetary policy communications signaling that the federal funds rate had likely reached its peak for this monetary policy tightening cycle.",https://www.federalreserve.gov//econres/notes/feds-notes/financial-conditions-and-risks-to-the-economic-outlook-20240920.html,1017016238071723599,"September 20, 2024",FED-BOARD-NOTES,09/21/2024
+Nonlinear Effects of Loan-to-Value Constraints,C. Bora Durdu and Sergio Villalvazo,"This paper investigates the impact of loan-to-value (LtV) borrowing constraints in models with occasionally binding credit constraints. These constraints give rise to a Fisherian debt-deflation mechanism, where exogenous shocks can trigger cascading effects resulting in significant declines in consumption, asset prices, and borrowing reversals—characteristic of financial crises. However, recent literature challenges traditional view by suggesting that collateral constraints may not always exacerbate financial disturbances but could instead foster dynamics leading to multiple equilibria. Building on this discussion, the paper explores equilibrium asset pricing models with LtV collateral constraints, identifying critical thresholds that govern asset price dynamics, consumption patterns, and current account behaviors. Our analysis uncovers that when the LtV limit is close to zero, tighter constraints induce smaller drops in consumption during crises. Conversely, when the LtV limit is close to one, we observe that tighter constraints induce larger drops in consumption during crises. The nonlinear relationship between the LtV ratio and adverse effects on macroeconomic outcomes aligns with cross-country evidence regarding the relationship between the level of financial development and the severity of consumption declines during crises.",https://www.federalreserve.gov/econres/feds/nonlinear-effects-of-loan-to-value-constraints.htm,2024-081,September 2024,FED-BOARD,09/21/2024
+Do Bill Shocks Induce Energy Efficiency Investments?,"Corey Lang, Kevin Nakolan, David S. Rapson and Reid Taylor",Inattention can lead to suboptimal investment in energy efficiency. We study whether electricity bill shocks draw attention to the benefits of home energy efficiency investments. Our novel identification strategy builds on the fact that prolonged extreme weather events (which raise electricity costs for many customers) fall within a single billing cycle for some customers but are split across cycles for others. We find that households exposed to average sized bill shocks are 22 percent more likely to invest in energy efficiency than households with normal bills. This result suggests that inattention is indeed a factor in residential energy decisions and utilities may be able to leverage bill shocks to promote efficiency investments.,https://www.dallasfed.org/-/media/documents/research/papers/2024/wp2405.pdf,2405,"July 16, 2024",FED-DALLAS,09/21/2024
+Social Security and High-Frequency Labor Supply: Evidence from Uber Drivers,"Timothy K. M. Beatty, Joakim A. Weill","We estimate the impact of anticipated transfers on labor supply using confidential driver-level data from Uber. Leveraging the staggered timing of Social Security retirement benefits within each month and a novel identification strategy, we find that the labor supply of older drivers declines by 2%, on average, during the week of benefit receipt—a precisely estimated but economically small effect. Individual-level analyses reveal that the average effect obscures heterogeneous micro-behavior: while the majority of drivers do not meaningfully adjust labor supply in response to social security benefits, a small group reduces labor supply by more than 40%. The results suggest that departures from standard models of labor supply can be substantial, but only for a small number of individuals.",https://www.federalreserve.gov/econres/feds/social-security-and-high-frequency-labor-supply-evidence-from-uber-drivers.htm,2024-079,September 2024,FED-BOARD,09/21/2024