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on Investment |
| By: | Pinjas Albagli; Rui Costa; Stephen Machin |
| Abstract: | When minimum wage increases impose a cost shock on employers of low wage workers, there are a variety of ways in which firms can adjust. Rather than study the main focal point of much minimum wage research, possible labour demand adjustment, this paper considers a more understudied angle. It examines whether firms can offset the cost shock through changing non-wage aspects of work related to the nature of work. This includes altering employment composition in the workplace, the use of alternative work arrangements and redefining job contracts. Whether these alter in response to minimum wages is studied through the lens of the UK's 2016 National Living Wage (NLW) introduction. In terms of traditionally studied outcomes, the NLW boosted worker wages, but with no change in total employment. Instead, firms did indeed adjust operations through changes in employment composition and by altering employment contracts. These non-labour demand adjustments of employment relations show how employment stability can be maintained in response to minimum wages as employers can restructure work through within-firm job composition and contracts. |
| Keywords: | minimum wages, employment composition, alternative work arrangements, job contracts |
| Date: | 2026–04–20 |
| URL: | https://d.repec.org/n?u=RePEc:cep:cepdps:dp2173 |
| By: | Art\=uras Juodis; Martin Weidner |
| Abstract: | We revisit panel regressions with unobserved heterogeneity through the lens of variance-weighted average treatment effects. Building on established results for cross-sectional OLS and one-way fixed effects panels, we show that two-way panel estimators with latent factors, specifically the principal components estimator of Greenaway-McGrevy, Han and Sul (2012) and the interactive fixed effects estimator of Bai (2009), also converge to interpretable estimands under fully nonparametric assumptions. Both estimators consistently estimate the same variance-weighted average of unit-time-specific treatment effects, where the weights are proportional to the conditional variance of the regressor given the unobserved heterogeneity. The result requires the number of estimated factors to grow with the sample size and applies to the single regressor case. We discuss the challenges that arise when extending to multiple regressors and to inference. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.18078 |
| By: | Ramón Talvi Robledo; Christopher Rauh; Ben Seimon; Hannes Mueller; Laura Mayoral |
| Abstract: | Forced displacement is an important policy challenge, yet forecasting is hindered by sparse, annually observed flow data and reporting delays. This article proposes a forecasting method for country outflows and dyadic flows tailored to this sparse data setting. We combine slow-moving structural predictors with high-frequency text-based signals, compress high-dimensional news into low-dimensional topic representations via Latent Dirichlet Allocation to mitigate overfitting, and estimate a stacked ensemble of gradient-boosted trees that captures non-linear origin–destination interactions while making optimal use of the available data. We further apply conformal prediction to construct statistically valid prediction intervals for bilateral flows. Analyzing the text component yields that destination-specific search intensity of migration terms is a central predictor of subsequent dyadic displacement flows. |
| Keywords: | conformal prediction, dyadic, early warning, forced displacement, forecasting, Google trends, machine learning |
| JEL: | P16 C53 D72 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:bge:wpaper:1573 |
| By: | Delaney, Judith (University of Bath); Devereux, Paul (University College Dublin) |
| Abstract: | We use population-level administrative data on secondary school students in England to examine how mathematical and verbal skills shape educational and labour market outcomes. Tracking cohorts from age 16 through higher education and into employment up to age 34, we show that these skills operate through distinct pathways. Verbal skills strongly predict educational attainment - including university enrolment, completion, and postgraduate study - while mathematical skills yield substantially larger earnings returns. At ages 30–34, moving from the 25th to the 75th percentile of the mathematics distribution is associated with 29% higher earnings, compared with 14% for verbal skills. This divergence is partly driven by field-of-study choice: individuals with stronger verbal skills are more likely to enter fields with higher completion rates but lower pay, while those with stronger mathematical skills sort into STEM and other high-paying fields. Gender differences in skills explain the female advantage in higher education and part of the STEM gap, but have limited impact on the gender earnings gap due to offsetting effects across these channels. |
| Keywords: | math skills, verbal skills, college, field of study, STEM |
| JEL: | I26 I24 I21 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18542 |
| By: | Harrington, Emma (University of Virginia); Shaffer, Hannah (Harvard Law School) |
| Abstract: | Decision-makers often rely on earlier actors but fail to correct for their biases. We model and measure two mechanisms: underestimating upstream bias and treating subjective information as ground truth. We link an original survey of 203 North Carolina prosecutors to their 505, 787 cases. Exploiting the rollout of police body-worn cameras (BWC), we show monitoring reduces incarceration disparities by 14 percent, little of which is driven by arrests. About one quarter of this effect reflects learning: prosecutors with greater BWC exposure view police as more biased and unreliable. Monitoring reduces disparities most for prosecutors who treat police reports as ground truth. |
| Keywords: | systemic discrimination, biased beliefs, monitoring, bodyworn cameras, prosecutorial discretion, racial disparities, criminal justice system |
| JEL: | J15 K14 K42 D82 D83 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18528 |
| By: | George Fatouros; Kostas Metaxas |
| Abstract: | We present the first portfolio-level validation of MarketSenseAI, a deployed multi-agent LLM equity system. All signals are generated live at each observation date, eliminating look-ahead bias. The system routes four specialist agents (News, Fundamentals, Dynamics, and Macro) through a synthesis agent that issues a monthly equity thesis and recommendation for each stock in its coverage universe, and we ask two questions: do its buy recommendations add value over both passive benchmarks and random selection, and what does the internal agent structure reveal about the source of the edge? On the S&P 500 cohort (19 months) the strong-buy equal-weight portfolio earns +2.18%/month against a passive equal-weight benchmark of +1.15% (approximating RSP), a +25.2% compound excess, and ranks at the 99.7th percentile of 10, 000 Monte Carlo portfolios (p=0.003). The S&P 100 cohort (35 months) delivers a +30.5% compound excess over EQWL with consistent direction but formal significance not reached, limited by the small average selection of ~10 stocks per month. Non-negative least-squares projection of thesis embeddings onto agent embeddings reveals an adaptive-integration mechanism. Agent contributions rotate with market regime (Fundamentals leads on S&P 500, Macro on S&P 100, Dynamics acts as an episodic momentum signal) and this agent rotation moves in lockstep with both the sector composition of strong-buy selections and identifiable macro-calendar events, three independent views of the same underlying adaptation. The recommendation's cross-sectional Information Coefficient is statistically significant on S&P 500 (ICIR=+0.489, p=0.024). These results suggest that multi-agent LLM equity systems can identify sources of alpha beyond what classical factor models capture, and that the buy signal functions as an effective universe-filter that can sit upstream of any portfolio-construction process. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.17327 |
| By: | Dedeepya Sukha (University of Cumberlands, Williamsburg, KY, USA); Atif Mohammad (University of Cumberlands, Williamsburg, KY, USA); Nikhil Natesh (University of Cumberlands, Williamsburg, KY, USA) |
| Abstract: | This paper examines the consequences of relying on artificial intelligence systems for religious and cultural understanding, arguing that such reliance threatens the transmission and preservation of spiritual traditions. Through an analysis of AI responses to questions about Hindu murti puja (deity worship), this paper introduces the concept of the "Polite Nothing, " a programmed pattern in which AI systems produce respectful, carefully worded responses that lack substantive engagement with the complexity, internal debates, and contextual nuances inherent to religious traditions. By asking a leading AI model three related questions about idol worship in Hinduism, this research demonstrates how these systems consistently deliver answers that appear helpful but ultimately evade theological depth, transform communal religious discourse into individualized consumer choice, and flatten centuries of philosophical debate into safe, anodyne statements. This pattern is not incidental but structural, resulting directly from alignment training designed to avoid controversy and potential offense. |
| Keywords: | Artificial Intelligence, Religious Education, Cultural Preservation, AI Bias, Hinduism, Algorithmic Evasion, Knowledge Transmission |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0631 |
| By: | Darrell Norman Burrell (Marymount University, USA); Allison J. Huff (The University of Arizona, USA); Delores Springs (Capitol Technology University, USA); Quatavia McLester (Columbus State University, USA); Daphnee Labidou-West (Marymount University, USA); Won Song (Capitol Technology University, USA) |
| Abstract: | This commentary examines the structural roots and consequences of racial bias in healthcare technology and the persistent underrepresentation of racial and ethnic minorities in clinical research. While medical technologies are often framed as objective and scientifically neutral, this paper argues that they are embedded within broader social, historical, and institutional contexts that shape their development and application. Empirical evidence demonstrates that widely used diagnostic tools, such as pulse oximeters and infrared thermometers, can produce systematically biased readings across racial groups, leading to clinically significant disparities in diagnosis and treatment. Concurrently, clinical trials continue to disproportionately enroll White participants, limiting the generalizability and validity of medical knowledge for diverse populations. The analysis integrates perspectives from social psychology and systems thinking to illustrate how mistrust, implicit bias, historical injustice, and institutional design collectively reinforce inequitable outcomes. These issues are not isolated technical flaws but interconnected failures spanning research design, regulatory oversight, industry incentives, and community engagement. As a result, healthcare systems risk institutionalizing error while perpetuating unequal risk distribution. The paper argues that meaningful reform requires a comprehensive systems-based approach, including regulatory accountability, inclusive research practices, culturally competent methodologies, and sustained community partnerships. Addressing these challenges is essential not only for improving scientific rigor but also for restoring public trust and advancing health equity. Ultimately, the paper positions equity as a foundational requirement for both ethical legitimacy and effective healthcare delivery in diverse societies. |
| Keywords: | Healthcare Equity, Racial Bias, Healthcare Technology, Biotechnology, Clinical Trials, Health Disparities, Health Administration, Medical Device Development, Healthcare Research |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0628 |
| By: | Yu, Jiao; Wang, Yi; Gill, Thomas M.; Chen, Xi |
| Abstract: | We estimate the effect of neighborhood disorder on dementia risk among middle-aged and older adults in the United States and identify cardiometabolic dysregulation as a mediating biological pathway. Using data from the Health and Retirement Study (HRS, 2006-2020), we show that exposure to visible neighborhood disorder is associated with higher risk of dementia (Hazard Ratio: 1.37; 95% CI: 1.08-1.74) and higher risk of cognitive impairment no dementia (CIND; HR: 1.50; 95% CI: 1.22-1.85) over a 14-year follow-up. Mediation analysis reveals that a composite cardiometabolic risk score-aggregating seven biomarkers spanning inflammatory, cardiovascular, and metabolic systems-accounts for approximately 16 percent of the total neighborhood disorder-dementia association and 19 percent of the neighborhood disorder-CIND association. These findings are robust to competing-risk regression for mortality, restriction to non-movers, age-at-onset restrictions, and exclusion of pandemic-year data. The results establish neighborhood disorder as a modifiable upstream risk factor for cognitive decline and identify cardiometabolic health as a biologically proximate mediating pathway. The findings have implications for place-based public health policy: community-level interventions that simultaneously reduce visible signs of neighborhood decay and address cardiometabolic risk may yield dementia-prevention dividends beyond what individual-level clinical strategies alone can achieve. |
| Keywords: | dementia, cognitive impairment, neighborhood disorder, cardiometabolic risk, social determinants of health, mediation analysis |
| JEL: | I12 I14 J14 R23 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1744 |
| By: | Guthrie Gray-Lobe; Michael Kremer; Joost de Laat; Oluchi Mbonu; Cole Scanlon |
| Abstract: | This study evaluates a large-scale SMS outreach program to engage caregivers of students in private primary schools in Kenya. Using a two-stage randomization design, we tested two types of weekly SMS messages: growth-mindset encouragement and personalized performance information. We find two main effects: First, outreach improved test scores by 0.07 standard deviations, with particularly strong gains among initially lower-performing students. This improvement generates 12 learning-adjusted years of schooling per US$100 spent—making it highly cost-effective relative to other education interventions. Second, outreach increased student exit rates by 4.7-5.0 percentage points, with effects concentrated among higher-achieving students (5.7 to 6.6 percent-age points). We develop a theoretical model of vertically differentiated schools where parental engagement affects both learning production and school choice. The model shows that when parents update their understanding of education production through engagement programs, they become more sensitive to perceived school quality differences. This increased sensitivity can lead lower-quality schools to forgo implementing engagement programs—even when costless—as enhanced parental discernment accelerates student exits. Our findings suggest a role for third-party provision of parent engagement programs in competitive education markets. |
| JEL: | D83 D91 I21 L15 O15 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35103 |
| By: | Pongspikul, Tayatorn; Palange, Kyra; Plastina, Alejandro; Ifft, Jennifer; Parcell, Joe; Ibendahl, Gregg; O’Brien, Dan; Roach, Alice |
| Abstract: | In February 2026, the U.S. Department of Agriculture (USDA)’s Economic Research Service (ERS) updated state-level farm income estimates through calendar year 2024 and released national farm income projections for calendar years 2025 and 2026. In March 2026, the Food and Agricultural Policy Research Institute at the University of Missouri (FAPRI-MU) also released national farm income projections for calendar years 2025 through 2035. The present report published by the Rural and Farm Finance Policy Analysis Center (RaFF) provides an updated outlook for Kansas farm income in calendar years 2025 and 2026, as well as preliminary projections for 2027. It intends to inform policymakers, industry analysts, and agricultural practitioners about the state agricultural sector’s expected profitability and its main drivers. |
| Keywords: | Agricultural Finance |
| Date: | 2026–04–15 |
| URL: | https://d.repec.org/n?u=RePEc:ags:umcraf:397810 |
| By: | Greg Cancelada |
| Abstract: | By using assumptions and math to analyze the relationships between different economic factors, economic models help economists forecast and understand the economy. |
| Keywords: | economic modeling; mathematical models |
| Date: | 2026–04–15 |
| URL: | https://d.repec.org/n?u=RePEc:fip:l00100:103042 |
| By: | Binder, Ariel (U.S. Census Bureau); Risch, Max (Tepper School of Business, Carnegie Mellon University); Voorheis, John (Center for Economic Studies, U.S. Census Bureau) |
| Abstract: | Housing is the largest capital asset for most families. While the intergenerational mobility literature has extensively studied the income distribution, it has devoted less attention to housing, in part due to data limitations. We document 3 features of intergenerational mobility by comparing housing capital and income in a new dataset covering 3.4 million U.S. families. First, housing is more persistent across generations than earnings. Moreover, the housing gap between White and Black children grows more sharply throughout the parental resource distribution than does the earnings gap. Second, less than half of intergenerational housing persistence operates through child earnings, leaving substantial scope for direct transmissions of capital assets and knowledge. The direct channel is much weaker among Black families and can almost fully explain their greater risk of downward mobility. Third, local housing supply constraints shape spatial differences in the intergenerational mobility of housing - but not of earnings - as measured in a quasi-experimental shift-share design. Our results highlight a more rigid structure of economic resources across families than implied by income studies. |
| Keywords: | housing markets, intergenerational mobility, homeownership, wealth distribution, capital, income, housing supply, racial disparities |
| JEL: | E24 O18 R31 D31 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18546 |
| By: | Mariana Fernández Soto; Ana Escoto; Diego Alburez-Gutierrez (Max Planck Institute for Demographic Research, Rostock, Germany); Iván Williams (Max Planck Institute for Demographic Research, Rostock, Germany) |
| Keywords: | Guatemala, Mexico, Uruguay, child care, kinship |
| JEL: | J1 Z0 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:dem:wpaper:wp-2026-012 |
| By: | Chakraborty, Lekha (National Institute of Public Finance and Policy) |
| Abstract: | The Union Budget 2026–27, presented alongside the 16th Finance Commission's recommendations, represents a critical juncture in India's fiscal federalism. Amidst a commitment to fiscal consolidation, the budget targets a central fiscal deficit of 4.3 percent of GDP while advancing debt sustainability goals. The retention of 41 percent vertical devolution, combined with performance-linked grants and incentives for state-level reforms, aims to address persistent vertical and horizontal imbalances. This paper examines the federal implications across key dimensions of Union Budget 2026-27 including the fiscal consolidation paths for centre and states, tax devolution dynamics, power sector reforms and the calculus of consent in the subtle targeted sectoral announcements, and concludes. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:npf:wpaper:26/447 |
| By: | MarcoVega (Banco Central de Reserva del Perú); Andrew Garcia (Universidad del Pacífico) |
| Abstract: | Este artículo introduce el uso de las redes de Kolmogorov-Arnold (KAN) para identificar e interpretar las formas funcionales de la curva de Phillips en el Perú. Los resultados indican que la curva podría exhibir no linealidades; sin embargo, estas no se derivan de la relación entre la inflación y la actividad económica o la tasa de desempleo —como se asume comúnmente en la literatura existente—, sino de la interacción entre las variaciones del tipo de cambio y la inflación. Aunque este hallazgo contrasta con la mayoría de las investigaciones previas, que enfatizan la no linealidad a través de la brecha del producto o el desempleo, no se descarta la posibilidad de linealidad. Los datos revelan tanto dinámicas lineales como no lineales. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:rbp:wpaper:2025-025 |
| By: | Rose Murunzi; Roy Havemann |
| Abstract: | Introduces a reform barometer to track progress in structural reforms in South Africa. The note assesses whether implemented reforms are translating into measurable improvements in economic performance and growth outcomes. |
| Keywords: | structural reform, South Africa, economic performance, growth |
| JEL: | O43 O55 P16 |
| Date: | 2026–03–11 |
| URL: | https://d.repec.org/n?u=RePEc:cxs:wpaper:202603 |