|
on Investment |
| By: | Francine D. Blau; Isaac Cohen; Matthew Comey; Lawrence Kahn; Nikolai Boboshko |
| Abstract: | Using 1979-2019 Current Population Survey data, we study the effect of state and federal minimum wage policies on gender, race, and ethnic inequality. We find that minimum wages substantially reduce intergroup wage inequality at least up to the 20th wage percentile, with no evidence of adverse employment effects. We conduct counterfactual simulations of between-group inequality due to minimum wage changes since 1979. Declines in the real minimum wage in the 1980s slowed progress in narrowing between-group inequality. Relatively small changes in minimum wages during 1989-1998 and 1998-2007 meant little role for the minimum wage over those time spans. Since 2007, several states have steeply raised their minimum wages, especially raising Hispanics’ relative wages, because they earn low wages and reside disproportionately in those states. Finally, we find that raising the federal minimum wage to $12/hour in 2020 dollars ($14.49 in 2025Q2 dollars) would reduce existing between-group wage gaps below the 15th percentile by 25-50%. |
| Keywords: | wage inequality, minimum wage, wage differentials, gender wage gaps, race wage gaps, hispanic-white wage gaps |
| JEL: | J15 J16 J31 J38 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12371 |
| By: | Blau, Francine D. (Cornell University); Cohen, Isaac; Comey, Matthew (Cornell University); Kahn, Lawrence M. (Cornell University); Boboshko, Nikolai (Cornell University) |
| Abstract: | Using 1979-2019 Current Population Survey data, we study the effect of state and federal minimum wage policies on gender, race, and ethnic inequality. We find that minimum wages substantially reduce intergroup wage inequality at least up to the 20th wage percentile, with no evidence of adverse employment effects. We conduct counterfactual simulations of between-group inequality due to minimum wage changes since 1979. Declines in the real minimum wage in the 1980s slowed progress in narrowing between-group inequality. Relatively small changes in minimum wages during 1989-1998 and 1998-2007 meant little role for the minimum wage over those time spans. Since 2007, several states have steeply raised their minimum wages, especially raising Hispanics’ relative wages, because they earn low wages and reside disproportionately in those states. Finally, we find that raising the federal minimum wage to $12/hour in 2020 dollars ($14.49 in 2025Q2 dollars) would reduce existing between-group wage gaps below the 15th percentile by 25-50%. |
| Keywords: | Hispanic-White wage gaps, race wage gaps, gender wage gaps, wage differentials, wage distribution, minimum wage, wage inequality |
| JEL: | J15 J16 J31 J38 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18345 |
| By: | Rabbitt, Matthew P.; Reed-Jones, Madeline; Hales, Laura J.; Suttles, Shellye; Burke, Michael P. |
| Abstract: | This report provides statistics on food security in U.S. households throughout 2024 based on the Current Population Survey Food Security Supplement data collected by the U.S. Department of Commerce, Bureau of the Census, in December 2024. An estimated 86.3 percent of U.S. households were food secure throughout the entire year in 2024, with access at all times to enough food for an active, healthy life for all household members. The remaining households (13.7 percent, not statistically significantly different from the 13.5 percent in 2023 or 12.8 percent in 2022) were food insecure at least some time during the year. Very low food security is the more severe range of food insecurity where one or more household members experience reduced food intake and disrupted eating patterns at times during the year because of limited money or other resources for food. In 2024, 5.4 percent of households were very low food secure, an estimate that is statistically similar to the 5.1 percent in 2023 and 5.1 percent in 2022. Children and adults were food insecure at times during 2024 in 9.1 percent of U.S. households with children, statistically similar to the 8.9 percent in 2023 and 8.8 percent in 2022. In 2024, very low food security among children was 0.9 percent, statistically similar to the 1.0 percent in 2023 and 1.0 percent in 2022. In 2024, the typical food-secure household spent 11.1 percent more on food than the typical food-insecure household of the same size and household composition. During the month before the 2024 survey, about 58.9 percent of food-insecure households participated in one or more of the three largest Federal nutrition assistance programs: the U.S. Department of Agriculture's Supplemental Nutrition Assistance Program (SNAP); the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC); and the National School Lunch Program (NSLP). |
| Keywords: | Agricultural and Food Policy, Consumer/Household Economics, Food Security and Poverty, Research Research Methods/Statistical Methods |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ags:uersrr:386180 |
| By: | Mehrotra, Santosh (University of Bath); Sarkar, Kingshuk (affiliation not available) |
| Abstract: | India introduced sweeping legal changes on labour laws in late 2025, summarising 29 laws into 4 labour Codes. The Key Changes and Concerns Industrial Relations Raises the threshold for requiring government permission for layoffs/retrenchments from 100 to 300 workers, encouraging firms to avoid permanent employees; Introduces "sole negotiating union" requiring 51% worker support; Imposes 14-day notices and prohibitions during conciliation, making legal strikes impossible Wages: Introduces unclear "floor wage" concept without adequate distinction from minimum wage; Lacks mechanism for revising the basic wage component based on changing consumption patterns; Social Security: Maintains 10-worker threshold for provident funds and benefits, excluding most unorganized sector workers; Misses opportunity to universalize social security as a legislative right Occupational Safety: Covers only establishments with 10+ workers, excluding smaller workplaces; The codes represent missed opportunities for genuine labor reform, avoiding issues like job security, collective bargaining rights, fair minimum wages, gender discrimination, and social security - especially for majority of India's workforce in the informal sector. |
| Keywords: | labour law, India, occupational health, social security, minimum wages, industrial relations |
| JEL: | J08 J38 J52 J53 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izapps:pp218 |
| By: | Alves, Daniel H. |
| Abstract: | Brazil is among the few countries where income distribution has become fairer in recent decades. Its Gini coefficient fell significantly in the 2000s while the left-wing Workers' Party government approved key equity-enhancing reforms in Congress. By analyzing hundreds of news pieces, legislative documents, and secondary sources, I show the strategies that incumbents from the left adopted to build and manage cross-party coalitions that allowed structural changes to materialize. This research is the first systematic effort to detail how three consequential redistributive policies in the areas of conditional cash-transfer programs, education, and minimum wages found their way through a fragmented legislature where the chief executive's party was minoritarian. Findings add nuance to social policymaking and reveal that partisanship-based approaches to how inequality declined in Latin America require deeper complexification. In the Brazilian case, leftist presidents improved redistribution by investing in multiparty cooperative arrangements while ideology got diluted in the process. |
| Keywords: | coalition dynamics; cooperation; Latin American politics; political parties; social policymaking |
| JEL: | R14 J01 |
| Date: | 2024–05–24 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130714 |
| By: | Resendiz, Jose L.; Ranger, Nicola; Sulaeman, Johan; Broadstock, David C. |
| Abstract: | This study examines sustainability-linked finance (SLF) as a tool for mobilising corporate finance for nature in Southeast Asia, addressing gaps in how nature-related risks and opportunities are incorporated into financial instruments. As businesses and their supply chains depend heavily on ecosystem services, they are increasingly exposed to the risks of nature degradation. Embedding SLF within a coherent transition finance framework would help businesses to transition, reducing impacts and dependencies on nature while managing emerging nature-related risks. In Southeast Asia, the SLF market has grown rapidly to nearly US$20 billion, driven mainly by sustainability-linked loans. Using data from SLF deals and nature-related key performance indicators (KPIs), we combine market statistics, network analysis and an AI-assisted review of corporate reports to examine how nature-aligned finance is being mobilised. The findings highlight significant potential to scale such products, but also reveal a persistent gap between corporate disclosures, loan covenants and global standards, which may increase greenwashing and pricing inaccuracy risks, potentially undermining investor confidence and limiting capital flows to nature-positive projects. To address these challenges, we recommend: a shared taxonomy of nature-related KPIs; modest fines or accelerated re-verification to align disclosures with performance targets; integrating nature within emerging transition finance frameworks; licensing sustainability coordinators; targeted fiscal and prudential incentives; and partial credit guarantees or concessional refinancing for taxonomy-aligned transactions. |
| JEL: | N0 F3 G3 |
| Date: | 2025–09–04 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130730 |
| By: | Xuan, Zhichong; Li, Xinrong; Yang, Boqiong; Zhao, Qiran |
| Abstract: | In response to the global push for low‐carbon development and the persistent tension between economic growth and ecological goals in developing countries, China launched the Low-Carbon City Pilot (LCCP) policy in 2010 to explore potential synergies between environmental regulation and economic performance. This study treats the LCCP policy as a quasi‐natural experiment to evaluate its average treatment effect on foreign direct investment (FDI) and to analyze its spatial spillover effects and underlying mechanisms. Using panel data for 282 prefecture‐level cities from 2005 to 2021, we employ staggered difference‐in‐differences and spatial difference‐in‐differences methods. Our findings indicate that the LCCP policy significantly deters FDI in pilot cities, lending support to the pollution haven hypothesis. A mechanism analysis identifies four pathways: induced green technological innovation, strengthened environmental governance, an optimized foreign investment structure, and public behavior-driven. Notably, the LCCP policy generates positive spillovers by stimulating FDI in adjacent cities. Heterogeneity analysis reveals that the negative impacts are more pronounced in growing and mature resource‐based cities, as well as in the eastern and central regions of China. These results suggest that, while environmental regulations may discourage FDI in the short run, they can effectively foster spatial cooperation and industry restructuring that promote sustainable development. |
| Keywords: | Environmental Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360767 |
| By: | Fischer, Mira (WZB - Social Science Research Center Berlin); Rau, Holger A. (University of Göttingen); Rilke, Rainer Michael (WHU Vallendar) |
| Abstract: | We study how AI tutoring affects learning in higher education through a randomized experiment with 334 university students preparing for an incentivized exam. Students either received only textbook material, restricted access to an AI tutor requiring initial independent reading, or unrestricted access throughout the study period. AI tutor access raises test performance by 0.23 standard deviations relative to control. Surprisingly, unrestricted access significantly outperforms restricted access by 0.21 standard deviations, contradicting concerns about premature AI reliance. Behavioral analysis reveals that unrestricted access fosters gradual integration of AI support, while restricted access induces intensive bursts of prompting that disrupt learning flow. Benefits are heterogeneous: AI tutors prove most effective for students with lower baseline knowledge and stronger self-regulation skills, suggesting that seamless AI integration enhances learning when students can strategically combine independent study with targeted support. |
| Keywords: | self-regulated learning, large language models, AI tutors, higher education |
| JEL: | C91 I21 D83 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18338 |
| By: | Cristina Bellés-Obrero; Manuel Flores Mallo; Pilar García-Gómez; Sergi Jimenez-Martin; Judit Vall Castelló |
| Abstract: | This chapter studies social security reforms and trends in inequalities among older workers over the last decades in Spain. Its main goal is to analyze the redistributive impact of the various pension reforms on older income inequality. Compared to the rules in 1985, recent pension reforms have led to an average increase on Social Security Wealth of approximately 18, 000€ for men and 15, 000€ for women. This represents a ten and eight percent increase, respectively. This effect is mostly driven by the mechanical or direct effect (e.g. via benefit adjustments), while changes in retirement probability (secondary or behavioral effect) are close to zero. Furthermore, we find striking differences across income quartiles, for both men and women. In both cases, there is a clear income gradient, where the richest quartile has benefitted the most with an increase close to twenty percent, or over €50, 000, for both men and women. Conversely, the change for the poorest income quartile for men and the two poorest income quartiles for women is close to zero or even slightly negative. This is likely due to the effect of minimum benefits (that mark the generosity of the system, see Boldrin et al, 1999) that automatically absorb any other effect for low-income individuals. |
| JEL: | D31 H55 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34577 |
| By: | Pitkäranta, Juho; Raukola, Antti |
| Abstract: | The turbulent first eleven months of Donald Trump's second presidency has been characterized by policy actions and statements that create large uncertainties and sideline multilateral cooperation. The Trump administration has fueled substantial trade policy uncertainty globally, as well as pushed protectionist policies that have induced negative supply shocks to the US economy. Monetary policy is frustrated by inflationary pressures from an elevated federal deficit. Green energy projects are proactively sidelined in favor of a return to fossil fuels. Stricter immigration policy and deportation of undocumented migrants threatens to reduce US economic output, adding to price pressures. The eventual push-back from the general public, courts and lawmakers has yet to materialize, so the Trump administration continues to move ahead on deregulation of financial markets, including the easing of capital and stress testing, as well as a modifying the laws and regulations affecting bank mergers and crypto currencies. |
| Keywords: | tariffs, trade war, fiscal policy, federal deficit, green energy, fossil fuels, deportations, financial deregulation, small open economies |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:bofitb:334517 |
| By: | Jianping Mei; Michael Moses; Jan Waelty; Yucheng Yang |
| Abstract: | We study how deep learning can improve valuation in the art market by incorporating the visual content of artworks into predictive models. Using a large repeated-sales dataset from major auction houses, we benchmark classical hedonic regressions and tree-based methods against modern deep architectures, including multi-modal models that fuse tabular and image data. We find that while artist identity and prior transaction history dominate overall predictive power, visual embeddings provide a distinct and economically meaningful contribution for fresh-to-market works where historical anchors are absent. Interpretability analyses using Grad-CAM and embedding visualizations show that models attend to compositional and stylistic cues. Our findings demonstrate that multi-modal deep learning delivers significant value precisely when valuation is hardest, namely first-time sales, and thus offers new insights for both academic research and practice in art market valuation. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.23078 |
| By: | Hiroki Shinozaki; Shigehiro Serizawa |
| Abstract: | We consider a package assignment problem with money, in which a set M of objects is allocated to agents. Each agent has preferences that are not necessarily quasi-linear. The admissible set of object allocations is chosen by the planner to pursue specific objectives in conjunction with the rule. A rule satisfies constrained efficiency if no allocation ―whose object allocation is admissible under the rule―Pareto dominates the outcome allocation. We study the compatibility between constraints on admissible object allocations and desirable properties of rules, and establish: A rule satisfies constrained efficiency and strategy-proofness, together with other mild properties, if and only if its admissible set is bundling unit-demand for some partition of M, satisfies no wastage and anonymity, and the rule is a bundling unit-demand minimum price Walrasian rule. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1292r |
| By: | Abraham Itzhak Weinberg |
| Abstract: | Financial market prediction is a challenging application of machine learning, where even small improvements in directional accuracy can yield substantial value. Most models struggle to exceed 55--57\% accuracy due to high noise, non-stationarity, and market efficiency. We introduce a hybrid ensemble framework combining quantum sentiment analysis, Decision Transformer architecture, and strategic model selection, achieving 60.14\% directional accuracy on S\&P 500 prediction, a 3.10\% improvement over individual models. Our framework addresses three limitations of prior approaches. First, architecture diversity dominates dataset diversity: combining different learning algorithms (LSTM, Decision Transformer, XGBoost, Random Forest, Logistic Regression) on the same data outperforms training identical architectures on multiple datasets (60.14\% vs.\ 52.80\%), confirmed by correlation analysis ($r>0.6$ among same-architecture models). Second, a 4-qubit variational quantum circuit enhances sentiment analysis, providing +0.8\% to +1.5\% gains per model. Third, smart filtering excludes weak predictors (accuracy $ |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.15738 |
| By: | Nicolas Ajzenman (McGill University); Martín Ardanaz (Inter-American Development Bank); Guillermo Cruces (Universidad de San Andrés-CONICET, University of Nottingham); Germán Feierherd (Universidad de San Andrés); Ignacio Lunghi (New York University & CEDLAS-IIE-UNLP) |
| Abstract: | Corruption—and the widespread perception of it—poses significant obstacles to development by eroding institutional trust and reducing citizens’ willingness to pay taxes. Yet, government efforts to improve public perceptions by combating corruption may prove ineffective—or even backfire—when confronted with entrenched pessimistic beliefs. We propose that providing an external benchmark of corruption to shift the reference point before highlighting government actions can mitigate these negative effects. In a survey experiment exploiting an institutional reform within Honduras’ tax agency, we find that messages focusing solely on reform efforts have limited or negative effects. By contrast, a combined message that first corrects pessimistic beliefs and then highlights anti-corruption efforts significantly reduces perceived corruption and tax evasion intentions. A field experiment with approximately 45, 000 taxpayers confirms that this sequencing approach increases actual tax compliance. These findings suggest that belief updating is possible—but only when information is structured to first engage and recalibrate skeptical priors. |
| Keywords: | Corruption, Tax Administration, Tax Evasion, Field Experiment |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:sad:wpaper:173 |
| By: | Manho Kang; Xiangtao Meng; Katheryn N. Russ; James Waters |
| Abstract: | Have recent tariffs resulted in increased costs for the US healthcare system? We examine US trade data and compile a database of statutory tariff changes. Tariffs on medical goods narrowly defined resulted in $3.4 Billion in duties assessed between February and July 2025—more than 10 times the same period in 2024, with a 55.8 percent rate of pass-through at the US border. We estimate that had medical goods imports observed in 2024 been subject to the statutory tariff levels prevailing in August 2025, assessed duties would have been $15.8 Billion, almost 30 times higher than those observed in real-time. Our aggregates understate imports of medical goods and other imports used in healthcare settings, as data limitations compel us to omit purchases of imported goods for construction, maintenance, and operations of facilities, as well as imports under certain HS10 and HS6 tariff codes that are used when identifying medical goods in many contexts but contain a mixture of imports for medical and non-medical purposes. |
| JEL: | F10 F13 F14 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34531 |
| By: | Roth, Felix; Rammer, Christian |
| Abstract: | Intangible assets have increasingly been identified as a main source of productivity gains. Since the pioneering work by Corrado, Hulten, and Sichel (2005), empirical research has largely focused on macro and industry-level studies, while firm-level studies have often been confined to a limited set of intangible assets, especially Research and Development (R&D). This paper employs a unique firm-level panel database that contains information on four types of intangible assets: R&D, software & databases (S&D), firm-specific human capital (HC), and brand value (BV). For R&D, we find much lower productivity returns than for S&D and HC. R&D even loses significance once controlling for other intangibles, except for high-tech manufacturing. In contrast to R&D, we find that S&D and HC tend to be the primary drivers of productivity gains, particularly in services. Our findings have implications for research policy, suggesting a stronger focus on supporting investment in non-R&D intangibles, including S&D and HC. |
| Keywords: | Non-R&D intangibles, productivity, R&D, digitalisation, firm-specific human capital, brand value, firm-level panel data |
| JEL: | E22 O33 O38 D24 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:333901 |
| By: | Kang, Nawon; Rad, Mani Rouhi; Nayga Jr., Rodolfo M.; Hrozencik, Aaron; Perez-Quesada, Gabriela |
| Abstract: | This study examines the long-term effects of United States Bureau of Reclamation (USBR) dams on agricultural productivity and population growth in the Western U.S., with a focus on the role of canals. Using a staggered Difference-in-Differences (DiD) approach, we compare downstream counties with and without canals to upstream counties. Our findings show that USBR dams led to substantial increases in irrigated farmland, the value of agricultural land, population, and crop sales in downstream counties relative to upstream counties. However, the effects were much stronger in downstream counties with canal infrastructure. For example, counties with canals saw greater increases in irrigated farmland, farmland values, and population growth compared to those without canals. In contrast, counties without canals experienced minimal or negative effects. Our robustness checks also confirm that the benefits extend beyond proximity to dams, with the most significant effects observed in counties with canal infrastructure. These results underscore the critical role of complementary infrastructure in shaping the returns to large-scale federal investments in water management, with broader implications for contemporary debates on climate resilience and rural development. |
| Keywords: | Community/Rural/Urban Development |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361120 |
| By: | Brown, Zachary S.; Connor, Lawson; Rejesus, Roderick M.; Yorobe Jr., Jose M. |
| Abstract: | Farmer control of agricultural pests raises the possibility of bioeconomic feedbacks and spillovers, whereby greater aggregate effort exerted on pest control lowers overall pest densities. This in turn decreases individual growers’ marginal incentives for pest control. While economists have written theoretically about such feedbacks or modeled it in simulations of bio-invasions, they rarely measure it econometrically. Here we adapt an instrumental variables methodology developed for discrete choice endogenous sorting models in the environmental and urban economics literatures to study bioeconomic feedbacks in pest control. As a methodological innovation, we introduce use of censored regression methods to handle 0% or 100% market shares in hedonic second-stage analysis of fixed effects in discrete choice models. We apply these methods to study area-level adoption and potential feedbacks from individuals’ decisions to adopt transgenic Bt corn, using a panel dataset from the Philippines. In a conceptual model, we generate the hypothesis that greater areawide deployment of Bt crops should reduce individual farmers’ incentives to use this technology, ceteris paribus. Our econometric estimation supports the hypothesis that greater areawide use of Bt attenuates individual incentives to use these varieties. In terms of economic significance, this feedback effect implies a mean long-run price elasticity for the Bt trait 67% lower than that implied by an econometric model ignoring it. Examining whether this estimated feedback relates to areawide pest suppression, we find farmers’ expectations about infestation from the main pest targeted by Bt crops are significantly reduced by higher areawide Bt deployment. We conclude by discussing the welfare and yield implications for these areawide bioeconomic feedbacks. |
| Keywords: | Environmental Economics and Policy |
| URL: | https://d.repec.org/n?u=RePEc:ags:cenrep:272080 |
| By: | Jikai Jin; Vasilis Syrgkanis |
| Abstract: | The design of efficient nonparametric estimators has long been a central problem in statistics, machine learning, and decision making. Classical optimal procedures often rely on strong structural assumptions, which can be misspecified in practice and complicate deployment. This limitation has sparked growing interest in structure-agnostic approaches -- methods that debias black-box nuisance estimates without imposing structural priors. Understanding the fundamental limits of these methods is therefore crucial. This paper provides a systematic investigation of the optimal error rates achievable by structure-agnostic estimators. We first show that, for estimating the average treatment effect (ATE), a central parameter in causal inference, doubly robust learning attains optimal structure-agnostic error rates. We then extend our analysis to a general class of functionals that depend on unknown nuisance functions and establish the structure-agnostic optimality of debiased/double machine learning (DML). We distinguish two regimes -- one where double robustness is attainable and one where it is not -- leading to different optimal rates for first-order debiasing, and show that DML is optimal in both regimes. Finally, we instantiate our general lower bounds by deriving explicit optimal rates that recover existing results and extend to additional estimands of interest. Our results provide theoretical validation for widely used first-order debiasing methods and guidance for practitioners seeking optimal approaches in the absence of structural assumptions. This paper generalizes and subsumes the ATE lower bound established in \citet{jin2024structure} by the same authors. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.17341 |
| By: | Williams, Dwight E.; Lallo, Cicero H.O.; Bekele |
| Abstract: | A study was conducted to evaluate the response of broilers to changes in the duration of feeding starter, grower and finisher diets when grown to 49 days. A total of 2560 day-old commercial broiler chicks of mixed sex (straight run) were assigned to 32 pens and sixteen (16) treatments were randomly assigned resulting in a completely randomized design. Diets were formulated to meet nutrient levels typical of the current local industty. Diets were changed from starter (222g CP/kg, 12.77 MJ ME/kg) at 10, 15, 20, 25, or 28 days to grower (202 g CP/kg, 12.76 MJ ME/kg) and from grower to finisher (198g CP/kg, 12.77 MJ ME/kg) at 36, 41, 43, 46 days of age or not at all. Broilers grown to 49 days attained the desired weight of 2400g on all feeding programs evaluated. Feed consumption responses over time were quadratic for the durations of feeding starter diet (R2.99.9%), grower diet (R2=87.5%) and finisher diet (R2=99.2%). Similarly responses of live body weight gain were quadratic for the durations of feeding starter diet (R2=99.9%), grower diet (R2=96.1%) and finisher diet (R2=99.2%). Feed conversion and calorie conversion showed significant (p<0.001) linear trends for the duration of feeding starter diet (R2=91.08 and 93.6%) and finisher diet (R2.81.2 and 81.1%), respectively but not the grower diet (R2=1.4%). Abdominal fat (AF) as a percentage of body weight at slaughter showed a quadratic (R2=87.3%) response to the duration of feeding starter diet, peaking at 20 days and then declined. AF showed an inverse linear response (R2=78.4%) as a function of duration of finisher diet The cost of starter, grower, and finisher diets showed significant differences (p<0.001) between treatments. However, total feed cost per bird was not significantly (p>0.506) affected by the different treatments. Margin over feed cost (MOFC), marginal physical product (MPP), and the value of the marginal product (VMP) were not significantly affected (p>0.325) by treatments. However, it was noted that utilising a program consisting of starter 1-20d and grower 21-49 days as an alternative to the current industry program can improve the industry MOFC by approximately 10%. |
| Keywords: | Agricultural and Food Policy, Environmental Economics and Policy, International Development |
| URL: | https://d.repec.org/n?u=RePEc:ags:carc04:265607 |
| By: | Rockwell, Matthew |
| Abstract: | We prove the existence and smoothness of solutions to the three-dimensional Navier-Stokes equations. Specifically, we establish that for viscosity greater than zero and dimension equal to three, given any smooth, divergence-free vector field with spatial decay satisfying appropriate decay conditions with decay parameter greater than five, and taking the forcing term identically zero, there exist smooth pressure and velocity functions on three-dimensional Euclidean space times the nonnegative time interval satisfying the Navier-Stokes equations with smooth solutions and bounded energy for all nonnegative time. Our approach reformulates the problem geometrically using differential forms and Hodge theory on Riemannian manifolds. We demonstrate that the Navier-Stokes equations are equivalent to geometric consistency conditions on a velocity field section of a bundle over spacetime, governed by the Hodge-Laplace operator. The existence of smooth, globally defined solutions follows from the Hodge decomposition theorem, elliptic regularity theory for the Laplace-de Rham operator, and weighted Sobolev transport estimates along Lagrangian trajectories. A key contribution is establishing that spatial decay of initial data implies temporal integrability of the velocity gradient through geometric necessity: the vanishing energy flux at spatial infinity, acting as a boundary condition, prevents gradient accumulation. This closes the gap in the Beale-Kato-Majda conditional regularity criterion, demonstrating that decay structure of initial data governs global regularity via geometric constraints rather than dynamical evolution mechanisms. The method provides a pathway to global smoothness that complements existing approaches based on smallness or critical Sobolev regularity. |
| Keywords: | Navier-Stokes Equation, Hodge Theory, Weighted Sobolev Spaces, Geometric Analysis |
| JEL: | C60 C61 C62 C63 C65 |
| Date: | 2025–11–21 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127103 |
| By: | Lagos, Francisco (University of Maryland at College Park); Saltmarsh, Jason (Old Dominion University); Liu, Jing (University of Maryland) |
| Abstract: | This study examines how centralized-admission school lotteries affect between-school racial and ethnic segregation in the largest U.S. public school districts. Using original nationwide panel data and a difference-in-differences design with staggered adoption, the research analyzes effects on school composition, intergroup exposure, and distribution evenness. The findings reveal that centralized-admission lotteries led to increased White student enrollment in district schools and modest improvements in intergroup exposure. Black-White exposure rose by 1.6 percentage points and student of color-White exposure by 1.8 points. However, White students experienced reduced exposure to all racial and ethnic groups, with similar patterns for Black, Asian, and other students of color. While centralized lotteries modestly redistribute students, they do not significantly reduce overall segregation, challenging assumptions about equity-promoting reforms. These results underscore the need for complementary policies including weighted lottery designs, transportation subsidies, and targeted adoption to address the structural roots of school segregation. |
| Keywords: | school choice, centralized-admission lotteries, school segregation, student assignment |
| JEL: | I24 I28 J15 H75 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18306 |
| By: | Alberto Baffigi (Banca d’Italia) |
| Abstract: | The origins of credit statistics by economic sector (Statistiche sul credito per rami di attività) form a crucial part of the history of official statistics in Italy. In the way they were conceived and in the institutional context in which they were developed, they represent a significant episode for at least two complementary reasons: they enabled a systematic encounter between statistics and economic analysis – something rare in the Italian tradition – and they gave rise to a form of statistical production that was autonomous from political power, and thus stable, reliable, and enduring. Within the context of the fascist dictatorship, the creation of the Research Department at the Bank of Italy contributed to making the institution a stable technostructure over time – one capable of ensuring methodological consistency in its statistical outputs. It allowed to establish a technostructure that did not merely carry out the will of the regime, but rather drew on a degree of theoretical and, to some extent, organizational autonomy. |
| Keywords: | Credit statistics, Bank of Italy, Fascist Italy |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:vnm:wpdman:226 |
| By: | Matthieu Mastio (UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT-SMAC - Systèmes Multi-Agents Coopératifs - IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse); Paul Saves (IRIT-SMAC - Systèmes Multi-Agents Coopératifs - IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse); Gaudou Benoit (UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT-SMAC - Systèmes Multi-Agents Coopératifs - IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse); Nicolas Verstaevel (UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT-SMAC - Systèmes Multi-Agents Coopératifs - IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse, IRIT - Institut de recherche en informatique de Toulouse - UT Capitole - Université Toulouse Capitole - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - CNRS - Centre National de la Recherche Scientifique - Toulouse INP - Institut National Polytechnique (Toulouse) - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - TMBI - Toulouse Mind & Brain Institut - UT2J - Université Toulouse - Jean Jaurès - Comue de Toulouse - Communauté d'universités et établissements de Toulouse - EPE UT - Université de Toulouse - Comue de Toulouse - Communauté d'universités et établissements de Toulouse) |
| Abstract: | Industrial symbiosis fosters circularity by enabling firms to repurpose residual resources, yet its emergence is constrained by socio-spatial frictions that shape costs, matching opportunities, and market efficiency. Existing models often overlook the interaction between spatial structure, market design, and adaptive firm behavior, limiting our understanding of where and how symbiosis arises. We develop an agent-based model where heterogeneous firms trade byproducts through a spatially embedded double-auction market, with prices and quantities emerging endogenously from local interactions. Leveraging reinforcement learning, firms adapt their bidding strategies to maximize profit while accounting for transport costs, disposal penalties, and resource scarcity. Simulation experiments reveal the economic and spatial conditions under which decentralized exchanges converge toward stable and efficient outcomes. Counterfactual regret analysis shows that sellers' strategies approach a near Nash equilibrium, while sensitivity analysis highlights how spatial structures and market parameters jointly govern circularity. Our model provides a basis for exploring policy interventions that seek to align firm incentives with sustainability goals, and more broadly demonstrates how decentralized coordination can emerge from adaptive agents in spatially constrained markets. |
| Keywords: | Market Analysis, Circular Economy, Industrial Symbiosis, Agent Based Simulation |
| Date: | 2026–05–25 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05426172 |
| By: | Gatti, Nicolas |
| Keywords: | Production Economics |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea24:343759 |
| By: | Shukla, Sumedha; Arora, Gaurav; Agarwal, Sandip Kumar |
| Abstract: | Climate change and the resulting increase in crop failures pose significant production risks, particularly for smallholder farmers dependent on agriculture as their primary income source. Growing multiple crops is regarded as an important resilience strategy, enabling risk diversification through both inter-seasonal practices (e.g., double or triple cropping) and intra-seasonal approaches like mixed cropping. This study examines the role of mixed cropping - the simultaneous cultivation of multiple crops on a single plot - in production risk management among smallholder farms in semiarid and tropical regions in India. From a farm management perspective mixed cropping is expected to support higher farm incomes, improved dietary diversity, and lower production costs. However existing research exploring its farm productivity and production risk impacts is limited, inconclusive and predominantly based on agronomic experimental data. Here we investigate the effects of a cotton-pigeonpea traditional mixed cropping system on farm productivity and production risk. We employ beta regressions in conjunction with a non-linear instrumental variable framework to estimate input-conditional yield densities using plot-level primary survey data (Arora et al. 2021). The welfare implications of mixed cropping are measured using certainty equivalent - the expected income minus the cost of risk exposure. To estimate risk exposure, we use higher-order moments of the yield distributions, adapting the framework developed by Di Falco and Chavas (2009) to our multiple cropping context. We find that mixed cropping reduces the variability of returns and increases skewness, leading to an overall reduction in downside risk exposure despite its slight negative effect on mean returns. To our best knowledge, we provide the first piece of evidence on the role of mixed cropping cotton-legumes in managing farm-level production risk in India. |
| Keywords: | Production Economics |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361060 |
| By: | Aslan Bakirov; Francesco Del Prato; Paolo Zacchia |
| Abstract: | How much do worker skills, firm pay policies, and their interaction contribute to wage inequality? Standard approaches rely on latent fixed effects identified through worker mobility, but sparse networks inflate variance estimates, additivity assumptions rule out complementarities, and the resulting decompositions lack interpretability. We propose TWICE (Tree-based Wage Inference with Clustering and Estimation), a framework that models the conditional wage function directly from observables using gradient-boosted trees, replacing latent effects with interpretable, observable-anchored partitions. This trades off the ability to capture idiosyncratic unobservables for robustness to sampling noise and out-of-sample portability. Applied to Portuguese administrative data, TWICE outperforms linear benchmarks out of sample and reveals that sorting and non-additive interactions explain substantially more wage dispersion than implied by standard AKM estimates. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.00776 |
| By: | Johnson, Glenn L. |
| Keywords: | Agricultural and Food Policy, Environmental Economics and Policy, International Development |
| URL: | https://d.repec.org/n?u=RePEc:ags:carc86:265045 |
| By: | Blagica Petreski; Marjan Petreski |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ftm:policy:2025-12/58 |
| By: | International Monetary Fund |
| Abstract: | Jordan’s economy continues to show resilience despite persistent headwinds from regional conflicts and global economic uncertainty. Thanks to the authorities’ pursuit of sound economic policies and reforms, aided by strong international support, Jordan’s economic activity continues to recover, inflation remains low, and reserve buffers are strong. Nonetheless, structural challenges, including in the labor market and public utility companies, persist, and the public debt burden remains elevated. |
| Date: | 2025–12–17 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfscr:2025/338 |
| By: | Marion Goussé (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - GENES - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - GENES - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique); Nicolas Jacquemet (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - ENPC - École nationale des ponts et chaussées - IP Paris - Institut Polytechnique de Paris); Jean-Marc Robin (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique) |
| Keywords: | Measuring inequality, marriage formation, household decision making |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:hal:cesptp:halshs-05419171 |
| By: | Gurung, Suraj; Chen, Lijun Angelia; Magnier, Alexandre; Gao, Zhifeng |
| Abstract: | The rise of the Home Cooking Movement (HCM) reflects growing consumer interest in locally sourced, value-added foods and a desire for closer ties to food origins. Legislative reforms in states like California, Utah, Iowa, and Wyoming have introduced varied regulatory frameworks—from strict licensing to full exemptions— which may influence consumer trust and behavior towards home kitchens. To examine how these regulatory differences and consumer values shape willingness to pay (WTP) and purchasing decisions, we designed a discrete choice experiment (DCE) with five key attributes: price, customer reviews, establishment type (licensed/exempt home kitchens or traditional restaurants), liability insurance, and certifications. Using a betweensubjects design, respondents were randomly assigned to one of three information treatments: control, altruistic, or egoistic. A random parameter logit (RPL) model was used to capture preference heterogeneity. Results show strong, consistent WTP for food safety credentials ($3.60–$5.95). However, framing plays a critical role: egoistically framed consumers required steep discounts to choose either licensed (−$3.46) or exempt (−$3.82) home kitchens, whereas altruistic messaging significantly reduced resistance and broadened acceptance. These findings highlight the importance of value-aligned messaging and credible food safety practices in fostering consumer acceptance of home kitchens. |
| Keywords: | Consumer/Household Economics |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360599 |
| By: | Ásgeirsdottir, Tinna Laufey (University of Iceland); Francesconi, Marco (University of Essex); Johannsdottir, Ásthildur M. (University of Iceland); Zoega, Gylfi (Birkbeck College, University of London) |
| Abstract: | Leveraging administrative data from the University of Iceland, which cover more than 60% of the undergraduate population in the country, we examine how home exams and peer networks shape grades around the COVID-19 crisis. Using difference-in-difference models with a rich set of fixed effects, we find that home exams taken during university closures raised grades by about 0.5 points (about 7%) relative to invigilated in-person exams outside the pandemic period. Access to a larger share of high-school peers leads to an average grade increase of up to two-fifths of a point, and exposure to higher-quality peers yielded additional, but smaller gains. Interactions between peer-network measures and the COVID/home-exam indicators are near zero, providing no evidence that peer networks amplified home-exam gains during the pandemic. |
| Keywords: | networks, COVID-19, online education, academic performance, academic dishonesty, Iceland |
| JEL: | I21 I23 J24 D85 J16 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp18344 |
| By: | Manfredo, Mark R.; Richards, Timothy J.; Webster, Scott; Chenarides, Lauren |
| Abstract: | During the first few months of the COVID-19 pandemic, food producers threw out millions of pounds of food while grocery store shelves stood empty. Despite the overall efficiency of the modern food system, COVID-19 uncovered a general lack of resilience in food supply chains. While we know quite a bit about what it means for a supply chain to be resilient, there are few formal theoretical or empirical models that provide quantitative measures of resilience. We interpret observations of wasted food during this period as a lack of resilience in the food supply chain. We develop both a theoretical explanation for the lack of resilience and an empirical example that demonstrates how a lack of resilience affects food supply chains. We base our definition of resilience on the theory of real options and economic hysteresis. Economic hysteresis is the perpetuation of a particular course of action after the original rationale has disappeared, or, in our case, failing to invest in new distribution channels. Our analytical model of supply chain resilience demonstrates how the real option embedded in investments to adapt to a disruption leads to hysteresis and a lack of resilience. Although hysteresis results from rational responses to uncertain economic environments, managers should be aware that delays in responding to disruptions have real social consequences – wasted food in our empirical example. Indeed, we find that a firm’s rational responses to disruptions result in excessive hysteresis compared to what is best for society as a whole because a firm’s “value of waiting” differs from a social planner’s. We demonstrate the comparative static properties of hysteresis and examine a range of policy solutions for mitigating the supply-chain loss that results from hysteresis. We show how building redundancy, increasing flexibility, and increasing supply chain collaboration are all ways in which the hysteretic effect of uncertainty on supply chain resilience can be reduced. More generally, we provide a framework that can help policymakers assess the merits of alternative interventions to improve supply chain resilience. |
| Keywords: | Industrial Organization, Demand and Price Analysis |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360967 |
| By: | Feyertag, Joe |
| Abstract: | Climate change, environmental degradation, and the accelerating transition to a low-carbon economy are reshaping global labour markets. These forces are altering both the demand for and supply of labour, with far-reaching implications for central banks. As institutions that closely monitor labour market dynamics to guide monetary policy, central banks will increasingly need to account for the disruptions caused by environmental pressures. This report addresses a critical gap in current analysis by exploring how environmental risks intersect with central banks’ mandates through the labour market. It aims to equip central banks with the insights needed to integrate these evolving risks into their policy frameworks and operational decisions. |
| JEL: | N0 R14 J01 F3 G3 |
| Date: | 2025–07–23 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:130735 |
| By: | Amado, Lindorf |
| Abstract: | Standard economic models often treat money as a social construct independent of physical laws. This paper proposes a unified thermodynamic theory of value, positing that monetary systems are information protocols evolved to maximize entropy production in dissipative structures (civilizations). By analyzing 10, 000 years of economic history—from the Neolithic era to the Digital Age—we demonstrate a strict linear relationship (R2 = 0:9934) between the Real Cost of Energy (E) and the Granularity of Money (G). We derive the Equation of Value, G / E, where the value of the accounting unit scales directly with the energy cost of labor. This framework resolves historical anomalies such as the collapse of the Roman Denarius and the failure of the 20th-century Gold Standard, interpreting them not as policy errors, but as thermodynamic phase transitions. The theory predicts that the current decline in the marginal cost of energy (via AI and renewables) necessitates a transition to a monetary substrate with near-infinite divisibility and zero friction. |
| Keywords: | Thermodynamics, Monetary Theory, Entropy, Granularity, Econophysics, AI, Gold Standard, Collapse, Deterministic |
| JEL: | B52 C10 E42 N10 O33 |
| Date: | 2025–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127378 |
| By: | Katarzyna Segiet (Statistics Norway) |
| Abstract: | Firms increasingly contract out a wide range of activities that were previously done in-house, such as cleaning, security, logistics, and catering. This paper provides evidence on the impact of outsourcing on workers' earnings and possible reasons that firms outsource by estimating panel data and event study models using Norwegian administrative data. Workers who become outsourced experience large earnings declines, which are driven by reductions in working hours. Firms are likely to outsource to reduce costs and reduce rigidity in contractual working hours, which is possible as contractor firms operate on lower non-wage costs and have more workers with less than full-time contractual working hours. |
| Keywords: | Domestic Outsourcing; Subcontracting |
| JEL: | J24 J31 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:ssb:dispap:1030 |
| By: | Michelle W. Bowman |
| Date: | 2026–01–07 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgsq:102308 |
| By: | Siddhartha Srinivas Rentala |
| Abstract: | This study investigates the efficacy of Conditional Restricted Boltzmann Machines (CRBMs) for modeling high-dimensional financial time series and detecting systemic risk regimes. We extend the classical application of static Restricted Boltzmann Machines (RBMs) by incorporating autoregressive conditioning and utilizing Persistent Contrastive Divergence (PCD) to incorporate complex temporal dependency structures. Comparing a discrete Bernoulli-Bernoulli architecture against a continuous Gaussian-Bernoulli variant across a multi-asset dataset spanning 2013-2025, we observe a dichotomy between generative fidelity and regime detection. While the Gaussian CRBM successfully preserves static asset correlations, it exhibits limitations in generating long-range volatility clustering. Thus, we analyze the free energy as a relative negative log-likelihood (surprisal) under a fixed, trained model. We demonstrate that the model's free energy serves as a robust, regime stability metric. By decomposing the free energy into quadratic (magnitude) and structural (correlation) components, we show that the model can distinguish between pure magnitude shocks and market regimes. Our findings suggest that the CRBM offers a valuable, interpretable diagnostic tool for monitoring systemic risk, providing a supplemental metric to implied volatility metrics like the VIX. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.21823 |