|
on Investment |
| By: | Ester Faia; Benjamin Lochner; Benjamin Schoefer |
| Abstract: | This paper presents the first direct test of two interlinked predictions at the core of the monopsony theory of the labor market: (i) that firms exploit wage-setting power by marking down wages below the marginal revenue product of labor, and (ii) that exogenous wage constraints, if binding, eliminate markdowns. Our research design revisits the 2015 introduction of a high minimum wage in Germany. Drawing on a monopsony model, we derive an empirically tractable difference-in-differences specification that provides a quantitative benchmark for the firm-level markdown response. Our main result is that empirical markdowns respond only 0–25% as much as the monopsony model would have predicted. Hence, at least for the labor market segment we study, (i) markdowns largely reflect other distortions than monopsony, (ii) markdowns are mismeasured, (iii) minimum wages induce widespread labor shortages, or (iv) the standard monopsony model does not provide a full, realistic account of the labor market. |
| JEL: | E0 J0 L0 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34699 |
| By: | Daisuke Kurisu; Yuta Okamoto; Taisuke Otsu |
| Abstract: | Difference-in-differences (DID) is one of the most popular tools used to evaluate causal effects of policy interventions. This paper extends the DID methodology to accommodate interval outcomes, which are often encountered in empirical studies using survey or administrative data. We point out that a naive application or extension of the conventional parallel trends assumption may yield uninformative or counterintuitive results, and present a suitable identification strategy, called parallel shifts, which exhibits desirable properties. Practical attractiveness of the proposed method is illustrated by revisiting an influential minimum wage study by Card and Krueger (1994). |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.08759 |
| By: | Patrick Kline |
| Abstract: | Economists often rely on estimates of linear fixed effects models developed by other teams of researchers. Assessing the uncertainty in these estimates can be challenging. I propose a form of sample splitting for network data that breaks two-way fixed effects estimates into statistically independent branches, each of which provides an unbiased estimate of the parameters of interest. These branches facilitate uncertainty quantification, moment estimation, and shrinkage. Algorithms are developed for efficiently extracting branches from large datasets. I illustrate these techniques using a benchmark dataset from Veneto, Italy that has been widely used to study firm wage effects. |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.08101 |
| By: | Hardman, Scott PhD; Karanam, Vaishnavi PhD |
| Abstract: | California has set an ambitious target to transition 100% of off-road vehicles and equipment to zero-emission (ZE) alternatives by 2035 “where feasible, ” as outlined in Executive Order N-79-20. Interviews were conducted with 16 stakeholders—contractors, manufacturers, rental firms, researchers, nonprofits, and public agencies. Intervieweesacknowledged positive attributes of ZE equipment, but barriers were more numerous and included inadequate charging infrastructure, limited grid access at job sites, high upfront equipment costs, limited ZE model availability, and complications with rental-based procurement models. Social and organizational barriers such as operator resistance, climate skepticism, and inequities faced by smaller firms were also noted. Most interviewees expressed skepticism that the 2035 ZE off-road goal is realistically achievable without significant policy and infrastructure support. Commonly recommended interventions included strengthening site-level grid capacity, expanding financial incentives and public investment, aligning regulations with market realities, and improving policymakers’ understanding of construction practices. |
| Keywords: | Engineering, Zero emission vehicles, All terrain vehicles, Technology adoption, Electric vehicle charging, Interviews, Policy analysis |
| Date: | 2026–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt4qk0182c |
| By: | Dov Te’eni (TAU - Tel Aviv University); Myriam Raymond (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université, GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement); Frantz Rowe (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université, IUF - Institut universitaire de France - M.E.N.E.S.R. - Ministère de l'Education nationale, de l’Enseignement supérieur et de la Recherche); Etienne Thénoz (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université); Philippe Trimborn |
| Abstract: | Generative AI (GenAI) holds potential for organizations, offering transformative opportunities while simultaneously raising concerns about its associated risks. Like many emerging technologies, GenAI presents organizations with a significant challenge: navigating uncertainty before making large-scale decisions about which systems to adopt and how to implement and leverage them. Managers cannot rely solely on general knowledge of GenAI; they require insights tailored to their specific organizational context. Drawing on an 18-month study of sandbox experiments conducted within a large international service organization, this paper presents CORE-sandbox experiments as a structured framework for systematically learning about the critical dimensions of uncertainty surrounding GenAI. The framework organizes learning into four key domains: Capabilities, Opportunities, Risks, and Ecosystem. The paper also advances the discourse on organizational learning and dynamic capabilities by demonstrating how in-situ and ex-situ learning cycles reinforce one another and how second and third-order organizational learning emerge under conditions of high uncertainty before GenAI rollout decisions are made. |
| Keywords: | Uncertainty, Risks, Business opportunities, Service organizations, Sandbox experiments, Organizational learning, Generative AI |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05461433 |
| By: | Arianna Burzacchi; Marco Pistore |
| Abstract: | Urban traffic regulation policies are increasingly used to address congestion, emissions, and accessibility in cities, yet their impacts are difficult to assess due to the socio-technical complexity of urban mobility systems. Recent advances in data availability and computational power enable new forms of model-driven, simulation-based decision support for transportation policy design. This paper proposes a novel simulation paradigm for the ex-ante evaluation of both direct impacts (e.g., traffic conditions, modal shift, emissions) and indirect impacts spanning transportation-related effects, social equity, and economic accessibility. The approach integrates a multi-layer urban mobility model combining a physical layer of networks, flows, and emissions with a social layer capturing behavioral responses and adaptation to policy changes. Real-world data are used to instantiate the current "as-is" scenario, while policy alternatives and behavioral assumptions are encoded as model parameters to generate multiple "what-if" scenarios. The framework supports systematic comparison across scenarios by analyzing variations in simulated outcomes induced by policy interventions. The proposed approach is illustrated through a case study aims to assess the impacts of the introduction of broad urban traffic restriction schemes. Results demonstrate the framework's ability to explore alternative regulatory designs and user responses, supporting informed and anticipatory evaluation of urban traffic policies. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.07735 |
| By: | Parinov, Sergey |
| Abstract: | This paper explores the application of the "Institutional Analysis and Development" (IAD) framework, pioneered by Elinor Ostrom, to develop an abstract model for mechanisms facilitating joint socio-economic activities. By generalizing IAD's principles of institutional design, the study describes the structure and key functions of an abstract mechanism for joint activity and identifies a set of building blocks enabling the creation of real-world mechanisms such as networks, hierarchies, markets, and institutions. These mechanisms are analyzed through the lens of communication modes—direct, indirect, and absent—highlighting their role in coordination and governance. The research conceptualizes mechanism design as an optimization task. The construction of joint activity mechanisms is viewed as a task of selecting the optimal combination of building blocks to suit the specific characteristics of the joint activity and its surrounding environment. The prospects for developing a formal model of joint activity mechanisms are also discussed. The study introduces the notion of a "metamechanism" to guide the evolution and hybridization of the traditional mechanisms. This approach enhances understanding of how diverse mechanisms emerge and adapt to socio-economic complexities, providing a theoretical basis for improving collective action systems. The findings have broad implications for the study of governance, organizational design, and the management of commons. |
| Keywords: | principles of institutional design, joint activity, abstract mechanism, network, hierarchy, market, institution |
| JEL: | B41 D02 D7 D82 D83 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127335 |
| By: | Mark Setterfield (Department of Economics, New School for Social Research, USA) |
| Abstract: | Slow growth and decline in the wage share of income are prominent stylized facts of US macroeconomic performance over the past 3-4 decades. Most explanations of these phenomenon trace their origins to structural change -- such as deunionization, globalization, or increased corporate concentration. This paper suggests that observed wage stagnation and secular stagnation in the US economy can also be thought of as path-dependent products of policy-induced macroeconomic outcomes in the 1970s/80s. A Marx-Keynes-Schumpeter (MKS) model is developed, in which the coincidence of wage stagnation and secular stagnation is shown to arise from an intial decline in the equilibrium rate of growth, which lowers both the steady-state rate of growth and accompanying wage share. It is then shown that the predictions of the model, following an intial reduction in the equilibrium growth rate, are consistent with a number of other secular macroeconomic pathologies that have afflicted the US economy since 1990. |
| Keywords: | Wage stagnation, secular stagnation, Marx-Keynes-Schumpeter model, path dependence, structural change |
| JEL: | E11 E12 E60 O41 O51 P17 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:new:wpaper:2601 |
| By: | Juan Pablo Madrigal-Cianci; Camilo Monsalve Maya; Lachlan Breakey |
| Abstract: | Prediction markets are often described as mechanisms that ``aggregate information'' into prices, yet the mapping from dispersed private information to observed market histories is typically noisy, endogenous, and shaped by heterogeneous and strategic participation. This paper formulates prediction markets as Bayesian inverse problems in which the unknown event outcome \(Y\in\{0, 1\}\) is inferred from an observed history of market-implied probabilities and traded volumes. We introduce a mechanism-agnostic observation model in log-odds space in which price increments conditional on volume arise from a latent mixture of trader types. The resulting likelihood class encompasses informed and uninformed trading, heavy-tailed microstructure noise, and adversarial or manipulative flow, while requiring only price and volume as observables. Within this framework we define posterior uncertainty quantification for \(Y\), provide identifiability and well-posedness criteria in terms of Kullback--Leibler separation between outcome-conditional increment laws, and derive posterior concentration statements and finite-sample error bounds under general regularity assumptions. We further study stability of posterior odds to perturbations of the observed price--volume path and define realized and expected information gain via the posterior-vs-prior KL divergence and mutual information. The inverse-problem formulation yields explicit diagnostics for regimes in which market histories are informative and stable versus regimes in which inference is ill-posed due to type-composition confounding or outcome--nuisance symmetries. Extensive experiments on synthetic data validate our theoretical predictions regarding posterior concentration rates and identifiability thresholds. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.18815 |
| By: | Tal, Gil PhD; Ramadoss, Trisha |
| Abstract: | The secondary market for zero-emission vehicles (ZEVs) will play a critical role in decarbonizing transportation and in bringing ZEVs to lower income populations. Yet research into this market remains limited. Thus, in this study, the characteristics of the used ZEV market, its buyers, and the sources and destinations of used ZEVs were explored. The flows of secondhand, pre-owned, or “used” ZEVs in California were quantified by analyzing vehicle registration and transfer information from the Department of Motor Vehicles from 2016 to 2020. Descriptive statistics were used to examine this market, and the sources and destinations of used ZEVs were modeled using linear regression. Several key trends became evident. First, plug-in hybrids appear to be entering the used market at higher rates than battery electric vehicles. Second, there was a net gain of used ZEVs into disadvantaged communities over the study period. Finally, the number of households in the highest income brackets and land use types play a significant role in which census tracts are sources and destinations for used ZEVs. While the highest income bracket does not seem to play a substantive role in either side of the market, the next three income brackets serve to both generate and procure used ZEVs. |
| Keywords: | Engineering, Zero emission vehicles, electric vehicles, used cars, used vehicle industry, demographics, linear regression analysis |
| Date: | 2026–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:cdl:itsdav:qt0p9928s8 |
| By: | Sultan Amed; Tanmay Sen; Sayantan Banerjee |
| Abstract: | Credit risk models are a critical decision-support tool for financial institutions, yet tightening data-protection rules (e.g., GDPR, CCPA) increasingly prohibit cross-border sharing of borrower data, even as these models benefit from cross-institution learning. Traditional default prediction suffers from two limitations: binary classification ignores default timing, treating early defaulters (high loss) equivalently to late defaulters (low loss), and centralized training violates emerging regulatory constraints. We propose a Federated Survival Learning framework with Bayesian Differential Privacy (FSL-BDP) that models time-to-default trajectories without centralizing sensitive data. The framework provides Bayesian (data-dependent) differential privacy (DP) guarantees while enabling institutions to jointly learn risk dynamics. Experiments on three real-world credit datasets (LendingClub, SBA, Bondora) show that federation fundamentally alters the relative effectiveness of privacy mechanisms. While classical DP performs better than Bayesian DP in centralized settings, the latter benefits substantially more from federation (+7.0\% vs +1.4\%), achieving near parity of non-private performance and outperforming classical DP in the majority of participating clients. This ranking reversal yields a key decision-support insight: privacy mechanism selection should be evaluated in the target deployment architecture, rather than centralized benchmarks. These findings provide actionable guidance for practitioners designing privacy-preserving decision support systems in regulated, multi-institutional environments. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.11134 |
| By: | Joshua S. Gans |
| Abstract: | Generative AI systems often display highly uneven performance across tasks that appear “nearby”: they can be excellent on one prompt and confidently wrong on another with only small changes in wording or context. We call this phenomenon Artificial Jagged Intelligence (AJI). This paper develops a tractable economic model of AJI that treats adoption as an information problem: users care about local reliability, but typically observe only coarse, global quality signals. In a baseline one-dimensional landscape, truth is a rough Brownian process, and the model “knows” scattered points drawn from a Poisson process. The model interpolates optimally, and the local error is measured by posterior variance. We derive an adoption threshold for a blind user, show that experienced errors are amplified by the inspection paradox, and interpret scaling laws as denser coverage that improves average quality without eliminating jaggedness. We then study mastery and calibration: a calibrated user who can condition on local uncertainty enjoys positive expected value even in domains that fail the blind adoption test. Modelling mastery as learning a reliability map via Gaussian process regression yields a learning-rate bound driven by information gain, clarifying when discovering “where the model works” is slow. Finally, we study how scaling interacts with discoverability: when calibrated signals and user mastery accelerate the harvesting of scale improvements, and when opacity can make gains from scaling effectively invisible. |
| JEL: | D83 O33 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34712 |
| By: | Hadda, kilani; Mohamed, Ben AMAR |
| Abstract: | This study investigates the dynamic relationships between agricultural productivity, green energy adoption, governance quality, and environmental degradation in BRICS economies over the period 2002–2023. Using a Pooled Mean Group Autoregressive Distributed Lag (PMG-ARDL) approach, complemented by FMOLS and CCR robustness estimators, the results show that agricultural productivity significantly increases long-run environmental pollution, reflecting the environmental cost of agricultural intensification. In contrast, green energy adoption and governance quality exert strong and consistent pollution-mitigating effects, underscoring their central role in promoting environmental sustainability. Overall, the findings emphasize that long-run structural factors dominate environmental outcomes in emerging agricultural economies. The study provides policy-relevant insights for advancing low-carbon and sustainable agricultural development in BRICS countries. |
| Keywords: | Environmental pollution- Agricultural productivity- - Green innovation- PMG -BRICS |
| JEL: | Q18 Q28 Q47 |
| Date: | 2025–10–14 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127353 |
| By: | Joe Delgado (University of the Incarnate Word, San Antonio, USA) |
| Abstract: | Rising demand in solo telehealth psychology practices requires balancing growth with limited time, supervision, and financial resources. This anonymized case study examined a U.S.-based solo practice evaluating three staffing models: a practicum student, a postdoctoral fellow, or a licensed psychologist. The objective was to expand client capacity while preserving care quality and financial viability. Using practice records, guidelines, labor data, and supervision requirements, the analysis compared supervision burden, revenue potential, and sustainability across models. Findings showed practicum students had the lowest direct cost but required intensive supervision, limiting overall capacity. Postdoctoral fellows emerged as a sustainable staffing configuration, offering financial feasibility and moderate independence. Licensed psychologists provided autonomy and billing flexibility but carried the highest financial risk. The case suggests staffing choices must weigh financial tradeoffs alongside the owner’s supervision capacity. For resource-constrained solo practitioners, the study offers a framework for testing staffing models before implementation. Aligning staffing strategy with clinical and financial realities enables solo telehealth practices to pursue sustainable growth while supporting workforce development. |
| Keywords: | Telehealth, solo practice, psychology workforce, practicum training, postdoctoral fellows, licensed psychologists, supervision capacity, staffing models, cost-benefit analysis, sustainable growth |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0590 |
| By: | Jinjun Liu; Ming-Yen Cheng |
| Abstract: | We study U.S. Treasury yield curve forecasting under distributional uncertainty and recast forecasting as an operations research and managerial decision problem. Rather than minimizing average forecast error, the forecaster selects a decision rule that minimizes worst case expected loss over an ambiguity set of forecast error distributions. To this end, we propose a distributionally robust ensemble forecasting framework that integrates parametric factor models with high dimensional nonparametric machine learning models through adaptive forecast combinations. The framework consists of three machine learning components. First, a rolling window Factor Augmented Dynamic Nelson Siegel model captures level, slope, and curvature dynamics using principal components extracted from economic indicators. Second, Random Forest models capture nonlinear interactions among macro financial drivers and lagged Treasury yields. Third, distributionally robust forecast combination schemes aggregate heterogeneous forecasts under moment uncertainty, penalizing downside tail risk via expected shortfall and stabilizing second moment estimation through ridge regularized covariance matrices. The severity of the worst case criterion is adjustable, allowing the forecaster to regulate the trade off between robustness and statistical efficiency. Using monthly data, we evaluate out of sample forecasts across maturities and horizons from one to twelve months ahead. Adaptive combinations deliver superior performance at short horizons, while Random Forest forecasts dominate at longer horizons. Extensions to global sovereign bond yields confirm the stability and generalizability of the proposed framework. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.04608 |
| By: | Severin Hornung (University of Innsbruck, Austria); Thomas Hoge (University of Innsbruck, Austria); Christine Unterrainer (University of Innsbruck, Austria) |
| Abstract: | This presentation reports a first wave of studies from a research program on the psychological significance of neoliberal ideology in the socio-politico-ecological polycrisis. Neoliberalism not only enforces globally dominant political-economic practices of market expansion, entrepreneurial freedom, dismantling the welfare state, and supremacy of capital interests, but also pervades psychological processes, belief systems, and behaviors. After reviewing theoretical and methodological foundations on system-justifying neoliberal ideologies, exemplary empirical results are reported, pertaining to the ecological climate crisis, the social crisis of eroding civil solidarity, and the legitimation crisis of liberal democracies. All are addressed in survey studies using the neoliberal ideological beliefs questionnaire with sub-dimensions of individualism, competition, and instrumentality. The first study examined relationships with system justification, environmental consciousness, climate-protective behavior, and estimated carbon footprint, confirming a detrimental role of neoliberal ideological beliefs. The second study established connections between neoliberal ideological beliefs, moral disengagement, and lacking civic engagement for people seeking refuge. The third study explored correlational patterns of neoliberal beliefs, political attitudes, and party preferences, showing a tendency towards right-wing populism and social dominance orientation. Additionally, qualitative interviews were conducted among socio-economically disadvantaged groups. Contradicting their social interests, participants endorsed neoliberal individualism, competition, and instrumentality, evidenced by meritocratic explanations for poverty and rejection of wealth redistribution. Underlying psychological processes were reduction of cognitive dissonance and appeasement of epistemic and existential motives. Psychodynamics of neoliberal ideologies in the polycrisis are highlighted, including self-reinforcing spirals, corrosion of transformative capacities, and the xenophobic authoritarian turn. Implications for following waves of research are discussed. |
| Keywords: | Neoliberal Ideology, System Justification, Polycrisis, Climate Crisis, Refugee Crisis, Crisis Of Democracy, Social And Political Psychology |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0588 |
| By: | Tiago Neves Sequeira (University of Coimbra, CeBER and Faculty of Economics); Pedro Lima (University of Coimbra, CeBER and Faculty of Economics); Joshua Duarte (University of Coimbra, CeBER and Faculty of Economics) |
| Abstract: | We develop an overlapping generations endogenous growth model with cash-in-advance constraints for (i) consumers and (ii) R&D firms which is consistent with an effect of inflation on the skill-premium labor share. Inflation decreases the skill premium in both cases and decreases the labor share through (i) which it increases through (ii). The newly described effect of inflation on the labor share is consistent with empirical evidence for a short-run effect. |
| Keywords: | inflation, labor share, human capital |
| JEL: | E24 J64 L11 O33 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:gmf:papers:2025-04 |
| By: | Lin, Jessie |
| Keywords: | International Development |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361026 |
| By: | Etsusaku Shimada (Faculty of Policy Studies, Iwate Prefectural University) |
| Abstract: | Optimization is the central organizing principle of economic analysis. Individual choice, social evaluation, and policy design are routinely formulated as the maximization of an objective function over a feasible set. This paper identifies a class of environments in which optimization itself ceases to be a coherent principle of evaluation. We study decision problems in which the domain of admissible actions includes losses that are irreversible, non-substitutable, and non-compensable. We show that, under minimal regularity conditions, no refinement of the objective function—such as state dependence, option values, or intertemporal trade-offs—can generally sustain coherent maximization on an unrestricted feasible set. In such environments, optimization necessarily leads to inconsistency: actions generating non-compensable losses may be selected as optimal whenever short-run gains dominate, regardless of how the evaluation criterion is specified. The main result is an impossibility theorem establishing that coherence failure is structural and does not stem from informational limitations, computational constraints, or ethical disagreement. We then provide a necessity result showing that coherence can be restored if and only if the feasible set is restricted so as to exclude actions that generate non-compensable losses. On the resulting restricted domain, standard optimization methods apply without contradiction. The analysis reframes irreversibility as a problem of feasibility design rather than objective-function design. It clarifies the limits of optimization-based evaluation and characterizes the minimal conditions under which optimization remains a valid principle of choice. This paper also serves as a foundational contribution to a broader research agenda on the structural limits of evaluation. By isolating the conditions under which optimization-based evaluation becomes incoherent, the analysis provides a unifying framework for understanding feasibility-based constraints across diverse economic domains. The analysis is intended to serve as a conceptual reference point for further work on feasibility, irreversibility, and evaluation, rather than to exhaust their possible applications. |
| Keywords: | Optimization, Non-compensability, Feasible sets, Irreversibility, Impossibility theorem |
| JEL: | D01 D81 D90 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:kyo:wpaper:1124 |
| By: | Masoud Soleimani |
| Abstract: | We develop a transparent and fully auditable LLM-based pipeline for macro-financial stress testing, combining structured prompting with optional retrieval of country fundamentals and news. The system generates machine-readable macroeconomic scenarios for the G7, which cover GDP growth, inflation, and policy rates, and are translated into portfolio losses through a factor-based mapping that enables Value-at-Risk and Expected Shortfall assessment relative to classical econometric baselines. Across models, countries, and retrieval settings, the LLMs produce coherent and country-specific stress narratives, yielding stable tail-risk amplification with limited sensitivity to retrieval choices. Comprehensive plausibility checks, scenario diagnostics, and ANOVA-based variance decomposition show that risk variation is driven primarily by portfolio composition and prompt design rather than by the retrieval mechanism. The pipeline incorporates snapshotting, deterministic modes, and hash-verified artifacts to ensure reproducibility and auditability. Overall, the results demonstrate that LLM-generated macro scenarios, when paired with transparent structure and rigorous validation, can provide a scalable and interpretable complement to traditional stress-testing frameworks. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.07867 |
| By: | Mostapha Benhenda (LAGA) |
| Abstract: | We introduce Look-Ahead-Bench, a standardized benchmark measuring look-ahead bias in Point-in-Time (PiT) Large Language Models (LLMs) within realistic and practical financial workflows. Unlike most existing approaches that primarily test inner lookahead knowledge via Q\\&A, our benchmark evaluates model behavior in practical scenarios. To distinguish genuine predictive capability from memorization-based performance, we analyze performance decay across temporally distinct market regimes, incorporating several quantitative baselines to establish performance thresholds. We evaluate prominent open-source LLMs -- Llama 3.1 (8B and 70B) and DeepSeek 3.2 -- against a family of Point-in-Time LLMs (Pitinf-Small, Pitinf-Medium, and frontier-level model Pitinf-Large) from PiT-Inference. Results reveal significant lookahead bias in standard LLMs, as measured with alpha decay, unlike Pitinf models, which demonstrate improved generalization and reasoning abilities as they scale in size. This work establishes a foundation for the standardized evaluation of temporal bias in financial LLMs and provides a practical framework for identifying models suitable for real-world deployment. Code is available on GitHub: https://github.com/benstaf/lookaheadbenc h |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.13770 |
| By: | Ryan Donnelly; Junhan Lin; Matthew Lorig |
| Abstract: | An agent holds a position in a perpetual contract with payoff function $\psi$ and attempts to liquidate the position while managing transaction costs, inventory risk, and funding rate payments. By solving the agent's stochastic control problem we obtain a closed-form expression for the optimal trading strategy when the payoff function is given by $\psi(s) = s$. When the payoff function is non-linear we provide approximations to the optimal strategy which apply when the funding rate parameter is small or when the length of the trading interval is small. We further prove that when $\psi$ is non-linear, the short time approximation can be written in terms of the closed-form trading strategy corresponding to the case of the identity payoff function. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.10812 |
| By: | Valentin-Stefan Nuica (Orthodox Theological Seminary “Sfântul Ioan Gură de Aur†, Targoviste, Romania) |
| Abstract: | This paper analyzes the role of the Church in the formation of young people within a cultural context marked by postmodernity, individualism, and the loss of moral reference points. The study highlights the theological foundations of the Church’s mission, the responsibility of the ecclesial community toward younger generations, and the need for an educational paradigm that cultivates discernment, empathy, identity, and communion. In the face of current spiritual, cultural, social, and psychological crises, the Church is called to offer young people a stable framework of guidance, an authentic Christian way of life, and concrete support for their integration into the community and society. The formation of young people thus becomes an essential missionary act, capable of shaping the future of both the Church and the world. |
| Keywords: | Youth, Christian Formation, Mission, Identity, Community |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0612 |
| By: | Abiyot Geneme Gebre (University of Keil, Germany) |
| Abstract: | Political regime transitions in Sub-Saharan Africa (SSA) exhibit a pronounced bifurcation between peaceful transformation and violent upheaval, yet conditions and causal mechanisms for stable, nonviolent change remain scant, partly due to pervasive treatment of structural and agency factors in isolation. This study advances an integrative, qualitative comparative framework that elucidates how individual political agency and structural dynamics interact to produce divergent outcomes, using Ethiopia and Sudan as focal cases. It synthesizes leadership trajectories, coalition architecture, and socio-political ecologies to trace how leadership turnover, party organization, and state–society relations converge to foster stability or provoke volatility. Ethiopia’s episodic leadership changes within a relatively cohesive ruling coalition, reinforced by a reformist orientation and functional parliamentary mechanisms, facilitated continuity and negotiated reform, while Sudan’s extended tenure, succession ambiguity, and shift toward centralized rule undermined legitimacy, intensifying civil–military contestation amid economic distress. By foregrounding mechanisms through which individual traits (ambition, inclusivity, legitimacy-building capacity) interact with institutional configurations (coalition coherence, reform and ideological reorientation, power-sharing norms) and broader context (economic pressures, diaspora mobilization, international scrutiny), the analysis demonstrates that peaceful transitions emerge from nested interactions across levels rather than any single dimension. The study concludes with policy implications for integrated strategies that bolster inclusive governance, institutional resilience, and adaptive leadership in SSA, advocating holistic reform over siloed interventions. |
| Keywords: | Political Regime Transition, Comparative Case Study, Agency, Structure, Ethiopia, Sudan |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0596 |
| By: | Cho, Whoi; Wang, Tong |
| Keywords: | Teaching/Communication/Extension/Profession |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:361135 |
| By: | Mele, Marco; Costantiello, Alberto; Anobile, Fabio; Leogrande, Angelo |
| Abstract: | This paper evaluates the structural, environmental, and climatic factors influencing carbon dioxide emissions from the building sector (CBE) in 27 European Union member states from 2005 to 2023. This analysis uses panel data from the World Bank and four econometric models—Random Effects, Fixed Effects, Dynamic Panel GMM, and Weighted Least Squares—coupled with machine learning and clustering to provide a robust analysis of emissions. The econometric models show that all models support a negative relationship between agriculture, forestry, and fishing value added (AFFV) and forest area (FRST), suggesting that a robust rural economy and substantial natural carbon sinks are accompanied by lower emissions in the building sector. On the other hand, water stress (WSTR), PM2.5 pollution, heating and cooling degree days, and nitrous oxide emissions (N2OP) are found to significantly, yet positively, affect CBE. Tests of diagnostic analyses support Fixed Effects and Weighted Least Squares models, whereas results from GMM models are limited by instrument validity violations. In machine learning analysis, K-Nearest Neighbors (KNN) models are found to be most diagnostic, with all performance metrics being improved, establishing a prominent role for coal electricity, water stress, agricultural intensities, and climatic factors. Subsequently, a solution with 10 clusters, selected using Bayesian Information Criteria and silhouettes, identified a set of environmental and economic characteristics based on differences between low- and high-emission groups. High-emitting groups result from agricultural intensification, pollution, and low energy efficiency, while low-emitting groups are associated with renewable energy, low pollution, and a favorable climate. This analysis, hence, presents a multifaceted assessment of building sector emissions, with climatic, structural, and energy transition patterns as driving factors for meeting decarbonization targets for the European Union. |
| Keywords: | Building-sector carbon emissions; Panel data econometrics; Machine learning prediction; Environmental and climatic drivers; Cluster analysis |
| JEL: | C3 C33 C38 Q41 Q54 Q56 |
| Date: | 2025–12–12 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127321 |
| By: | Leach, Colton |
| Keywords: | Environmental Economics and Policy |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360779 |
| By: | Evguenia Bessonova (Bank of Russia, HSE University, Russian Federation); Svetlana Popova (Bank of Russia, Russian Federation); Konstantin Styrin (Bank of Russia, NES, Russian Federation) |
| Abstract: | We study the effect of the participation in a subsidized lending program on economic outcomes of small and medium-sized enterprises (SMEs) in Russia. The estimated effect on sales and employment is statistically and economically significant and robust. The annual growth of sales increases by 10.7-11.4 p.p. and of employment by 4-7 p.p. The effect on profits is sizeable but not robust, being very sensitive to the way the control sub-sample is constructed. |
| Keywords: | Firm dynamics; Small and medium-sized enterprises; Subsidized lending; Loan guarantee programs |
| JEL: | D22 G38 L25 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bkr:wpaper:wps140 |
| By: | Jean-Gabriel Attali |
| Abstract: | We study approximation limits of single-hidden-layer neural networks with analytic activation functions under global coefficient constraints. Under uniform $\ell^1$ bounds, or more generally sub-exponential growth of the coefficients, we show that such networks generate model classes with strong quantitative regularity, leading to uniform analyticity of the realized functions. As a consequence, up to an exponentially small residual term, the error of best network approximation on generic target functions is bounded from below by the error of best polynomial approximation. In particular, networks with analytic activation functions with controlled coefficients cannot outperform classical polynomial approximation rates on non-analytic targets. The underlying rigidity phenomenon extends to smoother, non-analytic activations satisfying Gevrey-type regularity assumptions, yielding sub-exponential variants of the approximation barrier. The analysis is entirely deterministic and relies on a comparison argument combined with classical Bernstein-type estimates; extensions to higher dimensions are also discussed. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.04914 |
| By: | Taha Ameen; Flore Sentenac; Sophie H. Yu |
| Abstract: | Platforms matching spatially distributed supply to demand face a fundamental design choice: given a fixed total budget of service range, how should it be allocated across supply nodes ex ante, i.e. before supply and demand locations are realized, to maximize fulfilled demand? We model this problem using bipartite random geometric graphs where $n$ supply and $m$ demand nodes are uniformly distributed on $[0, 1]^k$ ($k \ge 1$), and edges form when demand falls within a supply node's service region, the volume of which is determined by its service range. Since each supply node serves at most one demand, platform performance is determined by the expected size of a maximum matching. We establish a uniformity principle: whenever one service range allocation is more uniform than the other, the more uniform allocation yields a larger expected matching. This principle emerges from diminishing marginal returns to range expanding service range, and limited interference between supply nodes due to bounded ranges naturally fragmenting the graph. For $k=1$, we further characterize the expected matching size through a Markov chain embedding and derive closed-form expressions for special cases. Our results provide theoretical guidance for optimizing service range allocation and designing incentive structures in ride-hailing, on-demand labor markets, and drone delivery networks. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2601.13426 |
| By: | Nicolas Hardy; Dimitris Korobilis |
| Abstract: | We revisit macroeconomic time-varying parameter vector autoregressions (TVP-VARs), whose persistent coefficients may adapt too slowly to large, abrupt shifts such as those during major crises. We explore the performance of an adaptively-varying parameter (AVP) VAR that incorporates deterministic adjustments driven by observable exogenous variables, replacing latent state innovations with linear combinations of macroeconomic and financial indicators. This reformulation collapses the state equation into the measurement equation, enabling simple linear estimation of the model. Simulations show that adaptive parameters are substantially more parsimonious than conventional TVPs, effectively disciplining parameter dynamics without sacrificing flexibility. Using macroeconomic datasets for both the U.S. and the euro area, we demonstrate that AVP-VAR consistently improves out-of-sample forecasts, especially during periods of heightened volatility. |
| Keywords: | Bayesian VAR; time-varying parameters; stochastic volatility; macroeconomic forecasting; uncertainty. |
| JEL: | C11 C32 C53 E32 E37 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:gla:glaewp:2025_12 |
| By: | Etsusaku Shimada (Faculty of Policy Studies, Iwate Prefectural University) |
| Abstract: | Fiscal sustainability is commonly evaluated using aggregate indicators such as GDP growth and tax revenue elasticity, yet this paper shows that such indicators can be fundamentally insufficient once fiscal capacity depends on the evolving structure of underlying tax bases. When tax revenue is generated by heterogeneous tax bases whose growth rates and revenue weights evolve over time, aggregation induces an intrinsic informational loss that cannot be resolved by refining elasticity estimates. To establish this result, tax revenue is modeled as the aggregation of industry-specific tax bases subject to heterogeneous growth dynamics and institutional features of corporate taxation. Within this framework, we show that tax revenue growth cannot, in general, be characterized by a single, time-invariant elasticity with respect to aggregate output. The analysis clarifies the structural conditions under which conventional benchmarks, including the Domar condition, remain valid. When tax bases evolve proportionally with aggregate output and industrial composition is stable, the Domar condition emerges as a special case of a more general stability condition. Once these restrictive assumptions are relaxed, changes in tax base composition and sectoral profit dynamics can generate systematic divergences between output growth and tax revenue growth. The paper derives a structural fiscal stability condition in which debt sustainability depends on the weighted growth dynamics of underlying tax bases rather than on aggregate output alone. Stylized facts from Japan and the United States illustrate how differences in industrial structure and tax institutions shape revenue dynamics in practice. More fundamentally, the analysis highlights the structural limitations of aggregate-indicator–based fiscal evaluation: fiscal sustainability is a property of how fiscal capacity is generated through the composition and dynamics of underlying tax bases. |
| Keywords: | Fiscal sustainability, Tax revenue elasticity, Aggregation-induced informational loss, Reweighting, Domar condition, Tax base heterogeneity |
| JEL: | H20 H63 E62 O40 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:kyo:wpaper:1123 |
| By: | Keener, Steven; Finn, John; Baird, Andrew F. |
| Abstract: | In November 2025, a federal judge in the Eastern District of Virginia unsealed a spreadsheet containing the locations of 614 automatic license plate reader (ALPR) cameras currently in use in Hampton Roads, Virginia. ALPR cameras are an emergent form of networked surveillance infrastructure that capture images of every vehicle that passes by, generate a “vehicle fingerprint, ” and store those data in databases searchable by law enforcement, typically without warrants or court orders for access. The release of these locational data provides a rare opportunity to examine the opaque geography of contemporary surveillance and to assess whether ALPR camera deployment reproduces the same racialized and classed patterns long associated with policing and state surveillance in the United States. In this article, we use geographic information systems (GIS) and descriptive statistical analysis to map the distribution of 614 Flock Safety ALPR cameras in relation to racial and poverty profiles of the neighborhoods where the cameras are located. Our findings show that ALPR camera deployment is deeply and systematically racialized and economically stratified, with predominantly Black and high-poverty neighborhoods bearing a disproportionate share of ALPR surveillance infrastructure across Hampton Roads. We argue that these patterns do not reflect isolated siting decisions, but rather are the result of broader structural dynamics, including the privatization of surveillance infrastructure, weak democratic oversight, and the normalization of seemingly objective, tech-washed policing. We conclude by discussing the implications of these findings for public policy, civil liberties, democratic accountability, and Fourth Amendment protections. |
| Date: | 2026–01–13 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:5ckgv_v1 |
| By: | Yueran Ma; Mengdi Zhang; Kaspar Zimmermann |
| Abstract: | We collect new data to document the long-run evolution of the firm size distribution in ten market-based economies in Asia, Europe, North America, and Oceania, where we can obtain comprehensive coverage of the population of firms. Around the world, we observe prevalent increases in the concentration of sales, net income, and equity capital over the past century. These trends hold in the aggregate and at the industry level. Meanwhile, employment concentration has been stable over the long run in most cases. The evidence shows that the rising dominance of large firms is a pervasive phenomenon, not limited to the recent decades or the United States, and that large firms often achieve greater scale without proportionally more workers. |
| JEL: | E01 L1 N1 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34711 |
| By: | Dakshina De Silva; Inkoo Lee; Soon-Cheul Lee; Maurizio Zanardi |
| Abstract: | We develop a three-country theoretical framework and provide new evidence on the role of third-country tariffs in shaping bilateral trade flows. Our model predicts that tariff preferences can generate trade diversion and that the magnitude of this effect depends on the full tariff schedule faced by competing suppliers. Leveraging highly disaggregated transaction-level data on South Korea’s imports, we show that bilateral applied tariffs significantly depress imports, while higher third-country tariffs divert trade toward the partner country. These effects are only identifiable when exploiting the richness of our data at the product level and vary substantially across preferential and non-preferential regimes and by the number of potential suppliers. Our findings highlight the importance of accounting for third-country tariffs when assessing the trade effects of tariff changes, a point that is particularly salient in the current context of U.S. policy proposals of tariff increases. |
| Keywords: | trade flows, applied tariffs, gravity equation |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:lan:wpaper:427560367 |
| By: | Julia Cagé (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research) |
| Abstract: | Inequality in political participation and influence has strongly increased in recent decades, breeding economic inequality. In this review, we focus on three aspects of political inequality: the increasing concentration of both political and charitable donations, the growing gap in descriptive representation, and the persistent lack of substantive representation. Based on the existing literature as well as on novel evidence, we relate these aspects to the recent widening of turnout inequality. We then examine novel forms of participation—e.g., the rise of small donors in the United States—and the efficiency of policies aimed at improving representation. Finally, we discuss new avenues for research. |
| Keywords: | Political donations, Descriptive representation, Substantive representation, Representative democracies, Campaign finance, Turnout, Charitable giving, Economic inequality, Political inequality |
| Date: | 2024–08–22 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05446439 |
| By: | Tomohiro Hirano; Alexis Akira Toda |
| Abstract: | Since McCallum (1987), it has been well known that in an overlapping generations (OLG) economy with land, the equilibrium is Pareto efficient because with balanced growth, the interest rate exceeds the growth rate (R > G), precluding infinite debt rollover (a Ponzi scheme). We show that, once we remove knife-edge restrictions on the production function and allow unbalanced growth, under some conditions an efficient equilibrium with land bubbles necessarily emerges and infinite debt rollover becomes possible, a markedly different insight from the conventional view derived from the Diamond (1965) landless economy. We also examine the possibility of Pareto inefficient equilibria. |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:cnn:wpaper:26-002e |
| By: | Martin S. Eichenbaum; Joao Guerreiro; Jana Obradovic |
| Abstract: | This paper presents new survey evidence on how household spending changes in response to fiscal transfers. Our key finding is that the planned propensity to spend out of transfers equals the marginal propensity to consume (MPC). This result implies that households do not incorporate future tax liabilities into their spending plans. The canonical HANK model cannot account for our survey results because people in that model are overly sensitive to future tax liabilities. We develop an extended HANK model in which households are partially inattentive to future tax liabilities and to the general-equilibrium consequences of fiscal policy. This inattention dampens forward-looking intertemporal MPCs, bringing the model into line with our survey evidence. We use the model to analyze the aggregate effects of fiscal policy changes and find that both transfer and government spending multipliers are larger in the inattentive HANK model than in the canonical HANK framework. |
| JEL: | E30 E39 E60 E70 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34691 |
| By: | Frodermann, Corinna (Institute for Employment Research (IAB), Nuremberg, Germany); Peters, Eileen (Hans-Böckler-Stiftung); Philipp, Marie-Fleur (Universität Tübingen); Wenzig, Claudia (Institute for Employment Research (IAB), Nuremberg, Germany) |
| Abstract: | "Promoting the labour market integration of women, and of mothers in particular, is a key objective of labour market and gender equality policy. Decisive factors for mothers’ participation in paid employment include not only labour market conditions and the availability of formal childcare options, but also prevailing attitudes toward family and work. Against this background, the authors examine normative attitudes toward formal childcare arrangements and maternal employment." (Author's abstract, IAB-Doku) ((en)) |
| Date: | 2026–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:iab:iabkbe:202602 |
| By: | Suzana Gueiros Teixeira (Technology Center, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil) |
| Abstract: | This article presents an application to the Amazon Fund, developed on the period of 2023/ 2024, based on demand from concerns which have risen in the recent decades. Therefore, the selected themes are proposed based on the developments of economic demands that mandatorily have impacted the region and, among local and regional impacts, global impacts such as those associated with Environment and Climate Security issues, understanding their complexity is of both Local and Global Governance, focused to be met on the current proposal. The work proposal is directed to the Amazon Fund in attendance to the Amazon Forest challenges from the Brazilian Legal Amazon area that, under the Ecological Territory Zoning, will focus on the Military Domain Zone. Among the Military Areas within the Amazon, some are of HistoricCultural valued Defense Sites, such as the Historical Fortification of Príncipe da Beira, in English Prince of Borders, which has been raised craved into the Amazon Forest in the State of Rondônia (constructed on the period of 1776 to 1783, by the Portuguese), neighboring Bolivia by an Amazonian River named Itenez Guaporé. The name of the river is of an indigenous nature, meaning Desert Valley or Possibly Waterfall River. The project proposal intends to positively impact on the local environmental biome and provide sustainable actions towards the area with topics which involve Defense. The background of information regarding this work, is based on open sources, nonetheless, we must alert that are of Defense and Security Interests. |
| Keywords: | Amazonian Defense Intelligence, Forest, Illicit, Historical Heritage |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:smo:raiswp:0601 |
| By: | Radek Stefanski; Lassi Ahlvik; Jørgen Juel Andersen; Torfinn Harding; Alex Trew |
| Abstract: | How large are the productivity differences arising from micro-level distortions, and how much of that is due to tax policy? Using over a century of field-level data (1900-2023), this paper examines the role of field-level revenue taxes in explaining misallocation in the oil and gas industry, a single large sector that produces a homogeneous, globally-traded good. A key advantage is our ability to link model-implied distortions directly to these observed tax rates. We show that misallocation is significant in the oil industry, and that over half of this misallocation can be accounted for by the dispersion in revenue tax rates across fields, exceeding the 2-25% explanatory power typical in studies of misallocation sources. We show that nearly all of the impact of this tax dispersion operates through the intensive margin (the inputs allocated at a field) rather than the extensive margin (the choice to enter a field). These findings have direct implications for tax policy |
| Keywords: | Misallocation; productivity; distortions; tax policy |
| JEL: | O47 O11 D24 Q32 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:gla:glaewp:2025_10 |
| By: | Ayettey, Gideon; Goyal, Raghav |
| Keywords: | Agricultural Finance, Farm Management |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea25:360692 |
| By: | Marcus Vinicius de Freitas |
| Abstract: | China's ascent to the position of the world's most prominent energy consumer has altered global energy markets and fundamentally reshaped the geopolitics of energy security. As China navigates the complexities of sustaining its economic momentum, ensuring access to reliable, affordable, and diversified energy sources has become an existential imperative, intricately woven into its foreign policy strategy. In parallel, Africa's immense wealth of both conventional and renewable resources, coupled with its drive toward industrialization and sustainable development, presents a remarkable opportunity for a transformative partnership. This Policy Paper explores the strategic intersection between China's energy imperatives and Africa's developmental aspirations. It argues for a relational cooperation model that transcends a narrow transactional approach, and champions an inclusive, sustainable, and future-oriented partnership. Historically characterized by overseas investments in oilfields, critical infrastructure, and renewable energy projects, China's engagement is examined against Africa's chronic energy poverty and industrialization needs. China can enhance its energy security and gain access to Africa's abundant energy resources. At the same time, Africa can accelerate its progress towards the goals enshrined in Agenda 2063, improve its energy infrastructure, and boost its industrialization. However, the partnership is not without significant risks. Issues of debt sustainability, environmental and social governance, and political instability threaten to undermine the transformational potential of China–Africa energy cooperation. Accordingly, this Policy Paper stresses the imperative for transparent, inclusive, and sustainable modes of engagement, advocating for stronger environmental stewardship, enhanced local capacity-building, and greater alignment with Africa's regional integration agendas. This emphasis on transparency and sustainability is crucial to building confidence in the partnership. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ocp:rpcoen:pp_27-25 |
| By: | Dimitris Korobilis |
| Abstract: | I introduce a high-dimensional Bayesian vector autoregressive (BVAR) framework designed to estimate the effects of conventional monetary policy shocks. The model captures structural shocks as latent factors, enabling computationally efficient estimation in high-dimensional settings through a straightforward Gibbs sampler. By incorporating time variation in the effects of monetary policy while maintaining tractability, the methodology offers a flexible and scalable approach to empirical macroeconomic analysis using BVARs, well-suited to handle data irregularities observed in recent times. Applied to the U.S. economy, I identify monetary shocks using a combination of high-frequency surprises and sign restrictions, yielding results that are robust across a wide range of specification choices. The findings indicate that the Federal Reserve’s influence on disaggregated consumer prices fluctuated significantly during the 2022–24 high-inflation period, shedding new light on the evolving dynamics of monetary policy transmission. |
| Keywords: | Disaggregated consumer prices; Latent factors; High-dimensional Bayesian VAR; Time-varying parameters; Sign restrictions; High frequency data |
| JEL: | C11 C32 C55 E31 E52 E58 E66 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:gla:glaewp:2025_09 |
| By: | Kerr, H. W. T.; Pitchford, P. H. |
| Keywords: | Livestock Production/Industries, Production Economics |
| URL: | https://d.repec.org/n?u=RePEc:ags:notarc:266269 |
| By: | Christian Ewerhart; Haoyuan Zeng |
| Abstract: | This paper studies mediation in infinitely repeated games with perfect monitoring. In departure from the literature, we assume that all private messages and internal records are publicly revealed at the end of each stage. We call the resulting equilibrium concept mediated subgame perfect equilibrium (MSPE). It is shown that the revelation principle holds. We introduce an effective correlated minimax value, which can be conveniently determined as the solution of a linear program, and use it to derive necessary and sufficient conditions for the implementability of payoffs under an MSPE. These conditions are standard for two-player games with a sufficient degree of patience but are, in general, strictly more permissive. Examples illustrate the impact of effective correlated minimax profiles and the subtle role of internal records. |
| Keywords: | Infinitely repeated games, mediation, revelation principle, perfect folk theorem, effective minimax value, correlated equilibrium, threat points |
| JEL: | C72 C73 |
| Date: | 2026–01 |
| URL: | https://d.repec.org/n?u=RePEc:zur:econwp:484 |
| By: | Lukas Vashold; Gustav Pirich; Maximilian Heinze; Nikolas Kuschnig |
| Abstract: | Mining operations in Africa are expanding rapidly, creating negative externalities that remain poorly understood. In this paper, we provide causal evidence for the impact of water pollution from mines on downstream vegetation and agriculture across the continent. We exploit discontinuities in water pollution caused by mines along river networks to compare vegetation health upstream and downstream. We find that mines significantly reduce peak vegetation downstream, impairing the productivity of croplands. These effects correspond to substantial crop losses and highlight the environmental and agricultural externalities of mining activity. |
| Keywords: | mining, agriculture, water pollution, vegetation, externality, natural resources |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:msh:ebswps:2025-9 |
| By: | Minhaj Mahmud (Asian Development Bank); Yujie Zhang (University of Pennsylvania) |
| Abstract: | This study examines the interplay between extreme temperatures and air pollution risks, the geographic and temporal distribution, as well as the population burden of climate shocks in Bangladesh, Indonesia, Pakistan, Thailand, and Viet Nam—countries severely impacted by climate change. Using ERA5-HEAT temperature data and PM2.5 pollution data, we first identify “hotspots” within and across the countries by analyzing district level trends in heat stress and pollution exposure. We further explore the correlation between temperature and pollution shocks. Finally, jointly considering the spatial distribution of populations and key climate and pollution hazards, we highlight the most vulnerable groups with population weighted exposure measures. Our findings reveal distinct country-specific patterns in both the correlation between heat stress and air pollution risk, and the population exposure to the hazards across demographic profiles. These results emphasize targeted policies to mitigate the compounded effects of climate and air pollution hazards on vulnerable populations across Asia. |
| Keywords: | heat;air pollution;climate change;Asia;population exposure |
| JEL: | J10 Q53 Q54 Q56 |
| Date: | 2026–01–27 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:022144 |
| By: | Ali, Amjad; Usman, Muhammad; Ahmad, Khalil |
| Abstract: | This study investigates how climate-related risks influence sovereign credit ratings on a two-dimensional scale, considering both the Climate Vulnerability Index and the Climate Resilience Index. Using a panel cross-sectional dataset covering fifteen developed and developing countries from 2020 to 2024, the research evaluates how the Climate Vulnerability Index and Climate Resilience Index, along with macroeconomic control variables such as gross domestic product per capita, debt-to-gross domestic product ratio, and inflation, affect sovereign creditworthiness. The results remain consistent across robustness tests, and neither the lagged indicators nor indices derived from principal component analysis demonstrate significant predictive power. These findings are supported by graphical data, including scatter plots and heat maps. Although the theoretical expectation is that higher climate vulnerability would lead to lower ratings, the data do not offer strong empirical support for this relationship within the study period for developed and, alternatively, for developing nations. The study concludes that current methods for assessing sovereign credit ratings do not necessarily account for climate-based risks, at least in developed countries over this time frame. Policy recommendations emphasize greater transparency and the integration of climate indicators into credit models, closing resilience gaps through national government action, and prompting international financial institutions to encourage the standardization of climate risk procedures, particularly for developing nations. This study contributes to the evolving discourse on sustainable finance by identifying compromises in climate-adjusted credit assessment and proposing methods and institutional reforms. Concrete policy recommendations include the integration of forward-looking climate indicators into sovereign credit models, the adoption of climate stress testing by rating agencies, and the promotion of standardized climate risk disclosure frameworks, especially in developing economies. |
| Keywords: | Climate Risk, Sovereign Credit Ratings, GDP per capita, Debt, Price Level |
| JEL: | E0 Q5 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127543 |