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on Investment |
| By: | Lucía Ramírez Leira (CEDLAS-IIE-FCE-UNLP); Carlo Lombardo (CEDLAS-IIE-FCE-UNLP & Cornell University); Leonardo Gasparini (CEDLAS-IIE-FCE-UNLP & CONICET) |
| Abstract: | In Argentina, the national minimum wage (NMW) coexists with sectoral wage floors (WF) established through collective bargaining agreements (CBA). These WFs exceed the NMW for most registered workers, rendering the minimum wage largely ineffective. Using novel data on union-negotiated wages combined with administrative records, this paper analyzes the impact of WFs set in CBAs on employment, wages, and wage inequality among formal workers. The analysis is conducted at both the industry and individual levels, utilizing a fixed-effects model by year and sector and a linear probability model based on individual worker trajectories. Results indicate that CBAs reduce overall wage inequality by decreasing inequality at the upper end of the distribution without affecting the lower end. No significant employment effects are found, except for a negative impact in sectors with a higher proportion of small firms (MSMEs). However, at the worker level, CBAs reduce the probability of remaining employed for work- ers near the wage floors, with more negative effects observed in MSMEs. Finally, CBAs’ positive effect on wage increases and negative effects on employment are more pronounced in unfavorable macroeconomic conditions. |
| JEL: | J22 J31 J38 K31 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:dls:wpaper:0353 |
| By: | Jae Yoon Lee (Korea Institute for Industrial Economics and Trade); Go Eun Lee (Korea Institute for Industrial Economics and Trade) |
| Abstract: | Under the authority of Section 232 of the Trade Expansion Act, on February 10, 2025, US President Donald Trump announced the repeal of existing exemptions and waivers for tariffs on steel, aluminum, and related products, introducing a uniform 25 percent tariff without exception. The measure went into effect on March 12.<p> South Korean steel exports were already in decline; US tariffs have only intensified the concerns of a major downturn. - From January to April, South Korean steel exports to the US plunged by 10.2 percent year-on-year (YoY). Exports to the rest of the world fell by 2.6 percent YoY.<p> Yet, the effects of the Trump tariffs have yet to fully manifest, as the recent slump in exports to the US is largely attributable to the base effect. - The pronounced YoY decline reflects exceptionally strong export performance to the US during the same period in 2024, when exports reached their highest levels since 2018.<p> While exports of key general-purpose items such as hot-rolled steel sheets and heavy plates fell significantly, products upon which the US remains dependent — such as steel pipes, surface-treated steel sheets, and tin-plated sheets, and specialty steel — maintained solid performance. - The impact of potential tariffs under the new Trump administration is expected to vary by product category. - As of 2023, US import dependency remained relatively high for steel pipes and tin-plated sheets. It was not as dependent on imports for general-purpose steel products, such as hot-rolled sheets and heavy plates.<p> Caution is needed regarding the potential adverse effects of tariffs, particularly in the general-purpose steel segment. - Now that the US has eliminated import quotas, Korean steelmakers are likely to face intensified price and market competition with other tariff-affected countries, such as Taiwan and Vietnam. The application of a flat 25 percent tariff could place Korean products at a disadvantage in terms of price competitiveness. Although the removal of quota protections may increase short-term pressure on steel exports, it is essential for Korea to respond by optimizing its export strategies and enhancing the competitiveness of its products. |
| Keywords: | US tariffs; steel; steel industry; steel exports; trade; international trade; Trump; Trump tariffs; |
| JEL: | L61 F52 F62 |
| Date: | 2025–05–21 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kietia:021438 |
| By: | Bachmann, Ruediger |
| Abstract: | * Die zweite Präsidentschaft Donald Trumps könnte die Vereinigten Staaten noch tiefer in eine erratische, autoritär geprägte Politik treiben - mit globalen Folgen. Deutschland und Europa dürfen darauf nicht mit Abwarten reagieren, sondern müssen strategisch und entschlossen handeln. Dabei liegt die Unberechenbarkeit Trumps nicht allein an seiner Persönlichkeit, sondern ist strukturell bedingt. Der sogenannte Trumpismus ist keine konsistente Ideologie, sondern ein instabiles Machtbündnis verschiedenster Strömungen - von christlichem Nationalismus über Großmachtchauvinismus bis hin zu technokratischem Oligarchendenken. Diese Koalition bleibt nur durch autoritäre Führungsloyalität und Feindbildmobilisierung zusammen - und produziert damit zwangsläufig erratische Politik. * Auch ökonomisch drohen massive Verwerfungen. Trumps protektionistische Agenda ist ineffizient und teils bewusst destruktiv angelegt. Besonders gravierend: Die fahrlässige Zoll- und Schuldenpolitik gefährdet die weltweite Rolle des US-Dollars als Reservewährung. Die Welt benötigt momentan aber den Kapitalmarkt der USA, während die USA sich damit einen hohen Konsum finanzieren können. Ein Rückzug globaler Kapitalströme aus den USA würde daher nicht nur der amerikanischen Wirtschaft schaden, sondern auch das internationale Finanzsystem destabilisieren. Erste Anzeichen für einen solchen Vertrauensverlust sind bereits sichtbar. * Die richtige Reaktion Deutschlands und vor allem Europas auf diese Erratik und Unsicherheit ist gerade kein Attentismus, sondern ein proaktives Umgehen damit. Europa muss unter den Bedingungen einer großmachtpolitisch geprägten Welt selbst zu einer strategischen Großmacht werden - militärisch, ökonomisch und kulturell. Andernfalls droht der politische Bedeutungsverlust in einer zunehmend multipolaren Welt. * Während bei der militärischen Stärkung erste Schritte erkennbar sind, fehlt es an einer ambitionierten Innovations- und Wachstumspolitik. Besonders kritisch sind die Rückschritte Europas bei Bildung und kulturellem Einfluss: Statt globale Talente anzuziehen, dominierten Abschottungstendenzen und provinzielles Denken - etwa in der deutschen Hochschul- und Steuerpolitik. * Die vorliegende Analyse zeichnet ein besorgniserregendes Bild der transatlantischen Zukunft: Die USA unter Trumps zweiter Präsidentschaft könnten multilaterale Institutionen weiter schwächen, Europa nicht mehr als Partner, sondern als Rivalen betrachten. Ein nostalgischer Transatlantizismus ist deshalb keine tragfähige Option mehr. Ein Europa, das aus vielen Schweizen besteht, ist nicht überlebensfähig. Nur eine geeinte, gestaltungsfähige europäische Großmacht könnte dem globalen Machtvakuum etwas entgegensetzen. Die politische Existenz Europas steht auf dem Spiel. |
| Abstract: | * Economically, Trumpism creates multiple problems. Trump's protectionist agenda is inefficient and in some cases deliberately destructive. His reckless tariff and debt policy is jeopardizing the global role of the US dollar as a reserve currency. The world currently needs the US capital market, while the US can use it to finance a high level of consumption. A withdrawal of global capital flows from the US would therefore not only damage the American economy but also destabilize the international financial system. The first signs of such a loss of confidence can already be seen. * Trump's tariff threats against the EU, but also his 'One Big Beautiful Bill' are just the latest examples of such reckless policy measures. OBBB provides fiscal stimulus at the wrong time with bad distributional effects. The right response from Germany and, above all, Europe to this erraticism and uncertainty is not one of waiting around, but a proactive approach. Under the conditions of a world characterized by great power politics, Europe itself must become a strategic great power-militarily, economically, and culturally. Otherwise, there is a risk of losing political relevance in an increasingly multipolar world. * While the first steps towards strengthening the military have been taken, an ambitious innovation and growth agenda is missing. According to the Kiel Report, Europe is moving in the wrong direction in terms of educational and cultural influence: instead of attempting to attract global talent, isolationist tendencies and provincial thinking dominate-for example in higher education and tax policy. * The analysis paints a worrying picture of the transatlantic future: the USA under Trump's second presidency will further weaken multilateral institutions and no longer see Europe as a partner, but as a rival. Nostalgic transatlanticism is therefore no longer a viable option. * A Europe made up of many Switzerlands is not viable. Only a united, creative Europe will be able to stand up towards the rising authoritarian powers in the world. Europe's political existence is at stake. |
| Keywords: | Donald Trump, USA, Populismus, Wirtschaftspolitik |
| JEL: | D72 E60 E65 E66 H60 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkrp:323951 |
| By: | Hanwool Lee; Sara Yu; Yewon Hwang; Jonghyun Choi; Heejae Ahn; Sungbum Jung; Youngjae Yu |
| Abstract: | General-purpose sentence embedding models often struggle to capture specialized financial semantics, especially in low-resource languages like Korean, due to domain-specific jargon, temporal meaning shifts, and misaligned bilingual vocabularies. To address these gaps, we introduce NMIXX (Neural eMbeddings for Cross-lingual eXploration of Finance), a suite of cross-lingual embedding models fine-tuned with 18.8K high-confidence triplets that pair in-domain paraphrases, hard negatives derived from a semantic-shift typology, and exact Korean-English translations. Concurrently, we release KorFinSTS, a 1, 921-pair Korean financial STS benchmark spanning news, disclosures, research reports, and regulations, designed to expose nuances that general benchmarks miss. When evaluated against seven open-license baselines, NMIXX's multilingual bge-m3 variant achieves Spearman's rho gains of +0.10 on English FinSTS and +0.22 on KorFinSTS, outperforming its pre-adaptation checkpoint and surpassing other models by the largest margin, while revealing a modest trade-off in general STS performance. Our analysis further shows that models with richer Korean token coverage adapt more effectively, underscoring the importance of tokenizer design in low-resource, cross-lingual settings. By making both models and the benchmark publicly available, we provide the community with robust tools for domain-adapted, multilingual representation learning in finance. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.09601 |
| By: | Diermeier, Matthias; Engler, Jan; Fremerey, Melinda; Wansleben, Leon |
| Abstract: | Angesichts des hohen Niveaus sozioökonomischer Segregation in vielen deutschen Städten stellt sich die Frage nach der Verteilung sozialer Infrastruktur über soziodemografisch unterschiedlich geprägte Stadtteile. Unsere Analyse ist die erste, die georeferenzierte Daten zu Kindertagesstätten mit soziodemografischen Informationen aus 52 deutschen Städten und 2.613 Stadtteilen kombiniert. Im Kern der Untersuchung steht der Zusammenhang zwischen dem Angebot an Kindertagesstätten und dem Anteil der Sozialhilfeempfänger in den jeweiligen Quartieren. Unsere Ergebnisse zeigen, dass Stadtteile mit größeren sozioökonomischen Herausforderungen schlechter mit Kindertagesstätten versorgt sind. Dies liegt vor allem an der kostenintensiven Ausweitung von öffentlich bezuschussten Kitaangeboten gemeinnütziger Träger in sozioökonomisch bessergestellten Stadtteilen. Die Ungleichheit in der Kitaversorgung wäre in westdeutschen Städten noch ausgeprägter, wenn öffentliche Kitas nicht überproportional häufig in sozioökonomisch benachteiligten Stadtteilen angesiedelt wären. Diese ungleichen nahräumlichen Versorgungslagen tragen möglicherweise zu der sozial stark stratifizierten Inanspruchnahme von Kinderbetreuung in Deutschland bei - trotz umfangreicher öffentlicher Finanzierung. |
| Abstract: | The high level of socioeconomic segregation in many German cities gives rise to the question of how social infrastructure should be distributed across areas with different sociodemographic characteristics. Our analysis is the first to combine georeferenced data on daycare facilities for children with sociodemographic information from 52 German cities and 2, 613 districts. At the center of the study is the relationship between the availability of daycare facilities and the proportion of social welfare recipients in the corresponding area. Our findings show that areas with greater socioeconomic challenges are less well provided with daycare facilities for children. This is primarily due to the cost-intensive expansion of publicly subsidized daycare facilities run by non-profit organizations in socioeconomically better-off neighborhoods. The inequality in daycare provision would be even more pronounced in western German cities if municipal daycare facilities were not disproportionately located in socioeconomically disadvantaged neighborhoods. These unequal local supply situations may contribute to the socially highly stratified use of childcare in Germany - despite extensive public funding. |
| Keywords: | Kindertagesstätten, Kitaversorgung, Nachbarschaftsmerkmale, soziale Infrastruktur, Sozialraum, sozioökonomische Segregation, Tagesbetreuung, Ungleichheit, daycare facilities for children, daycare provision, neighborhood characteristics, social infrastructure, social space, socioeconomic segregation, daycare, inequality |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:mpifgd:323934 |
| By: | Sebastian Roché (PACTE - Pacte, Laboratoire de sciences sociales - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - IEPG - Sciences Po Grenoble-UGA - Institut d'études politiques de Grenoble - UGA - Université Grenoble Alpes); Simon Varaine (PACTE - Pacte, Laboratoire de sciences sociales - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - IEPG - Sciences Po Grenoble-UGA - Institut d'études politiques de Grenoble - UGA - Université Grenoble Alpes); Paul Le Derff (CED - Centre Émile Durkheim - IEP Bordeaux - Sciences Po Bordeaux - Institut d'études politiques de Bordeaux - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Can the behavior of civil servants with a large autonomy, the police, be regulated by law? In the case of the use of deadly force, the subject remains understudied in Europe. A 2017 law in France relaxed restrictions and allowed for the first time the national police to use weapons beyond self-defense. This quasi-experimental study examines the impact that this regulatory change, used as an exogenous shock, has had on the number of deaths of occupants of vehicles. The monthly number of killings has significantly increased for the national police (experimental group), who are directly affected by the new regulation, but not other forces unaffected by the regulation such as the French gendarmerie, a military status force (control group 1), and other police forces of two neighboring states (Germany, Belgium, control group 2 and 3). The findings hold after controlling for the variations in level of violence in society, and police exposure to and death in dangerous traffic violations during the study period. When using more conservative specifications, the observed increase in lethal shootings does not reach statistical significance due to a lack of statistical power related to the rarity of police lethal shootings in the European context. We recommend that national regulations governing the use of weapons by police more clearly and unambiguously embed the notions of proportionality and absolute necessity. |
| Keywords: | use of force, weapons, law and regulation, departmental policy, use of force weapons law and regulation departmental policy |
| Date: | 2025–09 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:halshs-05120493 |
| By: | Michael C. Best; Luigi Caloi; François Gerard; Evan Plous Kresch; Joana Naritomi; Laura Zoratto |
| Abstract: | Governments frequently use proxies for deservingness—tags—to implement progressive tax and transfer policies. These proxies are often imperfect, leading to misclassification and inequities among equally deserving individuals. This paper studies the efficiency effects of such misclassification in the context of the property tax system in Manaus, Brazil. We leverage quasi-experimental variation in inequity generated by the boundaries of geographic sectors used to compute tax liabilities and a large tax reform in a series of augmented boundary discontinuity designs. We find that inequities significantly reduce tax compliance. The elasticity of compliance with respect to inequity is between 0.12 and 0.25, accounting for half of the overall change in compliance at the boundaries. A simple model of presumptive property taxation shows how mistagging affects the optimal tax schedule, highlighting the opposite implications of responses to the level of taxation and to inequity for optimal tax progressivity. Interpreting our findings through the lens of the model implies that optimal progressivity is around 50% lower than it would be absent inequity responses. These results underscore the importance of inequity for public policy design, especially in contexts with low fiscal capacity. |
| JEL: | H21 H26 H71 O17 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34062 |
| By: | Justin Katz; Hunt Allcott |
| Abstract: | We present a new model of competition between digital media platforms with targeted advertising. The model adds new insights around how user heterogeneity and overlap, along with user and advertiser substitution patterns, determine equilibrium ad load. We apply the model to evaluate the proposed separation of Facebook and Instagram. We estimate structural parameters using evidence on diminishing returns to advertising from a new randomized experiment and information on user overlap, diversion ratios, and price elasticity from earlier experiments. In counterfactual simulations, a Facebook-Instagram separation increases ad loads, transferring surplus from platforms and users to advertisers, with limited total surplus effects. |
| JEL: | D12 L1 L4 L86 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34028 |
| By: | Severin Diepolder; Andrea Araldo; Tarek Chouaki; Santa Maiti; Sebastian H\"orl; Constantinos Antoniou |
| Abstract: | Shared Mobility Services (SMS), e.g., demand-responsive transport or ride-sharing, can improve mobility in low-density areas, which are often poorly served by conventional Public Transport (PT). Such improvement is generally measured via basic performance indicators, such as waiting or travel time. However, such basic indicators do not account for the most important contribution that SMS can provide to territories, i.e., increasing the potential, for users, to reach surrounding opportunities, such as jobs, schools, businesses, etc. Such potential can be measured by isochrone-based accessibility indicators, which count the number of opportunities reachable in a limited time, and are thus easy for the public to understand. % The potential impact of SMS on accessibility has been qualitatively discussed and implications on equity have been empirically studied. However, to date, there are no quantitative methods to compute isochrone-based indicators of the accessibility achieved via SMS. This work fills this gap by proposing a first method to compute isochrone accessibility of PT systems composed of conventional PT and SMS, acting as a feeder for access and egress trips to/from PT hubs. This method is grounded on spatial-temporal statistical analysis, performed via Kriging. It takes as input observed trips of SMS and summarizes them in a graph. On such a graph, isochrone accessibility indicators are computed. We apply the proposed method to a MATSim simulation study concerning demand-responsive transport integrated into PT, in the suburban area of Paris-Saclay. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.13100 |
| By: | Schultze, Michelle |
| Abstract: | Kyrgyzstan serves as a key case study for the broader Central Asia–Russia labor pipeline, which supported an estimated 8 million migrants annually in 2020. Prior to the Russo-Ukraine war, remittances from Russia accounted for approximately 30% of Kyrgyzstan’s GDP, driven by over 10% of its population working in Russia. However, understanding wartime migration dynamics is challenging due to suspected political interference in Russian data, restricted foreign access to this data, and the informality that characterizes Central Asian migration patterns. This study incorporates Yandex Wordstat, Google Trends, XGBoost (which outperforms other machine learning methods), and autoregressive models to "nowcast" missing data. The results reveal a push effect linked to war onset in February 2022 and war intensity. However, all three of the analyzed migration datasets suggest a potential delayed labor substitution effect as Central Asian migrants fill vacancies left by conscripted Russian workers, proxied by casualty data from Mediazona and the BBC. The study also examines remittance trends, which seem to increase along with the labor substitution effect after a two-month lag. These results are robust to Russia- and Kyrgyzstan-side socioeconomic controls such as wage levels and population dynamics. This study provides new insight into the largely opaque Central Asia–Russia labor pipeline, a critical element in development policymaking for both regions. It also introduces a novel methodology for nowcasting migration trends, particularly through Yandex Wordstat, which has been largely overlooked in English-language scholarship. |
| Date: | 2025–07–24 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:z2wch_v1 |
| By: | Alejandro Rodriguez Dominguez |
| Abstract: | This paper challenges the claim that causal factor modeling is a necessary condition for investment efficiency. Through formal analysis and empirical counterexamples, we show that predictive models, even when structurally misspecified, can produce directionally accurate signals, valid mean-variance frontiers, and positive Sharpe ratios. Contrary to the assertion that causal omission leads to systematic inefficiency, we demonstrate that calibration errors, not lack of causal structure, are the primary source of performance degradation. Drawing from statistical learning theory and robust optimization, we argue that predictive validity, not causal interpretability, is the key metric in portfolio construction. Our theoretical results distinguish between signal ranking and sizing, and our experiments confirm that portfolio optimization remains viable even under omitted variables and nonlinearity. These findings support a predictive-first modeling philosophy: models may be wrong in structure, yet still useful in practice. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.23138 |
| By: | Melentyeva, Valentina; Riedel, Lukas |
| Abstract: | We show that the widespread approach to estimate the career costs of motherhood - so called "child penalties" - is prone to produce biased results, as it pools first-time mothers of all ages without accounting for their differences in characteristics and outcomes. We propose a novel method building on the recent advances in the difference-in-differences literature to address this issue. Applied to German administrative data, our method yields 30 percent larger post-birth earnings losses than the conventional approach. We document meaningful effect heterogeneity by maternal age in both magnitude and interpretation, highlighting its key role in understanding the impact of motherhood. |
| Keywords: | child penalty, maternal labor supply, heterogeneous treatment effects, event study |
| JEL: | J13 J16 J31 C23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:zewdip:321862 |
| By: | Nicko A Magnaye (Mindoro State University); John Rex T Saguid (Mindoro State University); Rizalyn S. Cartagena (Mindoro State University); Shella V Bruit (Mindoro State University); Nannette A Olarte (Mindoro State University); Alexandra M Cracicas (Mindoro State University) |
| Abstract: | Science's field of artificial intelligence is concerned with giving machines more human-like ways to solve challenging issues. The area of computer science focuses on getting computers to behave more like people. This typically entails taking traits from human intelligence and applying them as algorithms in a way that is computer friendly. Depending on the defined needs, a more or less flexible or efficient strategy might be used, which affects how artificial the intelligent behavior seems. The demand to create new technology to aid in bettering care for the world's aging population is increasing. Numerous social, economic, and health issues need to be resolved due to how quickly the older adult population is expanding. AI can be very helpful in this area by assisting the healthcare system in meeting the rising demand for senior healthcare services. In this study, we'll examine how AI is helping seniors take better care of themselves.AI-powered products and technologies can assist seniors in maintaining their independence while also improving their quality of life. But, AI may employ threats to senior citizens. They may require support in coping with new technology and managing AI-powered products. Furthermore, elders may be particularly concerned about data privacy and the possibility of misuse or malfunction.AI can benefit seniors in many areas, but seniors must cautiously approach it. Senior citizens must have access to the necessary training and support to use AI safely and successfully. Furthermore, improvement plans to prevent issues such as data protection and ensure that AI is used legally are necessary.Concerning the keywords used, the acronyms and terms that were provided in the some manner were advantageous to the reader in order to educate themselves on the ideas that have been visible in the text while he was reading it. |
| Keywords: | ARTIFICIAL INTELLIGENCE A BOON BANE SENIOR CITIZEN, ARTIFICIAL INTELLIGENCE, A BOON, BANE, SENIOR CITIZEN |
| Date: | 2023–07–02 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05090662 |
| By: | Marius Protte |
| Abstract: | This study replicates and adapts the experiment of Hoelzl and Rustichini (2005), which examined overplacement, i.e., overconfidence in relative self-assessments, by analyzing individuals' voting preferences between a performance-based and a lottery-based bonus payment mechanism. The original study found underplacement - the majority of their sample apparently expected to perform worse than others - in difficult tasks with monetary incentives, contradicting the widely held assumption of a general human tendency toward overconfidence. This paper challenges the comparability of the two payment schemes, arguing that differences in outcome structures and non-monetary motives may have influenced participants' choices beyond misconfidence. In an online replication, a fixed-outcome distribution lottery mechanism with interdependent success probabilities and no variance in the number of winners - designed to better align with the performance-based payment scheme - is compared against the probabilistic-outcome distribution lottery used in the original study, which features an independent success probability and a variable number of winners. The results align more closely with traditional overplacement patterns than underplacement, as nearly three-fourths of participants prefer the performance-based option regardless of lottery design. Key predictors of voting behavior include expected performance, group performance estimations, and sample question outcomes, while factors such as social comparison tendencies and risk attitudes play no significant role. Self-reported voting rationales highlight the influence of normative beliefs, control preferences, and feedback signals beyond confidence. These results contribute to methodological discussions in overconfidence research by reassessing choice-based overconfidence measures and exploring alternative explanations for observed misplacement effects. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.15568 |
| By: | Berlingieri, Francesco; d'Hombres, Béatrice; Kovacic, Matija |
| Abstract: | This paper explores the relationship between loneliness, trust, and populist voting across both extremes of the ideological spectrum. The contribution of this research is mainly two-fold. First, it considers different dimensions of loneliness and accounts for its predetermined component stemming from social isolation in childhood and adverse childhood experiences. Second, it disentangles the effects of loneliness and trust by incorporating actual trust behaviour from a large-scale trust game experiment conducted in 27 European member states, involving more than 25, 000 individuals. The richness of the data allows to account for and disentangle the impact of competitive explanatory factors such as emotions, objective social isolation, social media use and economic preferences. The main findings suggest the following: (i) social loneliness significantly impacts populist voting, particularly on the extreme right, whereas the emotional dimension of loneliness is associated with more left-leaning, but non-populist, voting preferences; (ii) higher levels of actual trust are associated with lower support for right-wing populist parties; (iii) loneliness and trust operate through distinct channels: loneliness exerts a greater impact on women and older individuals, while trust plays a more significant role among men and middle-aged individuals, and (iv) the effect of social loneliness on support of populist parties is significantly attenuated in contexts with a history of recurrent economic crises, suggesting a potential experience-based learning mechanism. |
| Keywords: | Loneliness, interpersonal trust, political polarisation, populism |
| JEL: | D72 D91 P00 C91 Z13 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1634 |
| By: | Irekponor, Victor; Oshan, Taylor M. |
| Abstract: | Spatially varying coefficient (SVC) models are often regarded as “big models” due to the extensive volume of outputs that they produce. This can make it challenging to identify important trends, and maps are typically used when interpreting results from these models. However, visualization best practices are often overlooked, and uncertainty is not incorporated, leading to misinterpretation and complicating pattern extraction and comparison. This has important implications for reproducibility and replicability (R&R) in SVC models, which has received limited attention in the literature. Addressing these gaps requires a structured approach that enhances interpretability, facilitates model comparison, and effectively incorporates model uncertainty when analyzing SVC model output. This study introduces svc-viz, an open-source Python tool that codifies best practices into a standardized framework for interpreting and communicating SVC model results. By integrating established visualization principles, svc-viz improves clarity and reduces the risk of misinterpretation. Additionally, svc-viz introduces strategies for visualizing model uncertainty and assessing replicability across datasets, methods, and model inputs. The utility of the tool is demonstrated using a 2020 U.S. presidential election dataset. By formalizing visualization strategies, this study advances reproducibility, replicability, and uncertainty consideration in multiscale local modeling, providing researchers with a more robust framework for analyzing and communicating spatial relationships. |
| Date: | 2025–07–21 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:jgf75_v1 |
| By: | Sharma, Pyaar Ki Raat; Yokai, Nekobaba; Lóng, Xiǎngxiàng |
| Abstract: | This paper explores the role of telecommunications infrastructure as an emerging social determinant of health, focusing on its relationship with life expectancy. While traditional determinants such as income, education, and healthcare access remain vital, the integration of digital infrastructure has introduced new pathways through which health outcomes are shaped. Drawing on recent literature and guided by a conceptual framework that incorporates digital access, labor market informality, and institutional capacity, this study argues that digital inequality mirrors and exacerbates existing health disparities. The paper highlights how the interplay of these structural factors can explain why improved infrastructure does not uniformly translate into longer life expectancy. Emphasis is placed on the need for multidimensional policy interventions that promote digital inclusion, address informality, and strengthen institutions. The findings underscore the importance of treating digital infrastructure not merely as a technical issue, but as a central component of health equity in the digital age. |
| Keywords: | Life Expectancy, Digital Inequality, Telecommunications Infrastructure, Informality, Health Equity |
| JEL: | E0 |
| Date: | 2024–04–06 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125303 |
| By: | Guio, Armando |
| Abstract: | En este informe se examinan el desarrollo y los impactos de los entornos regulatorios de prueba en países de ingreso bajo e ingreso mediano. El trabajo, que busca arrojar luz sobre la viabilidad y la eficacia de estos innovadores espacios, contiene un análisis exhaustivo dirigido a los responsables de la formulación de políticas, las organizaciones internacionales y las autoridades nacionales que están evaluando la posibilidad de poner en marcha entornos regulatorios de prueba para nuevos sectores y tecnologías. Uno de los aspectos clave que se analizan es el surgimiento de estos entornos como instrumentos vitales para la gestión de tecnologías disruptivas como la inteligencia artificial, las redes 5G y las criptomonedas. Tras popularizarse entre las autoridades financieras de los países de ingreso alto, la adopción de este instrumento se ha extendido, lo que ha dado lugar a investigaciones sobre sus beneficios tangibles en varias economías. En este informe se subraya la necesidad de adoptar un enfoque meticuloso al evaluar el nivel de preparación y los potenciales efectos de los entornos de prueba y se presenta la herramienta de Evaluación de la Madurez para los Entornos Regulatorios de Prueba (Regulatory Sandbox Maturity Assessment (RESMA)), un instrumento diseñado para evaluar el nivel de preparación de un país para poner en marcha iniciativas de este tipo. Mediante estudios de caso y entrevistas con funcionarios públicos, el informe destaca la importancia de contar con un marco de políticas claro y equipos interdisciplinarios y de realizar esfuerzos sostenidos para garantizar el éxito y los impactos de los entornos regulatorios de prueba. Además, se hace hincapié en la importancia de las alianzas estratégicas y las iniciativas colaborativas de ejecución para mejorar la eficacia de estos espacios de experimentación regulatoria. |
| Date: | 2025–02–19 |
| URL: | https://d.repec.org/n?u=RePEc:ecr:col022:81295 |
| By: | Engels, Barbara; Scheufen, Marc; Schmitz, Edgar |
| Abstract: | Deutschland muss seine wirtschaftliche Leistungsfähigkeit in einem schwierigen Umfeld sichern. Der Mangel an Fachkräften, die stagnierende Produktivität und eine schwächelnde Innovationstätigkeit bedrohen Wachstum und Wohlstand. Künstliche Intelligenz (KI) kann ein Schlüssel zur Bewältigung dieser Herausforderungen sein. Dafür muss sie allerdings von vielen Unternehmen umfassend eingesetzt werden. Diese Studie untersucht den aktuellen Stand der KI-Nutzung in deutschen Unternehmen basierend auf einer Befragung von 1.038 Unternehmen im Rahmen des IW-Zukunftspanels. Derzeit setzen 37 Prozent der befragten Unternehmen KI ein. Große Unternehmen nutzen mit 66 Prozent wesentlich häufiger KI als kleine Unternehmen (36 Prozent). Hinsichtlich der Branchen sind unternehmensnahe Dienstleister mit 55 Prozent besonders häufig KI-Nutzer, gefolgt vom Maschinenbau, der Elektroindustrie und dem Fahrzeugbau mit knapp 40 Prozent. Im Gegensatz dazu setzen Unternehmen aus Branchen wie Bauwirtschaft, Großhandel und Logistik KI deutlich seltener ein (unter 25 Prozent). Die befragten Unternehmen nutzen KI hauptsächlich zur Automatisierung von Routinearbeiten, Unterstützung bei komplexen Aufgaben und zur Qualitätsverbesserung. Vor allem generative KI ist beliebt. Allerdings erfolgt der KI-Einsatz meist nur punktuell in einzelnen Unternehmensbereichen und selten unternehmensweit. Dass die befragten Unternehmen vor allem kostenfreie KI-Tools einsetzen und deutlich seltener KITools einkaufen oder selbst entwickeln, deutet ebenfalls darauf hin, dass die KI-Nutzung in der deutschen Wirtschaft insgesamt bislang eher oberflächlich ist. Die Studie empfiehlt konkrete Maßnahmen, um KI flächendeckend zu implementieren und die wirtschaftlichen Chancen zu nutzen: Bildungsoffensiven, gezielte finanzielle Förderung, intelligente Regulierungsumsetzung und eine verbesserte digitale Infrastruktur sind zentrale Hebel. Zudem sollte Deutschland sein Geschäftsmodell der industriellen Wertschöpfung mit den Potenzialen der KI verzahnen und dabei eigene, europäisch geprägte KI-Lösungen entwickeln. Gelingt es Deutschland, KI "Made in Germany" zum Qualitätssiegel für Innovation und Zuverlässigkeit zu machen, könnte KI tatsächlich zu einer tragenden Säule nachhaltigen Wachstums und Wohlstands werden. |
| Abstract: | Germany has to secure its economic performance in a difficult environment. The shortage of skilled labour, stagnating productivity and weakening innovation are threatening growth and prosperity. Artificial intelligence (AI) can be a key to overcoming these challenges. However, it needs to be used extensively by many companies. This study analyses the current status of AI use in German companies based on a survey of 1, 038 companies as part of the IW Future Panel. Currently, 37 per cent of the companies surveyed use AI. At 66 per cent, large companies use AI much more frequently than small companies (36 per cent). In terms of sectors, business-related service providers are particularly frequent users of AI at 55 per cent, followed by mechanical engineering, the electrical industry and vehicle construction at just under 40 per cent. In contrast, companies from sectors such as construction, wholesale and logistics use AI much less frequently (less than 25 per cent). The companies surveyed mainly use AI to automate routine work, support complex tasks and improve quality. Generative AI is particularly popular. However, AI is usually only used selectively in individual areas of the company and rarely company-wide. The fact that surveyed companies predominantly use free-of-charge AI tools, and less frequently purchase or develop their own tools, also indicates that the overall adoption of AI in the German economy is rather superficial so far. The study provides specific recommendations for achieving broader AI implementation and leveraging its economic opportunities: targeted educational initiatives, focused financial incentives, intelligent regulatory frameworks, and improved digital infrastructure are key levers. Moreover, Germany should integrate its industrial value-creation model with the potential of AI, developing distinctly European AI solutions. If Germany succeeds in establishing AI "Made in Germany" as a hallmark for innovation and reliability, artificial intelligence could indeed become a cornerstone of sustainable economic growth and prosperity. |
| Keywords: | Künstliche Intelligenz, Unternehmen, Komparativer Vorteil, Internationaler Wettbewerb, Deutschland |
| JEL: | O33 M15 O38 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iwkrep:321854 |
| By: | Kase, Hanno; Rigato, Rodolfo Dinis |
| Abstract: | We introduce an estimated medium scale Heterogeneous-Agent New Keynesian model for forecasting and policy analysis in the Euro Area and discuss the applications of this type of models in central banks, focusing on two main exercises. First, we examine an alternative scenario for monetary policy during the early 2020s inflationary episode, showing that earlier hikes in interest rates would have affected more strongly households at the lower end of the wealth distribution, whose consumption our model suggests was already depressed relative to the rest of the population. To provide intuition for this result, we introduce a new decomposition of the effects of monetary policy on consumption across the wealth distribution. Second, we show that introducing heterogeneous households does not come at the cost of forecasting accuracy by comparing the performance of our model to its exact representative-agent counterpart and demonstrating nearly identical results in predicting key aggregate variables. JEL Classification: D31, E12, E21, E52 |
| Keywords: | forecasting, heterogeneous-agent New Keynesian models, inequality, monetary policy |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253086 |
| By: | Hobson, Christopher |
| Abstract: | Faced with a continually mounting array of shocks, surprises and shifts, there is an understandable search for frames to describe these confusing conditions. A combination of the collapse of previous certainties with the lack of a new paradigm solidifying has led many to depict the present moment as an interregnum. This is not a neutral term, to use it is to bring forth the poetic phrasing of Antonio Gramsci: ‘the old is dying and the new cannot be born’. Through a genealogical engagement with Gramsci’s prison notebook entry, this paper traces the remarkable trajectory of the term from obscurity to being adopted by commentators across the political spectrum. The paper considers Gramsci’s original prison notebook entry, observes the lack of engagement with it during the 1960s and 70s when other parts of his work were picked up. Indeed, it was only following the Great Financial Crisis of 2008, and the entry being coterminously invoked by two influential scholars, Zygmunt Bauman and Slavoj Žižek. The paper examines how Bauman and Žižek each offered a template for how interregnum has been used in the years since. In the first mode, as represented by Bauman, Gramsci’s entry is placed at the beginning of the analysis and then serves as a frame for the subsequent discussion of maladies identified. In the second mode, as found in Žižek, interregnum appears at the end as part of the argument’s grand finale. In both renditions, Gramsci is deployed to buttress already established arguments. The paper surveys some more interesting and provocative engagements with the entry in recent years presented by Carlo Bordoni, Wolfgang Streeck and Adam Tooze. These are an exception to the more common trend of Gramsci’s interregnum being flattened and thinned out, reduced to an analytical meme. Bemoaning the death of the ‘old’ and the rise of ‘monsters’ is much easier than seriously reckoning with the contradictions and difficulties of an expanding empty space, one devoid of historical guarantees or clear precedents. |
| Date: | 2025–07–23 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:gzhrq_v1 |
| By: | Beyer, Andreas; Nobile, Lorenzo |
| Abstract: | Using a novel worldwide dataset of 5, 264 syndicated loans issued to 329 firms from 2006 to 2021, we study how climate-related litigation risk affects firm’s cost of borrowing. We find robust empirical evidence that firms targeted by climate lawsuits pay significantly higher spreads on their bank loans. These effects are more pronounced for firms with weaker environmental performance and higher ESG controversies. The results suggest that lender’s view climate litigation as a material risk factor, which is increasingly priced into debt contracts. JEL Classification: G21, G32, Q56, K32 |
| Keywords: | bank loans, climate lawsuits, litigation risk, loan spreads |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253087 |
| By: | Junjie Zhao; Chengxi Zhang; Chenkai Wang; Peng Yang |
| Abstract: | Reinforcement learning (RL) has successfully automated the complex process of mining formulaic alpha factors, for creating interpretable and profitable investment strategies. However, existing methods are hampered by the sparse rewards given the underlying Markov Decision Process. This inefficiency limits the exploration of the vast symbolic search space and destabilizes the training process. To address this, Trajectory-level Reward Shaping (TLRS), a novel reward shaping method, is proposed. TLRS provides dense, intermediate rewards by measuring the subsequence-level similarity between partially generated expressions and a set of expert-designed formulas. Furthermore, a reward centering mechanism is introduced to reduce training variance. Extensive experiments on six major Chinese and U.S. stock indices show that TLRS significantly improves the predictive power of mined factors, boosting the Rank Information Coefficient by 9.29% over existing potential-based shaping algorithms. Notably, TLRS achieves a major leap in computational efficiency by reducing its time complexity with respect to the feature dimension from linear to constant, which is a significant improvement over distance-based baselines. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.20263 |
| By: | Md Talha Mohsin |
| Abstract: | Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide variety of Financial Natural Language Processing (FinNLP) tasks. However, systematic comparisons among widely used LLMs remain underexplored. Given the rapid advancement and growing influence of LLMs in financial analysis, this study conducts a thorough comparative evaluation of five leading LLMs, GPT, Claude, Perplexity, Gemini and DeepSeek, using 10-K filings from the 'Magnificent Seven' technology companies. We create a set of domain-specific prompts and then use three methodologies to evaluate model performance: human annotation, automated lexical-semantic metrics (ROUGE, Cosine Similarity, Jaccard), and model behavior diagnostics (prompt-level variance and across-model similarity). The results show that GPT gives the most coherent, semantically aligned, and contextually relevant answers; followed by Claude and Perplexity. Gemini and DeepSeek, on the other hand, have more variability and less agreement. Also, the similarity and stability of outputs change from company to company and over time, showing that they are sensitive to how prompts are written and what source material is used. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.22936 |
| By: | International Monetary Fund |
| Abstract: | While gradually declining in market share, Europe remains the second largest asset management market globally. The industry is mostly concentrated in a few member states (MS) with a significant amount of delegation of portfolio management services outside of the EU. The majority of funds are held by institutional investors, and the share of funds held by investors outside of the EU continues to grow. |
| Date: | 2025–07–25 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfscr:2025/212 |
| By: | Montano, Pierina; Quineche, Ricardo; Tipo, Royer |
| Abstract: | This study challenges the conventional assumption of uniform monetary policy transmission by examining interest rate pass‑through across the conditional distribution using quantile cointegration. Using U.S. data from 1994–2024, we estimate long‑run relationships between the federal funds rate and both lending rates and Treasury yields at quantiles 0.1–0.9, employing the Phillips–Hansen fully modified quantile estimator with quantile CUSUM stability tests. We find that transmission is fundamentally asymmetric and varies systematically with economic conditions. Under conventional policy measures, pass‑through mechanisms display marked instability, with cointegration frequently breaking down in crisis periods when policy effectiveness is most crucial. The prime rate remains stably linked to the policy rate only at select quantiles, while Treasury yields show clear maturity‑dependent patterns—medium‑term maturities are generally more resilient than short‑ or long‑term yields. Temporal robustness checks reveal that transmission was more unstable during the pre‑Global Financial Crisis era than often assumed, but markedly more stable in the pre‑COVID period, consistent with institutional learning and enhanced policy frameworks. Using the Wu‑Xia shadow rate in place of the federal funds rate delivers complete stability for the prime rate and substantial stability gains for most Treasury maturities. This indicates that many breakdowns observed under conventional measures reflect policy‑measurement limitations at the zero lower bound rather than genuine transmission failures. The results suggest central banks should adopt state‑contingent frameworks that recognize transmission asymmetries, deploy unconventional tools proactively in stressed conditions, and invest in institutional improvements that can sustain transmission effectiveness across diverse economic environments. |
| Keywords: | Quantile cointegration, Monetary policy transmission, Interest rate pass-through, Asymmetric interest rate effects |
| JEL: | E43 C32 C21 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:323756 |