Hasil untuk "Labor market. Labor supply. Labor demand"

Heather CONNOLLY

Fedor Shabashev

Prediction markets have gained adoption as on-chain mechanisms for aggregating information, with platforms such as Polymarket demonstrating demand for stablecoin-denominated markets. However, denominating in non-interest-bearing stablecoins introduces inefficiencies: participants face opportunity costs relative to the fiat risk-free rate, and Bitcoin holders in particular lose exposure to BTC appreciation when converting into stablecoins. This paper explores the case for prediction markets denominated in Bitcoin, treating BTC as a deflationary settlement asset analogous to gold under the classical gold standard. We analyse three methods of supplying liquidity to a newly created BTC-denominated prediction market: cross-market making against existing stablecoin venues, automated market making, and DeFi-based redirection of user trades. For each approach we evaluate execution mechanics, risks (slippage, exchange-rate risk, and liquidation risk), and capital efficiency. Our analysis shows that cross-market making provides the most user-friendly risk profile, though it requires active professional makers or platform-subsidised liquidity. DeFi redirection offers rapid bootstrapping and reuse of existing USDC liquidity, but exposes users to liquidation thresholds and exchange-rate volatility, reducing capital efficiency. Automated market making is simple to deploy but capital-inefficient and exposes liquidity providers to permanent loss. The results suggest that BTC-denominated prediction markets are feasible, but their success depends critically on the choice of liquidity provisioning mechanism and the trade-off between user safety and deployment convenience.

Habib Badawi

This paper analyzes the intersection of presidential authority and cryptocurrency markets during Donald J. Trump's second term (2025-2029). We examine developments from 2024 through October 2025, focusing on how executive influence, family business ventures, and digital assets became intertwined in ways that blurred boundaries between public office and private profit. Using a mixed-methods approach that combines quantitative market data with qualitative institutional assessment, we identify politically linked digital assets as a distinct class characterized by reflexive valuations, asymmetric risk distribution, and systemic vulnerabilities. The Trump family's integrated cryptocurrency ecosystem reached peak valuations exceeding eleven billion dollars before collapsing by more than one trillion in market capitalization following a tariff announcement in October 2025. Results highlight conflicts of interest, failures in market microstructure, and the emergence of political finance as a monetizable phenomenon in the digital age. The study contributes to understanding how presidential signaling reshapes capital flows, how politically branded tokens function as quasi-currencies, and how sudden policy actions can trigger cascading liquidations across global digital asset systems.

Nayar López Castellanos

En este texto se realiza un análisis sobre los aspectos más relevantes que han caracterizado al gobierno de Andrés Manuel López Obrador en los últimos cinco años. En el contexto de la llamada Cuarta Transformación, México ha transitado por una intensa etapa política en la que se han generado cambios importantes a pesar de no trastocar las estructuras del capitalismo. De igual forma, se ubica el proceso mexicano en el contexto regional destacando diferencias y similitudes con respecto a otros países que han transitado por gobiernos que se ubican del centro hacia la izquierda. Palabras clave: México; AMLO; Izquierda; América Latina.

Abd. Kholik Khoerulloh, Holis Abdul Aziz

Society 5.0 is resulting in transformation across a wide range of sectors, including manufacturing, education, healthcare, and services. Through the adoption of artificial intelligence, machines can carry out tasks that previously could only be performed by humans, resulting in significant changes in the types of jobs and skills available in the labor market. This research aims to detail and identify how technological changes affect the labor market, as well as explore solutions and strategies to capitalize on opportunities and deal with challenges that arise from these changes for society's overall well-being. This research uses a literature study method with a predictive approach. The results showed that in the era of Society 5.0, people must improve their skills through education and training to adapt to the changes. Cross-sectoral cooperation between the government, the private sector, and the community is crucial. Joint efforts to formulate supportive policies and innovation in creating new sustainable jobs are vital to mitigating the negative impacts and harnessing the positive potential of technological change in the labor market. This research is expected to have a significant impact, ranging from policy development to improving social welfare, by comprehensively understanding how technology affects life and work in modern society.

Pedro Rossi

Transcrição da conferência do Prof. Dr. Pedro Rossi na mesa de abertura do V INTERCRÍTICA (10 e 11 de outubro de 2022) que foi realizado nas dependências da Escola Politécnica de Saúde Joaquim Venâncio da Fundação Oswaldo Cruz (EPSJV/Fiocruz) e da Universidade Estadual do Rio de Janeiro (UERJ).

Tale Hellevik, Katharina Herlofson, Axel West Pedersen

Det er av stor interesse å kunne måle presist hvordan den typiske avgangsalderen utvikler seg på samfunnsnivå og hvordan den eventuelt varierer mellom grupper på individnivå. I denne artikkelen redegjør vi for ulike fremgangsmåter for å måle individers tidspunkt for avgang fra yrkeslivet. Eksemplene er hentet fra nyere internasjonal og norsk forskning. Videre sammenlikner vi resultater fra to operasjonaliseringer av avgangstidspunkt basert på henholdsvis surveydata og registeropplysninger. Vi finner at samsvaret er stort på aggregert nivå, mens det er langt svakere på individnivå med betydelige systematiske forskjeller i samsvaret mellom ulike kategorier av yrkesaktive.

Konstantin Koerner, Mathilde Le Moigne

Abstract How does a firm’s foreign direct investment (FDI) in a low-wage country change its onshore task demand in a high-wage country? Is the shift more intensive for jobs that the literature has designated offshorable? We address these questions using a matched difference-in-differences (DiD) approach with data on German firms that have similar propensities to conduct FDI in the Czech Republic. Our novel matching procedure draws on post-lasso logit estimates and shows that high task intensities of managing, administration, and labor legislation play a major role in firms’ engagement in international expansion. The outcomes of the DiD estimation show that after acquiring a foreign affiliate, multinational enterprises (MNEs) increase the intensities of their activities typical of headquarters such as managing, analyzing, and negotiating relative to the corresponding task intensities among non-MNEs. We also find sector-specific decreases, such as a reduction in typical production tasks (monitoring, producing, measuring) in manufacturing MNEs or typical service tasks (informing, medical, repairing) in service MNEs.

Yuanzheng Li, Xinxin Long, Yang Li et al.

Industrial demand response (IDR) plays an important role in promoting the utilization of renewable energy (RE) in power systems. However, it will lead to power adjustments on the supply side, which is also a non-negligible factor in affecting RE utilization. To comprehensively analyze this impact while enhancing RE utilization, this paper proposes a power demand-supply cooperative response (PDSCR) strategy based on both day-ahead and intraday time scales. The day-ahead PDSCR determines a long-term scheme for responding to the predictable trends in RE supply. However, this long-term scheme may not be suitable when uncertain RE fluctuations occur on an intraday basis. Regarding intraday PDSCR, we formulate a profit-driven cooperation approach to address the issue of RE fluctuations. In this context, unreasonable profit distributions on the demand-supply side would lead to the conflict of interests and diminish the effectiveness of cooperative responses. To mitigate this issue, we derive multi-individual profit distribution marginal solutions (MIPDMSs) based on satisfactory profit distributions, which can also maximize cooperative profits. Case studies are conducted on an modified IEEE 24-bus system and an actual power system in China. The results verify the effectiveness of the proposed strategy for enhancing RE utilization, via optimizing the coordination of IDR flexibility with generation resources.

Ekzhin Ear, Jose L. C. Remy, Shouhuai Xu

Cyber ranges mimic real-world cyber environments and are in high demand. Before building their own cyber ranges, organizations need to deeply understand what construction supplies are available to them. A fundamental supply is the cyber range architecture, which prompts an important research question: Which cyber range architecture is most appropriate for an organization's requirements? To answer this question, we propose an innovative framework to specify cyber range requirements, characterize cyber range architectures (based on our analysis of 45 cyber range architectures), and match cyber range architectures to cyber range requirements.

Amanda Moreira da Silva

O livro de José Rodrigues, intitulado Os empresários e a educação superior, é pequeno na forma, mas grandioso no propósito e no conteúdo. Resgatar essa obra 15 anos depois de publicada é tarefa fundamental para todos aqueles que se propõem a entender os desafios da educação brasileira. Um estudo importante de ser retomado nos dias de hoje, quando novas dinâmicas de mercantilização e financeirização se inserem na educação superior e aprofundam o caráter privatizante das reformas em curso há mais de cinquenta anos no Brasil. O estatuto de clássico e ao mesmo tempo a atualidade do referido livro pode ser verificado pela riqueza de definições, princípios e conceitos apresentados e que o autor busca difundir ao longo de sua trajetória pujante no campo educacional, com contribuições importantíssimas para as reflexões acerca do empresariamento da educação. Palavras-chave: Empresariamento da educação. Educação superior. Mercantilização da educação.

Angela Tamberlini

No momento que o pensamento ultraneoliberal e ultraconservador se impõe temporariamente sobre as diferentes sociedades do planeta, apresentar o contraponto da investida destes pensamentos e do capital é de fundamental importância, o que demonstra a presença de muitas lutas e resistências, compondo outros discursos, mesmo que não hegemônico, mas que se faz necessário o reconhecimento, explicitando que um outro mundo, uma outra educação é possível.

PATRICIA DUARTE

O presente trabalho problematiza o slogan da inovação na educação. A partir de um levantamento bibliográfico, identificamos que a questão remonta ao contexto de agravamento da crise do capital nas décadas de 1960 e 1970, caracterizando uma retomada da teoria do capital humano. O levantamento documental preliminar, no sítio do Ministério da Educação (MEC) e do Centro de Inovação para a Educação Brasileira (CIEB), indica que este tem despontado enquanto agente e referência para o projeto de educação da classe dominante para os trabalhadores do século XXI. Palavras-chave: Centro de Inovação para a Educação Brasileira. Políticas públicas. Inovação em educação.

Jesus Jorge Pérez García

En el texto presentamos resultados de la investigación del doctorado realizada en comunidades rurales en Cuba (2010 – 2015).Tomando o materialismo histórico dialéctico como método, a partir das categorías memoria y experiencia desde la revolución cubana hasta la actualidad; considerando los legados de generaciones como: campesinos y líderes revolucionarios, simientes de un proceso de construcción colectiva que atendió la formación de los recursos humanos y ubicó al hombre en sitial prioritario, con métodos de participación colectiva, en articulación con los adelantos de la técnica, la ciencia y la preservación del medio ambiente en equilibrio entre la sociedad-naturaleza-economía. Palabras-clave: Agroecología. Campesino-campesino. Socio ambiental. Participación.

Beatrice Schütte, Lotta Majewski

Artificial intelligence (AI) is an integral part of our everyday lives, able to perform a multitude of tasks with little to no human intervention. The number of devices with integrated digital features on the market, including consumer products, is constantly increasing. Many legal issues related to this phenomenon have not been comprehensively addressed or resolved yet. Also, the question arises whether the existing legal rules on damages liability can resolve cases involving AI so as to make case outcomes predictable across the Union. The EU institutions are in the process of evaluating if and to what extent new legislation regarding AI is needed, envisioning a European approach to avoid fragmentation of the Single Market. This article critically analyses the most relevant preparatory documents and proposals with regard to civil liability for AI issued by EU legislators. Moreover, it is crucial to clarify the applicability of existing EU legislation such as the framework concerning product safety and product liability to new technologies. To achieve a more predictable framework for the future, the legislation applicable to AI must be aligned and it must be evident which rules are applicable in which situation. The envisioned level playing field throughout the Single Market justifies harmonisation of many aspects of damages liability for AI-related harm. In the process, particular AI characteristics should be carefully considered in terms of questions such as causation, fault, and the burden of proof.

Xi Chen, Jiameng Lyu, Yining Wang et al.

In addition to maximizing the total revenue, decision-makers in lots of industries would like to guarantee balanced consumption across different resources. For instance, in the retailing industry, ensuring a balanced consumption of resources from different suppliers enhances fairness and helps main a healthy channel relationship; in the cloud computing industry, resource-consumption balance helps increase customer satisfaction and reduce operational costs. Motivated by these practical needs, this paper studies the price-based network revenue management (NRM) problem with both demand learning and fair resource-consumption balancing. We introduce the regularized revenue, i.e., the total revenue with a balancing regularization, as our objective to incorporate fair resource-consumption balancing into the revenue maximization goal. We propose a primal-dual-type online policy with the Upper-Confidence-Bound (UCB) demand learning method to maximize the regularized revenue. We adopt several innovative techniques to make our algorithm a unified and computationally efficient framework for the continuous price set and a wide class of balancing regularizers. Our algorithm achieves a worst-case regret of $\widetilde O(N^{5/2}\sqrt{T})$, where $N$ denotes the number of products and $T$ denotes the number of time periods. Numerical experiments in a few NRM examples demonstrate the effectiveness of our algorithm in simultaneously achieving revenue maximization and fair resource-consumption balancing

Dragos Gorduza, Xiaowen Dong, Stefan Zohren

Understanding stock market instability is a key question in financial management as practitioners seek to forecast breakdowns in asset co-movements which expose portfolios to rapid and devastating collapses in value. The structure of these co-movements can be described as a graph where companies are represented by nodes and edges capture correlations between their price movements. Learning a timely indicator of co-movement breakdowns (manifested as modifications in the graph structure) is central in understanding both financial stability and volatility forecasting. We propose to use the edge reconstruction accuracy of a graph auto-encoder (GAE) as an indicator for how spatially homogeneous connections between assets are, which, based on financial network literature, we use as a proxy to infer market volatility. Our experiments on the S&P 500 over the 2015-2022 period show that higher GAE reconstruction error values are correlated with higher volatility. We also show that out-of-sample autoregressive modeling of volatility is improved by the addition of the proposed measure. Our paper contributes to the literature of machine learning in finance particularly in the context of understanding stock market instability.

Viet-Trung Tran, Hai-Nam Cao, Tuan-Dung Cao

Vietnamese labor market has been under an imbalanced development. The number of university graduates is growing, but so is the unemployment rate. This situation is often caused by the lack of accurate and timely labor market information, which leads to skill miss-matches between worker supply and the actual market demands. To build a data monitoring and analytic platform for the labor market, one of the main challenges is to be able to automatically detect occupational skills from labor-related data, such as resumes and job listings. Traditional approaches rely on existing taxonomy and/or large annotated data to build Named Entity Recognition (NER) models. They are expensive and require huge manual efforts. In this paper, we propose a practical methodology for skill detection in Vietnamese job listings. Rather than viewing the task as a NER task, we consider the task as a ranking problem. We propose a pipeline in which phrases are first extracted and ranked in semantic similarity with the phrases' contexts. Then we employ a final classification to detect skill phrases. We collected three datasets and conducted extensive experiments. The results demonstrated that our methodology achieved better performance than a NER model in scarce datasets.

Priscila Moreira Borges

Esta dissertação foi defendida em 2018 e analisou as relações de gênero na trajetória da Central Única dos Trabalhadores (CUT) entre os anos de 1983 e 2010. A preocupação desta pesquisa foi avaliar no mundo sindical de que forma a desigualdade também estava nos organismos de poder da instituição. A partir desse contexto analisou-se sobretudo a implantação de uma política de gênero em seu interior (inserção nas diretorias; instâncias internas de organização das mulheres; políticas de promoção de participação feminina). Apesar de inúmeros esforços como políticas de cotas para as diretorias, o poder sindical ainda se mantem extremamente masculino. A escolha da CUT foi por esta ser a maior central sindical do país e a pioneira nas discussões de gênero. Utilizou-se como metodologia a análise documental das resoluções do Congressos Nacionais da CUT (CONCUT) e a revisão bibliográfica de marcos teóricos como a divisão sexual do trabalho, representação política e organização sindical.

Alfred Galichon, Bernard Salanié

This paper provides an introduction to structural estimation methods for matching markets with transferable utility.