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

Julian Jäger, Elisabeth Sattler-Bublitz, Miriam Beblo

Abstract We analyze how employees perceive and evaluate the integration of people with disabilities into the German labor market. In an experimental complement to the Employment Survey by the German Federal Institutes for Vocational Training and Occupational Safety and Health, we ask respondents to estimate the labor force participation rates of persons with and without disabilities. We then inform a subsample about the actual gap between the rates. Regardless of having a disability, respondents are aware of a participation gap, share similar beliefs about its causes, and rate integration as less advanced when they are informed about a larger gap than expected. The largest differences exist in perceptions of the size of the gap and policy preferences: Respondents with disabilities perceive a smaller gap and are more in favor of integrative policies than those without disabilities.

Rubén Castro Landsman, Juan Tapia Gertosio, Diego Mejías González

Abstract The common intuition is that unemployment duration is shorter for workers with higher education. However, there is no theoretical support for this intuition, and empirically, there is no systematic review of the findings to date. We conducted a literature review of empirical articles that report findings on the association between the duration of unemployment and education level. 103 papers that reported a quantitative and empirical association were included in the review, and the results show that only 30% of those articles support the common intuition. Furthermore, 26% of the articles support the counterintuitive association: that unemployment duration is longer for workers with higher education. The analysis concludes, therefore, that the common intuition is not supported by the empirical literature. While the meta-analysis shows that the intuitive association is even less likely to be found in developing countries, which authors relate to waiting unemployment and overeducation, many channels are discussed in the literature, suggesting that the association is complex and far from the simple common intuition.

Ida Drange, Andreea Ioana Alecu, Anders Underthun

Lovregulerte yrker er yrker hvor myndighetene stiller krav til kompetansen og ferdighetene til personene som skal utøve yrket. Mens Norge har avtaler om gjensidig godkjenning av yrkeskvalifikasjonene til andre nordiske og europeiske arbeidstakere, vil yrkesutøvere med utdanning fra land utenfor EU og EØS måtte søke om å få utdanningen sin vurdert som jevngod med norsk utdanning. I 2017 ble kompletterende utdanning for sykepleiere, ingeniører og lærere etablert for å gi profesjonsutøvere med utenlandsk utdanning en forutsigbar vei tilbake til yrket i Norge. Kompletterende utdanning krever minst ett år med fulltidsstudier ved et norsk universitet eller en norsk høyskole og har som formål å kvalifisere kandidatene til yrket. Selv om utdanningen formelt kvalifiserer til ansettelse, vil ansettbarheten til kandidatene også avhenge av arbeidsgiveres vurdering av kompetanse og attraktivitet. I denne artikkelen benytter vi data fra Felles studentsystem, Arbeidsgiver- og arbeidstakerregisteret og inntektsregisteret til å undersøke om kompletterende utdanning gir profesjonsrelevant arbeid og styrker profesjonsutøvernes posisjon på arbeidsmarkedet. Vi finner variasjon på tvers av yrkesgruppene, noe som tyder på at kompletterende utdanning er mest nyttig for sykepleiere, som får relevant arbeid, endog i liten grad på sykehus.

Torberg Falch, Bjarne Strøm

Artikkelen studerer samspillet mellom lærerarbeidsmarkedet og lærerutdanninga i Norge ved å analysere data for lærermangel, lærerutdanning og læreretterspørsel i grunnskolen de siste 50 år. Arbeidet er basert på en ny dataserie for lærermangel og lærerutdanning. Et hovedresultat er at lærermangelen er medsyklisk: Det blir økt mangel på kvalifiserte lærere når arbeidsledigheten i økonomien reduseres. Samtidig finner vi at opptaket til lærerutdanninga øker signifikant når lærermangelen øker, noe som demper utslagene på lengre sikt. Opptaket reagerer også direkte på endret ledighet. I tillegg påvirkes lærermangelen av etterspørselen etter lærere og beholdningen av kvalifiserte lærere totalt. Resultatene indikerer redusert lærermangel i årene framover.

Albert BERRY

Ertian Chen

Estimation and counterfactual analysis in dynamic structural models rely on assumptions about the dynamic process of latent variables, which may be misspecified. We propose a framework to quantify the sensitivity of scalar parameters of interest (e.g., welfare, elasticity) to such assumptions. We derive bounds on the scalar parameter by perturbing a reference dynamic process, while imposing a stationarity condition for time-homogeneous models or a Markovian condition for time-inhomogeneous models. The bounds are the solutions to optimization problems, for which we derive a computationally tractable dual formulation. We establish consistency, convergence rate, and asymptotic distribution for the estimator of the bounds. We demonstrate the approach with two applications: an infinite-horizon dynamic demand model for new cars in the United Kingdom, Germany, and France, and a finite-horizon dynamic labor supply model for taxi drivers in New York City. In the car application, perturbed price elasticities deviate by at most 15.24% from the reference elasticities, while perturbed estimates of consumer surplus from an additional $3,000 electric vehicle subsidy vary by up to 102.75%. In the labor supply application, the perturbed Frisch labor supply elasticity deviates by at most 76.83% for weekday drivers and 42.84% for weekend drivers.

Yao Zhang, Zaixi Shang, Silpan Patel et al.

Supply chain operations generate vast amounts of operational data; however, critical knowledge such as system usage practices, troubleshooting workflows, and resolution techniques often remains buried within unstructured communications like support tickets, emails, and chat logs. While RAG systems aim to leverage such communications as a knowledge base, their effectiveness is limited by raw data challenges: support tickets are typically noisy, inconsistent, and incomplete, making direct retrieval suboptimal. Unlike existing RAG approaches that focus on runtime optimization, we introduce a novel offline-first methodology that transforms these communications into a structured knowledge base. Our key innovation is a LLMs-based multi-agent system orchestrating three specialized agents: Category Discovery for taxonomy creation, Categorization for ticket grouping, and Knowledge Synthesis for article generation. Applying our methodology to real-world support tickets with resolution notes and comments, our system creates a compact knowledge base - reducing total volume to just 3.4% of original ticket data while improving quality. Experiments demonstrate that our prebuilt knowledge base in RAG systems significantly outperforms traditional RAG implementations (48.74% vs. 38.60% helpful answers) and achieves a 77.4% reduction in unhelpful responses. By automating institutional knowledge capture that typically remains siloed in experts' heads, our solution translates to substantial operational efficiency: reducing support workload, accelerating resolution times, and creating self-improving systems that automatically resolve approximately 50% of future supply chain tickets. Our approach addresses a key gap in knowledge management by transforming transient communications into structured, reusable knowledge through intelligent offline processing rather than latency-inducing runtime architectures.

Lajos Tamás Szabó

Abstract I estimate the effect of tightness on wages in Hungary and Slovakia. The Mortensen Pissarides model predicts a positive relationship but the empirical evidence is scarce. I instrument tightness by the distance of a district from the Austrian border, interacted with a dummy that marks the opening of the Austrian labour market to these countries in 2011. I find a positive effect of tightness on wages, which is in line with the conclusion of the models. If tightness increase by 1 per cent than ceteris paribus wages increase by roughly 0.2 per cent both in Hungary and Slovakia as well.

Asmera Teshome, Jeilu Oumer

This study examined the alignment between the supply of STEM skills by higher education institutions and the demand for these skills in the labor market in Ethiopia, employing a mixed-methods approach. Quantitative data from 275 respondents were analyzed using mean, standard deviation, and paired sample t-tests, while thematic analysis was applied to qualitative data. The results revealed significant mismatches between the skills provided by educational institutions and those required by the labor market, with the greatest disparities found in generic skills, followed by technical and interpersonal skills, and the least in discipline-specific skills. The study highlights the urgent need for higher education institutions to enhance their collaboration with industry stakeholders to develop curricula that effectively address these gaps. Recommendations include conducting regular market needs assessments, integrating external expert lectures, and applying project-based learning to foster critical and innovative thinking skills among students, preparing them more effectively for employment.

Nathalia Ferreira Gonçales, Celso Alexandre Souza Alvear

Este artigo sistematiza as ações do projeto "Construção de Ferramentas de Comercialização de Produtos da Reforma Agrária no Rio de Janeiro", realizado entre agosto de 2021 e dezembro de 2022 no Armazém do Campo do Rio de Janeiro, do MST. O projeto, executado como pesquisa-ação, desenvolveu um sistema de vendas para atender diferentes regiões e núcleos de comercialização no estado. A produção de sistemas de código aberto e a elaboração participativa permitiram criar um ambiente virtual de comunicação entre consumidores e produtores, aproximando cidade e campo. Palavras-chave: Tecnologia Social, Software Livre, Cestas agroecológicas, Reforma Agrária.

Runa Brandal Myklebust, Marjan Nadim, Julia Orupabo

Gjennom aktivitets- og redegjørelsesplikten (ARP) er alle norske virksomheter lovpålagt å arbeide aktivt, målrettet og planmessig med å fremme likestilling og hindre diskriminering basert på alle diskrimineringsgrunnlag. Ifølge forskningen om hva som skaper fremgang i virksomheters mangfoldsarbeid, er det nettopp slike strukturrettede tiltak hvor noen i organisasjonen gis et institusjonelt ansvar for mangfoldstiltakene, som er vesentlig for å lykkes. I denne artikkelen undersøker vi to spørsmål. Hvordan former den lovpålagte forpliktelsen til å drive mangfoldsarbeid virksomheters arbeid med likestilling og mangfold? Hva skal til for at de som er ansvarlige for og involverte i mangfoldsarbeidet, opplever dette arbeidet som virkningsfullt og effektivt? Basert på en studie av 15 offentlige og private virksomheter finner vi at tre aspekter ved ARP er sentrale for å forstå hvordan ARP fungerer som et verktøy i virksomhetenes mangfoldsarbeid, både i positiv og i negativ forstand: ARP som plikt, ARP som metode og ARP som ansvarsstruktur. Studien viser at aktivitets- og redegjørelsesplikten kan fungere som en brekkstang for mangfoldsarbeid i virksomhetene og bidra til å etablere ansvarsstrukturer for dette arbeidet. Samtidig møter arbeidet med de lovpålagte pliktene betydelig motstand i virksomhetene, og mange opplever at ARP-arbeidet i liten grad skaper synergier med det eksisterende arbeidet med likestilling og mangfold. Analysen viser også at selv om det finnes ansvarsstrukturer for mangfoldsarbeidet, er graden av gjennomslag de ansvarlige opplever å ha i organisasjonen, avhengig av i hvilken grad det generelle mangfoldsarbeidet er forankret i ledelsen og/eller integrert i virksomhetens kjernevirke.

Vasily Tolstikov

An automated market maker where the price can cross the zero bound into the negative price domain with applications in electricity, energy, and derivatives markets is presented. A unique feature involves the ability to swap both negatively and positively priced assets between one another, which unlike traditional markets requires a numeraire in the form of a currency. Model extensions to skew and concentrate liquidity are shown. The liquidity fingerprint, payoff, and invariant are compared to the Black-Scholes covered call and the Logarithmic Market Scoring Rule invariants.

Saurab Chhachhi, Fei Teng

Given the vital role that smart meter data could play in handling uncertainty in energy markets, data markets have been proposed as a means to enable increased data access. However, most extant literature considers energy markets and data markets separately, which ignores the interdependence between them. In addition, existing data market frameworks rely on a trusted entity to clear the market. This paper proposes a joint energy and data market focusing on the day-ahead retailer energy procurement problem with uncertain demand. The retailer can purchase differentially-private smart meter data from consumers to reduce uncertainty. The problem is modelled as an integrated forecasting and optimisation problem providing a means of valuing data directly rather than valuing forecasts or forecast accuracy. Value is determined by the Wasserstein distance, enabling privacy to be preserved during the valuation and procurement process. The value of joint energy and data clearing is highlighted through numerical case studies using both synthetic and real smart meter data.

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Ali Raheman, Anton Kolonin, Alexey Glushchenko et al.

Crypto-currency market uncertainty drives the need to find adaptive solutions to maximise gain or at least to avoid loss throughout the periods of trading activity. Given the high dimensionality and complexity of the state-action space in this domain, it can be treated as a "Narrow AGI" problem with the scope of goals and environments bound to financial markets. Adaptive Multi-Strategy Agent approach for market-making introduces a new solution to maximise positive "alpha" in long-term handling limit order book (LOB) positions by using multiple sub-agents implementing different strategies with a dynamic selection of these agents based on changing market conditions. AMSA provides no specific strategy of its own while being responsible for segmenting the periods of market-making activity into smaller execution sub-periods, performing internal backtesting on historical data on each of the sub-periods, doing sub- agent performance evaluation and re-selection of them at the end of each sub- period, and collecting returns and losses incrementally. With this approach, the return becomes a function of hyper-parameters such as market data granularity (refresh rate), the execution sub-period duration, number of active sub-agents, and their individual strategies. Sub-agent selection for the next trading sub-period is made based on return/loss and alpha values obtained during internal backtesting as well as real trading. Experiments with the AMSA have been performed under different market conditions relying on historical data and proved a high probability of positive alpha throughout the periods of trading activity in the case of properly selected hyper-parameters.

Oleh Danyliv

The article is an empirical study of market impact through order book events. It describes a mechanism of extracting an average participation rate and a market impact of small orders which represent individual slices of large metaorders. The study is based on tick data for futures contracts. It is shown that the impact could be either linear or a concave function as a function of trading volume, depending on the instrument. After normalisation, this dependency is shown to be very similar for a wide range of instruments. A simple yet effective model for market impact estimation is proposed. This model is linear in nature and is derived based on straightforward microstructure reasoning. The estimation shows satisfactory results for both concave and linear market impact volume dependencies.

Sonia Maria Rummert, Jaqueline Ventura

Em outubro de 2021, um vídeo com jovens e adultos (em sua maioria mulheres) procurando por comida em um caminhão de lixo em Fortaleza chamou a atenção, nas redes sociais, sobre a situação de aprofundamento da desigualdade social e da ampliação da fome no país. Estima-se que hoje, vinte e cinco milhões de brasileiros não saibam o que, nem se irão comer. País, em virtude das políticas atualmente implementadas, sobretudo, pelo governo federal e traz para jovens e adultos da classe trabalhadora imensos desafios para existir e resistir.

Berenike Vollmer

The North Atlantic Treaty Organizations (NATO) public-private Space Asset Supply Chain (SASC) currently exhibits significant cybersecurity gaps. It is well-established that data obtained from space assets is fundamental to NATO, as they allow for the facilitation of its missions, self-defence and effective deterrence of its adversaries. Any hostile cyber operation, suspending control over a space asset, severely impacts both NATO missions and allied Member States national security. This threat is exacerbated by NATOs mostly unregulated cyber SASC. Hence, this thesis answers a twofold research question: a) What are current cybersecurity gaps along NATOs global SASC; and b) How can NATO and its allied Member States gain greater control over such gaps to safeguard the supply of NATO mission-critical information? An ontological field study is carried out by conducting nineteen semi-structured interviews with high-level representatives from relevant public, private and academic organizations. This research was undertaken in collaboration with the NATO Cooperative Cyber Defence Centre of Excellence (CCDCOE) in Tallinn, Estonia. This thesis concludes that current cybersecurity gaps along NATOs SASC are caused by cyber vulnerabilities such as legacy systems or the use of Commercial-Off-the-Shelf (COTS) technology. Inadequate cyber SASC management is caused by hindrances such as misaligned classification levels and significant understaffing. On this basis, NATO should consider two major collaboration initiatives: a) Raising Awareness throughout the whole of the NATO system, and b) Pushing forward the creation of regulation through a standardized security framework on SASC cybersecurity. Doing so would enable NATO and its Member States to recognise cyberthreats to mission-critical data early on along its cyber SASC, and thus increase transparency, responsibility, and liability.

Damjan Vavpotič, Karmen Knavs, Ljubica Knežević Cvelbar

Understanding tourist visitation patterns is crucial for decision makers in order to create smart tourism industry. A growing body of tourism research uses geo-location data in order to better understand tourism demand. In this paper, we present a new approach based on a market basket analysis. This approach uses geo-location data shared by tourists on tourism platforms in order to bundle the range of available tourism services and understand which experiences are consumed together. The approach was tested on the case of Vienna, Austria. Based on our analyses we argue that the proposed approach has potential for use at the destination level and provides relevant information on tourism demand patterns important for smart tourism decision-making.

Takanobu Mizuta

Who should be charged with responsibility for an artificial intelligence performing market manipulation have been discussed. In this study, I constructed an artificial intelligence using a genetic algorithm that learns in an artificial market simulation, and investigated whether the artificial intelligence discovers market manipulation through learning with an artificial market simulation despite a builder of artificial intelligence has no intention of market manipulation. As a result, the artificial intelligence discovered market manipulation as an optimal investment strategy. This result suggests necessity of regulation, such as obligating builders of artificial intelligence to prevent artificial intelligence from performing market manipulation.