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

Francine D. Blau, M. Ferber, A. Winkler

I. Singh

Ronald G. Ehrenberg, R. Smith

B. Bernanke

Hyunjoong Kim, Zachary Kilpatrick, Kresimir Josic

How do social animals make effective decisions in the absence of a leader? While coordination can improve accuracy, it also introduces delays as information propagates through the group. In changing environments, these delays can outweigh the benefits of globally coordinated decisions, even when local interactions remain tightly organized. This raises a key question: how can groups implement efficient collective decision-making without central coordination? We address this question using a collective foraging model in which individuals share information and rewards, but each must choose whether to bear the cost of exploring or to remain idle. We show that decentralized collectives can match the performance of centrally controlled groups through a division of labor: a small, heterogeneous subset explores even when expected rewards are negative, acquiring information to enable future foraging, while a coordinated majority forages only when expected rewards are positive. Information redundancy causes the optimal number of explorers to grow sublinearly with group size, so that larger groups need proportionally fewer explorers. The heterogeneity of the group is maximized at intermediate ecological pressures, but optimal groups are homogeneous when costs or fluctuations are extreme. Crucially, these group-level policies do not require central coordination, emerging instead from agents following simple threshold-based decision rules. We thus demonstrate a mechanism through which leaderless collectives can make effective decisions under uncertainty and show how ecological pressures can drive changes in the distribution of strategies employed by the group.

Ludger Woessmann

The multitude of tasks performed in the labor market requires skills in many dimensions. Traditionally, human capital has been proxied primarily by educational attainment. However, an expanding body of literature highlights the importance of various skill dimensions for success in the labor market. This article examines the returns to cognitive, personality, and social skills, which are three important dimensions of basic skills. Recent advances in text analysis of online job postings and professional networking platforms offer novel methods for assessing a wider range of applied skill dimensions and their labor market relevance. Synthesis and integration of the evidence of the relationship between multidimensional skills and earnings, including the matching of skill supply and demand, will enhance our understanding of the role of human capital in the labor market.

Yuya Takada, Kiyoshi Izumi

National statistical institutes are beginning to use non-traditional data sources to produce official statistics. These sources, originally collected for non-statistical purposes, include point-of-sales(POS) data and mobile phone global positioning system(GPS) data. Such data have the potential to significantly enhance the usefulness of official statistics. In the era of big data, many private companies are accumulating vast amounts of transaction data. Exploring how to leverage these data for official statistics is increasingly important. However, progress has been slower than expected, mainly because such data are not collected through sample-based survey methods and therefore exhibit substantial selection bias. If this bias can be properly addressed, these data could become a valuable resource for official statistics, substantially expanding their scope and improving the quality of decision-making, including economic policy. This paper demonstrates that even biased transaction data can be useful for producing official statistics for prompt release, by drawing on the concepts of density ratio estimation and supervised learning under covariate shift, both developed in the field of machine learning. As a case study, we show that preliminary statistics can be produced in a timely manner using biased data from a Japanese private employment agency. This approach enables the early release of a key labor market indicator that would otherwise be delayed by up to a year, thereby making it unavailable for timely decision-making.

Hongcheng Li

This paper studies contracting in the presence of externalities with a non-contractible outsider. Multiple equilibria arise from strategic symmetry between the insider agent and the outsider. To address strategic uncertainty, the principal guarantees their actions in a unique equilibrium. A novel duality approach reformulates her problem as a series of problems in which she selects agent expectations. The key constraint is that the principal cannot convince the agent to expect non-guaranteed response from the outsider. Due to strategic rents, the principal optimally induces attenuated agent incentives. With completely symmetric strategic dependence, her coordination and commitment power become perfect substitutes; in addition, public contracting can strictly decrease her surplus compared to private contracting, in sharp contrast with the case where she ignores robustness. Applications include regulating international competition, platform design, and labor union contracting.

Lucas Godoy Garraza, Leontine Alkema

Estimating the causal effect of fertility on women's employment is challenging because fertility and labor decisions are jointly determined. The difficulty is amplified in low- and middle-income countries, where longitudinal data are scarce. In this study, we propose a novel approach to estimating the causal effect of fertility on employment using widely available Demographic and Health Survey (DHS) observational data. Using infecundity as an instrument for family size, our approach combines principal stratification with Bayesian Additive Regression Trees to flexibly account for covariate-dependent instrument validity, work with count-valued intermediate variables, and produce estimates of causal effects and effect heterogeneity, i.e., how effects vary with covariates in the survey population. We apply the approach to DHS data from Nigeria, Senegal, and Kenya. We find in the survey sample and general population that an additional child significantly reduces employment among women in Nigeria but has no clear average effect in Senegal or Kenya. Across all three countries, however, there is strong evidence of effect heterogeneity: younger, less-educated women experience large employment penalties, while older or more advantaged women are largely unaffected. Robustness checks confirm that these findings are not sensitive to key modeling assumptions. While limitations remain due to the cross-sectional nature of the DHS data, our results illustrate how flexible non-parametric models can uncover important effect variation.

Aparna Ravi, Emmanuel Teitelbaum

Consumers play an important role in regulating labor rights in global supply chains, either by punishing companies that violate labor rights or rewarding those that market fair labor practices. There is, however, currently limited understanding of how consumer demand can be effectively harnessed to protect freedom of association and collective bargaining (FACB) rights in garment-exporting countries. Through a series of conjoint experiments, we test the strength of consumer demand for FACB rights relative to other labor and environmental standards, and manipulate price and information frames to analyze the extent to which a business case exists to promote FACB rights. We find that consumers display willingness to pay premiums for various ethical labels around labor protections, indicating a business case for promoting ethical labor standards in supply chains. However, we also find that consumer demand for certain labor rights—including FACB rights and payment of a living wage—can diminish considerably in the context of price increases, thus limiting the profits firms might accrue by marketing labor rights protections. Our results open up the black box of consumer demand for different labor standards and evaluate the different modes through which consumers can influence labor protections in the global economy.

Tone Alm Andreassen, Lasse Holtar, Therese Saltkjel

For personer med sammensatte utfordringer må arbeidsrettet bistand kombineres med utdanning, helsehjelp eller sosiale tjenester. Mange europeiske land har derfor gjennomført reformer for å sikre mer helhetlige tjenester, slik Norge gjorde med Nav-reformen. Navs tjenester har vært mye studert, men vi vet fortsatt lite når det gjelder variasjoner i førstelinjens organisering, arbeid og samarbeid, og om disse kan påvirke tjenestene til brukerne. Ved bruk av klyngeanalyse av data fra en spørreundersøkelse til Nav-kontorledere undersøker vi med en konfigurasjonstilnærming hvordan mønstre i intern integrasjon og eksternt samarbeid danner ulike profiler av Nav-kontor. Gjennom en regresjonsanalyse undersøker vi hvordan disse profilene kan påvirke mulighetene til å gi helhetlige tjenester til brukere med sammensatte utfordringer. Vi kontrollerer for andre forhold som vi antar vil påvirke kontorenes muligheter til å gi helhetlige tjenester til denne brukergruppen, som kontorstørrelse, arbeidsbelastning og omfanget av sykefravær. Resultatene viser seks distinkte Nav-kontorprofiler, hvorav noen bedre enn andre kan bistå brukere med sammensatte utfordringer. Disse kontorene er integrerte og samarbeidsorienterte og kjennetegnes av at lederne rapporterer om høy måloppnåelse, både når det gjelder helhetlig tilbud til brukere med sammensatte utfordringer, og når det gjelder bistand til å komme i eller tilbake til jobb.

Svetlana M. Kuldina, Alexey I. Nazarov, Nikolay A. Kuldin

The purpose of the study was to find ways to ensure the effectiveness of training of universal specialists in energy fields in the implementation of the concept of lifelong learning through a practice-oriented approach.Research methods. To understand the current and future needs of the energy industry, especially in terms of the development of higher professional education, the study used the method of forecasting, direct survey of regional employers of energy enterprises, analysis of the needs of industrial partners in qualified specialists. The normative basis of the study was the Decree of the President of the Russian Federation Nо. 204 (2018) and the federal state educational standard of higher education in the direction of training 13.03.02 “Electric power engineering and electrical engineering”. The theoretical basis of the study is the model of the system of continuous professional education, adapted to the training of specialists for the energy industry. The joint use of these methods has formed a holistic approach to understanding the personnel problems of the power industry and the possibilities of the educational system in their solution.Results. Based on the model of the system of continuous professional education and the results of the analysis of the labor market demand in the Republic of Karelia, a practice-oriented educational program for training specialists in the field of power engineering was designed and implemented. Employers are increasingly looking for specialists with universal skills, capable of solving both typical and non-standard tasks and ready for further training during their working life. Successful implementation of the developed educational program is based on the joint cooperation of energy sector employers and university lecturers. Integration of industry experience with theoretical knowledge, vision of the industry development prospects allowed industrial partners and the university to jointly ensure the successful implementation of the designed educational program, helping to solve the problem of deficit of qualified personnel in the energy sector of the economy in the regions of the Russian Federation. The article presents the experience of the Department of energy supply of enterprises and energy efficiency of Petrozavodsk State University in training bachelors for the energy sector of the economy. The article reveals the totality of all the components of the model of the continuous education system, which contributes to the training of a universal specialist in the field of energy. The integrative qualities of the model are demonstrated, including the possibilities to receive higher and additional professional education for university students, productive combination of study and work at enterprises, ensuring the effectiveness of training, which is achieved by involving industrial partners in the educational process and strengthening the motivational component of the learning process. The educational programs are supplemented with disciplines forming digital and engineering competences, integrative forms of training are introduced: training and profile practice on the basis of ElectroSkills, internships with part-time employment, project activities with the solution of real tasks of enterprises.Conclusion. The authors have proposed and realized new approaches to the formation of professional skills required for university graduates. The key role of industrial partners’ participation in the educational process during the whole period of training is shown, the existing problems and difficulties in the implementation of practice-oriented approach in the training of specialists are outlined, the ways of eliminating the identified problems are proposed. The content and methods of step-by-step implementation of the practice-oriented educational program of training students of energy fields are demonstrated on specific examples.

Susan Athey, Herman Brunborg, Tianyu Du et al.

This paper builds an empirical model that predicts a worker's next occupation as a function of the worker's occupational history. Because histories are sequences of occupations, the covariate space is high-dimensional, and further, the outcome (the next occupation) is a discrete choice that can take on many values. To estimate the parameters of the model, we leverage an approach from generative artificial intelligence. Estimation begins from a ``foundation model'' trained on non-representative data and then ``fine-tunes'' the estimation using data about careers from a representative survey. We convert tabular data from the survey into text files that resemble resumes and fine-tune the parameters of the foundation model, a large language model (LLM), using these text files with the objective of predicting the next token (word). The resulting fine-tuned LLM is used to calculate estimates of worker transition probabilities. Its predictive performance surpasses all prior models, both for the task of granularly predicting the next occupation as well as for specific tasks such as predicting whether the worker changes occupations or stays in the labor force. We quantify the value of fine-tuning and further show that by adding more career data from a different population, fine-tuning smaller LLMs (fewer parameters) surpasses the performance of fine-tuning larger models. When we omit the English language occupational title and replace it with a unique code, predictive performance declines.

M. T. Devine, V. Bertsch

To meet carbon emission targets, governments around the world seek electricity consumers to invest in self-sufficiency technologies such as solar photovoltaic and battery storage. Such behaviour is sought in markets typically characterised by an oligopoly amongst generating firms. In this work, we study the interactions between investment decisions on the demand side and the supply side, and we investigate how price-making behaviour on the supply side affects these interactions compared to a situation with perfect competition. To do so, we introduce a novel stochastic mixed complementarity problem to model several players in an oligopolistic electricity market. On the supply side, we consider generating firms who make operational and investment decisions. On the demand side, we consider both industrial and residential consumers, each of whom may invest in self-sufficiency technologies. The uncertainties of wind and solar generation are the sources of the model's stochasticity. We apply the model to a case study of a stylised Irish electricity system in 2030. Our results demonstrate that price-making on the supply side increases investment in self-sufficiency on the demand side, leading to a reduction in prices and carbon emissions. We also find that both market power and self-sufficiency alter the investment and decommissioning decisions made by generation firms. Counter-intuitively, we also observe that the absence of a feed-in premium increases investment in solar generation on the demand side. Our findings highlight the importance of including both demand and supply side investment in models of electricity markets characterised by an oligopoly.

Vedant Das Swain, Qiuyue "Joy" Zhong, Jash Rajesh Parekh et al.

Client-Service Representatives (CSRs) are vital to organizations. Frequent interactions with disgruntled clients, however, disrupt their mental well-being. To help CSRs regulate their emotions while interacting with uncivil clients, we designed Care-Pilot, an LLM-powered assistant, and evaluated its efficacy, perception, and use. Our comparative analyses between 665 human and Care-Pilot-generated support messages highlight Care-Pilot's ability to adapt to and demonstrate empathy in various incivility incidents. Additionally, 143 CSRs assessed Care-Pilot's empathy as more sincere and actionable than human messages. Finally, we interviewed 20 CSRs who interacted with Care-Pilot in a simulation exercise. They reported that Care-Pilot helped them avoid negative thinking, recenter thoughts, and humanize clients; showing potential for bridging gaps in coworker support. Yet, they also noted deployment challenges and emphasized the indispensability of shared experiences. We discuss future designs and societal implications of AI-mediated emotional labor, underscoring empathy as a critical function for AI assistants for worker mental health.

Antonio A. Casilli, Paola Tubaro, Maxime Cornet et al.

Labor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rely on humans to execute repetitive and difficult-to-automate, but no less essential, tasks such as labeling images, sorting items in lists, recording voice samples, and transcribing audio files. Online platforms and networks of subcontractors recruit data workers to execute such tasks in the shadow of AI production, often in lower-income countries with long-standing traditions of informality and lessregulated labor markets. This study unveils the resulting complexities by comparing the working conditions and the profiles of data workers in Venezuela, Brazil, Madagascar, and as an example of a richer country, France. By leveraging original data collected over the years 2018-2023 via a mixed-method design, we highlight how the cross-country supply chains that link data workers to core AI production sites are reminiscent of colonial relationships, maintain historical economic dependencies, and generate inequalities that compound with those inherited from the past. The results also point to the importance of less-researched, non-English speaking countries to understand key features of the production of AI solutions at planetary scale.

Kun Chu, Xufeng Zhao, Cornelius Weber et al.

Although there has been rapid progress in endowing robots with the ability to solve complex manipulation tasks, generating control policies for bimanual robots to solve tasks involving two hands is still challenging because of the difficulties in effective temporal and spatial coordination. With emergent abilities in terms of step-by-step reasoning and in-context learning, Large Language Models (LLMs) have demonstrated promising potential in a variety of robotic tasks. However, the nature of language communication via a single sequence of discrete symbols makes LLM-based coordination in continuous space a particular challenge for bimanual tasks. To tackle this challenge, we present LAnguage-model-based Bimanual ORchestration (LABOR), an agent utilizing an LLM to analyze task configurations and devise coordination control policies for addressing long-horizon bimanual tasks. We evaluate our method through simulated experiments involving two classes of long-horizon tasks using the NICOL humanoid robot. Our results demonstrate that our method outperforms the baseline in terms of success rate. Additionally, we thoroughly analyze failure cases, offering insights into LLM-based approaches in bimanual robotic control and revealing future research trends. The project website can be found at http://labor-agent.github.io.

Sabiou Inoua, Vernon Smith

This paper introduces and formalizes the classical view on supply and demand, which, we argue, has an integrity independent and distinct from the neoclassical theory. Demand and supply, before the marginal revolution, are defined not by an unobservable criterion such as a utility function, but by an observable monetary variable, the reservation price: the buyer's (maximum) willingness to pay (WTP) value (a potential price) and the seller's (minimum) willingness to accept (WTA) value (a potential price) at the marketplace. Market demand and supply are the cumulative distribution of the buyers' and sellers' reservation prices, respectively. This WTP-WTA classical view of supply and demand formed the means whereby market participants were motivated in experimental economics although experimentalists (trained in neoclassical economics) were not cognizant of their link to the past. On this foundation was erected a vast literature on the rules of trading for a host of institutions, modern and ancient. This paper documents textually this reappraisal of classical economics and then formalizes it mathematically. A follow-up paper will articulate a theory of market price formation rooted in this classical view on supply and demand and in experimental findings on market behavior.

Rodrigo Cardoso da Silva

Trata-se de uma pesquisa que tem como fenômeno social de estudo, processos educativos e saberes socioambientais que se configuram, informam e/ou orientam experiências de trabalho da coleta do açaí, no nordeste da Amazônia paraense. A referida pesquisa integra a linha de pesquisa Saberes Culturais e Educação na Amazônia, do Programa de Pós-Graduação em Educação da Universidade do Estado do Pará (PPGED-UEPA). Trata-se de saberes socioambientais e processos educativos que sustentam relações não predatórias com a natureza e conformam modos de vida demarcados pela dualidade estrutural no processo de produção e reprodução à existência das lideranças na comunidade, que com o passar do tempo, essas práticas de trabalho realizadas pelos moradores passaram a incorporar novos processos educativos e saberes socioambientais, em decorrência as mudanças que foram ocorrendo na dinamização da produção capitalista e nas suas inovações tecnológicas. E para não concluir, os sujeitos históricos da comunidade Salento lutam e (re) existem com as vozes contra a estrutura opressora, eurocêntrica, negacionistas e colonialista, imposta pelo capital. Portanto, trata-se de um modo de vida que desafia a ciência e a educação.