At the current stage of the country’s socio-economic development, overcoming unemployment, poverty and ensuring effective employment in Georgia remains the main task of macroeconomic policy. Despite the recent reforms and certain positive shifts in economic development, there are still a number of difficulties in the labor market, which, on the one hand, are related to the shortage of jobs across the country, and on the other hand, to the shortage of highly qualified labor. In addition, there is a noticeable lack of personnel with the necessary knowledge, skills and experience in certain professions or specialties. This largely determines the imbalance between the demand and supply of labor in the Georgian labor market. The problem is made even more visible by modern global trends related to demographic, organizational, structural changes, large-scale labor emigration, technological innovations and other innovations.
Given the above situation, great importance is attached to systematic research of the labor market, especially in the direction of studying the real demand for labor, so that the existing higher and vocational education system in the country is correctly oriented towards training personnel with the appropriate profession and qualifications, which will fully meet the requirements of employers for the labor force and minimize the imbalance in the labor market. Eliminating the existing problem can have a positive impact on overcoming poverty, especially in relation to the “new poor”.
Poverty research is complex in nature and takes into account all the achievements that have taken place in economic, political, sociological and psychological scientific directions, which reveals the interdisciplinary nature of poverty research. This paper presents an analysis of the practical and theoretical approaches related to the study of the problem of poverty in socio-economic science.
At the current stage of the country’s socio-economic development, overcoming unemployment, poverty and ensuring effective employment remain the main tasks of macroeconomic policy in Georgia. Despite the recent reforms and certain positive shifts in the direction of economic development, there are still a number of difficulties in the economy, which, on the one hand, are related to the shortage of jobs across the country, and on the other hand, to the shortage of highly qualified labor. In addition, there is a noticeable lack of personnel with the necessary knowledge, skills and experience in certain professions or specialties. This largely determines the imbalance between the demand and supply of labor in the Georgian labor market. The problem is made even more visible by modern global trends related to demographic, organizational, structural changes, large-scale labor emigration, technological innovations and other innovations.
In modern economic relations, the impact of the functioning of the labor market on the “new poor” is relevant, which is explained primarily by the fact that in many cases employment cannot provide adequate living conditions for an individual. Poverty in its essence is a global challenge. At the same time, poverty is characterized by a subjective nature, which means that it is perceived differently by everyone. There may be different answers to the question of what poverty means: for someone it is associated with a lack of food, for someone with the absence of shelter, and for someone it may be associated with the possibility of receiving quality education. For some, it may be associated only with health.
Abstract Is labor-saving technological change efficient when labor market frictions arise? Does it exacerbate them? This paper presents a growth model with R&D and two types of technological change: labor-saving technological change, which reduces the labor share (the output elasticity of labor), and labor-complementary, which increases it. The paper presents two kinds of friction in the labor market: unemployment and dual labor markets. When there are dual labor markets, the marginal product of labor and the wages are higher in the “good-jobs sector” than in the “bad-jobs sector,” involving an inefficiently low amount of labor allocated to the good-jobs sector. Labor-saving technological change exacerbates the source of inefficiency in the labor market. It raises unemployment and destroys jobs in the good-jobs sector, generating negative external effects in the labor market. Consequently, investment in labor-saving technological change is inefficiently large and should be taxed. The results regarding labor-complementary technological change are the opposite. JEL: D60, E24, J31, J50, J60, H21, H23, O30, O41.
O presente artigo discute a formação da Escola Latino-Americana de Agroecologia (ELAA), originária dos movimentos dos trabalhadores no campo, em uma perspectiva macrossocial. Argumentamos que a dinâmica pedagógica-laboral da ELAA ilustra tanto os avanços quanto os atuais limites das concepções científico-técnicas na expansão internacional do capitalismo. Assim, abordamos a temática a partir da teoria marxista da dependência, destacando o conflito entre a matriz primário-exportadora do empresariado e os projetos autônomos da classe trabalhadora no continente.
Palavra-chave: Escola Latino-Americana de Agroecologia; Teoria Marxista da Dependência; Ciência, Tecnologia & Sociedade.
Special aspects of education, Labor market. Labor supply. Labor demand
This study explores the dynamics between technological advancements, educational reforms, and their consequent impact on the labor market in Chile over 1980–2018 reported by Campos-González and Balcombe (2024). The authors analyze the evolution of the skill premium in response to significant policy changes and global technological trends revealing a pivotal shift in the Chilean labor market: the transition from a technology-driven phase, where rapid technological advancements heightened the demand for skilled labor in the pre-2000 period, to an education-driven phase post-2000, marked by comprehensive educational reforms. These reforms effectively increased the supply of educated workers, leading to the stabilization, and posterior decrease of the skill premium. The authors contribute to the broader understanding of how nations can navigate the challenges posed by the digital age, providing valuable insights for policymakers and educators in fostering equitable and sustainable economic growth. The study’s findings are particularly relevant to emerging economies undergoing similar transitions, offering a framework for policy formulation that synchronizes educational advancements with technological progress to ensure inclusive economic development.
This paper conducts an empirical investigation into the effects of Designated Market Makers (DMMs) on key market quality indicators, such as liquidity, bid-ask spreads, and order fulfillment ratios. Through agent-based simulations, this study explores the impact of varying competition levels and incentive structures among DMMs on market dynamics. It aims to demonstrate that DMMs are crucial for enhancing market liquidity and stabilizing price spreads, thereby affirming their essential role in promoting market efficiency. Our findings confirm the impact of the number of Designated Market Makers (DMMs) and asset diversity on market liquidity. The result also suggests that an optimal level of competition among DMMs can maximize liquidity benefits while minimizing negative impacts on price discovery. Additionally, the research indicates that the benefits of increased number of DMMs diminish beyond a certain threshold, implying that excessive incentives may not further improve market quality metrics.
Accurate demand forecasting is crucial for optimizing supply chain management. Traditional methods often fail to capture complex patterns from seasonal variability and special events. Despite advancements in deep learning, interpretable forecasting models remain a challenge. To address this, we introduce the Multi-Channel Data Fusion Network (MCDFN), a hybrid architecture that integrates Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU) to enhance predictive performance by extracting spatial and temporal features from time series data. Our comparative benchmarking demonstrates that MCDFN outperforms seven other deep-learning models, achieving superior metrics: MSE (23.5738), RMSE (4.8553), MAE (3.9991), and MAPE (20.1575%). Theil's U statistic of 0.1181 (U<1) of MCDFN indicates its superiority over the naive forecasting approach, and a 10-fold cross-validated statistical paired t-test with a p-value of 5% indicated no significant difference between MCDFN's predictions and actual values. We apply explainable AI techniques like ShapTime and Permutation Feature Importance to enhance interpretability. This research advances demand forecasting methodologies and offers practical guidelines for integrating MCDFN into supply chain systems, highlighting future research directions for scalability and user-friendly deployment.
Michael Stiller, Melanie Ebener, Hans Martin Hasselhorn
Abstract In times of demographic change, better job quality is needed to promote health and thereby extend employment participation among older workers. Past research has focussed on the investigation of single job quality characteristics, but neglected their combined effects on health and employment. To address this limitation, we have built upon an established typology based on nine job quality characteristics and representing five profiles of overall poor or good job quality constellations among manual and non-manual older workers, respectively. It was investigated how constant and changing job quality affects non-employment and how mental and physical health mediate this association. Analyses were based on representative data from N = 2,952 employees born in 1959 or 1965, who participated in all current waves (in the years 2011, 2014 and 2018) of the German lidA cohort study. Job quality was measured in 2011 and 2014 according to profile assignment per wave, composite mental and physical health scores from 2014 were used as mediators and non-employment (vs. employment) in 2018 represented the outcome. Two separate mediation models were calculated, one for manuals and one for non-manuals. Among manuals with constantly poor job quality, the risk of non-employment was increased through both poor mental and physical health. Deteriorating job quality increased this risk through poor mental health, while changing from manual to non-manual work reduced this risk through better physical health. Among non-manuals, poor job quality was not related to the risk of non-employment and no health effects were found to significantly mediate such a risk. In conclusion, the health risks of poor later-life job quality demand critical consideration to maintain employability, particularly of manual workers in poor quality jobs. Timely workplace improvements for certain groups are needed to increase employment participation in good health, thereby increasing efficiency and fairness of measures promoting longer working lives.
After a decade of on-demand mobility services that change spatial behaviors in metropolitan areas, the Shared Autonomous Vehicle (SAV) service is expected to increase traffic congestion and unequal access to transport services. A paradigm of scheduled supply that is aware of demand but not on-demand is proposed, introducing coordination and social and behavioral understanding, urban cognition and empowerment of agents, into a novel informational framework. Daily routines and other patterns of spatial behaviors outline a fundamental demand layer in a supply-oriented paradigm that captures urban dynamics and spatial-temporal behaviors, mostly in groups. Rather than real-time requests and instant responses that reward unplanned actions, and beyond just reservation of travels in timetables, the intention is to capture mobility flows in scheduled travels along the day considering time of day, places, passengers etc. Regulating goal-directed behaviors and caring for service resources and the overall system welfare is proposed to minimize uncertainty, considering the capacity of mobility interactions to hold value, i.e., Motility as a Service (MaaS). The principal-agent problem in the smart city is a problem of collective action among service providers and users that create expectations based on previous actions and reactions in mutual systems. Planned behavior that accounts for service coordination is expected to stabilize excessive rides and traffic load, and to induce a cognitive gain, thus balancing information load and facilitating cognitive effort.
Regarding climate change, the need to reduce greenhouse gas emissions is well-known. As building heating contributes to a high share of total energy consumption, which relies mainly on fossil energy sources, improving heating efficiency is promising to consider. Lowering supply temperatures of the heating systems in buildings offers a huge potential for efficiency improvements since different heat supply technologies, such as heat pumps or district heating, benefit from low supply temperatures. However, most estimations of possible temperature reductions in existing buildings are based on available measurement data on room level or detailed building information about the building's physics to develop simulation models. To reveal the potential of temperature reduction for several buildings and strive for a wide applicability, the presented method focuses on estimations for temperature reduction in existing buildings with limited input data. By evaluating historic heat demand data on the building level, outdoor temperatures and information about installed heaters, the minimal actual necessary supply temperature is calculated for each heater in the building using the LMTD approach. Based on the calculated required supply temperatures for each room at different outdoor temperatures, the overall necessary supply temperatures to be provided to the building are chosen. Thus, the minimal heatcurve possible for an existing building is deduced. The method described is applied to multiple existing office buildings at the campus of Forschungszentrum Juelich, Germany, demonstrating the fast application for several buildings with limited expenditure. Furthermore, a developed adapted heatcurve is implemented in one real building and evaluated in relation to the previously applied heatcurve of the heating system.
Ellen Rodrigues da Silva Miranda, Maria Jacqueline Girão Soares de Lima
Expomos neste artigo, a partir de achados de uma pesquisa de mestrado concluída e pesquisas em andamento, a relação entre mulheres quilombolas, natureza e sociedade como processo de aproximação entre teoria e práxis interseccional ecofeminista na Amazônia Paraense. Ancoradas na abordagem qualitativa de enfoque materialista histórico-dialético, analisamos observações, anotações de campo e entrevistas semiestruturadas. As aproximações são apontadas em experiências de luta cotidiana ao realizarem ações contra as investidas de privatizações dos rios, florestas e animais, operadas pelo capitalismo.
Palavras-chave: Mulheres quilombolas; Experiência; Natureza-território; Interseccionalidade; Ecofeminismo.
Special aspects of education, Labor market. Labor supply. Labor demand
As the demand for mobility in our society seems to increase, the various issues centered on urban mobility are among those that worry most city inhabitants in this planet. For instance, how to go from A to B in an efficient (but also less stressful) way? These questions and concerns have not changed even during the covid-19 pandemic; on the contrary, as the current stand, people who are avoiding public transportation are only contributing to an increase in the vehicular traffic. The are of intelligent transportation systems (ITS) aims at investigating how to employ information and communication technologies to problems related to transportation. This may mean monitoring and managing the infrastructure (e.g., traffic roads, traffic signals, etc.). However, currently, ITS is also targeting the management of demand. In this panorama, artificial intelligence plays an important role, especially with the advances in machine learning that translates in the use of computational vision, connected and autonomous vehicles, agent-based simulation, among others. In the present work, a survey of several works developed by our group are discussed in a holistic perspective, i.e., they cover not only the supply side (as commonly found in ITS works), but also the demand side, and, in an novel perspective, the integration of both.
Market makers play an essential role in financial markets. A successful market maker should control inventory and adverse selection risks and provide liquidity to the market. As an important methodology in control problems, Reinforcement Learning enjoys the advantage of data-driven and less rigid assumptions, receiving great attention in the market-making field since 2018. However, although the China Commodity market has the biggest trading volume on agricultural products, nonferrous metals, and some other sectors, the study of applying RL to Market Making in China market is still rare. In this thesis, we try to fill the gap. Our contribution is threefold: We develop the Automatic Trading System and verify the feasibility of applying Reinforcement Learning in the China Commodity market. Also, we probe the agent's behavior by analyzing how it reacts to different environmental conditions.
We study how firm heterogeneity and market power affect macroeconomic fragility, defined as the probability of long slumps. We propose a theory in which the positive interaction between firm entry, competition and factor supply can give rise to multiple steady-states. We show that when firms are highly heterogeneous in terms of productivities, even small temporary shocks can trigger firm exit and make the economy spiral in a competition-driven poverty trap. We calibrate our model to incorporate the well-documented trends on rising firm heterogeneity in the US economy, and show that they significantly increase the likelihood and length of slow recoveries. We use our framework to study the 2008-09 recession and show that the model can rationalize the persistent deviation of output and most macroeconomic aggregates from trend, including the behavior of net entry, markups and the labor share. Post-crisis cross-industry data corroborates our proposed mechanism. We conclude by showing that firm subsidies can be powerful in preventing long slumps and can lead to welfare gains between 10% and 50%.
La idea del conflicto capital-vida es un aporte fundamental de los feminismos para comprender la toxicidad del sistema hegemónico que tiende a imponerse globalmente, como constitutivo del proyecto modernizador que lleva cuando menos quinientos años desplegándose, un sistema económico que destruye otras formas de economía previas, un sistema frente al cual intentamos desplegar formas económicas otras, en resistencia, subversivas.
En este texto intentamos rastrear el surgimiento de este concepto, entender sus dimensiones sistémicas y debatir su pertinencia para comprender el momento actual.
Special aspects of education, Labor market. Labor supply. Labor demand
O objeto deste artigo é refletir sobre o processo de aproximação a Universidade por parte de jovens trabalhadores no período entre 1999 e 2013. Período da realidade brasileira, marcada por frequentes crises econômicas que modificam em continuação o mercado de trabalho e, de consequência, fragilizam as trajetórias ocupacionais das pessoas. Estas alterações repercutem na vida das pessoas, introduzindo sentimentos de incerteza e de insegurança social. Neste contexto buscar o diploma universitário, é uma estratégia para ampliar as perspectivas futuras de promoção profissional. Os jovens trabalhadores ao retornar aos estudos, se disponibilizam a reorganizar seus cotidianos: conciliar o tempo dedicado a frequentar a universidade, a assistir a família e a manter o emprego. No decorrer do artigo, apesar de sublinhar as inovações, tudo indica que a cultura de gênero permanece como marcador de diferença de opções e escolhas.
Palavras-chave: gênero e trabalho; trabalho e universidade; gênero e universidade.
Special aspects of education, Labor market. Labor supply. Labor demand
Este artigo visa discutir a respeito da concepção de
educação profissional na Reforma do Ensino
Médio, no intuito de compreender o sentido da inserção da profissionalização no currículo do ensino
médio regular. A metodologia consiste em discussão teórica, análise documental das normativas para
o ensino médio e pesquisa de campo de abordagem qualitativa. Como proposta de intervenção,
descreve e analisa os dados obtidos com o desenvolvimento de um curso de formação, destinado à
discussão a respeito da profiss ionalização e da especialização no ensino médio regular, realizado
com os profissionais da educação de uma escola estadual em Poços de Caldas/MG.
Palavras chave : Educação Profissional e Tecnológica. Reforma do Ensino Médio.
Special aspects of education, Labor market. Labor supply. Labor demand
Nazaruddin Malik, Muhammad Sri Wahyudi Suliswanto, Mochamad Rofik
This study analyzes the impact of the shocks caused by the COVID-19 pandemic on the labor market. The research is vital for expanding the literature about maintaining the unemployment rate amid crisis, ultimately reducing unnecessary social costs. The quantitative approach in this study uses a Granger causality test to understand the effect of the shock caused by the COVID-19 pandemic on unemployment. Meanwhile, the qualitative approach in this study uses literature related to economic growth, crisis management, and unemployment. Granger causality tests show that economic slowdown hurts the unemployment rate. Based on discussion and synthesis from works of literature, this paper recommends some of the policies to maintain growth and prevent a more severe collapse in the labor market; the government needs to sustain aggregate demand and supply. Also, ensure the supply chain runs well amid various restrictions. Besides, this paper also proposes that the government maximizes alternative budget resources. Meanwhile, strengthening the labor system and developing health and food security industries must be a priority policy amid-post the pandemic.
Political science (General), Social sciences (General)