Hasil untuk "Labor policy. Labor and the state"

Ashwini Agrawal, David A. Matsa

This paper presents evidence that firms choose conservative financial policies partly to mitigate workers' exposure to unemployment risk. We exploit changes in state unemployment insurance laws as a source of variation in the costs borne by workers during layoff spells. We find that higher unemployment benefits lead to increased corporate leverage, particularly for labor-intensive and financially constrained firms. We estimate the ex ante, indirect costs of financial distress due to unemployment risk to be about 60 basis points of firm value for a typical BBB-rated firm. The findings suggest that labor market frictions have a significant impact on corporate financing decisions.

T. Kromydas

The purposes and impact of higher education on the economy and the broader society have been transformed through time in various ways. Higher education institutional and policy dynamics differ across time, but also between countries and political regimes and therefore context cannot be neglected. This article reviews the purpose of higher education and its institutional characteristics juxtaposing two, allegedly rival, conceptual frameworks; the instrumental and the intrinsic one. Various pedagogical traditions are critically reviewed and used as examples, which can potentially inform today’s policy making. Since, higher education cannot be seen as detached from all other lower levels of education appropriate conceptual links are offered throughout this article. Its significance lies on the organic synthesis of literature across social science, suggesting ways of going forward based on the traditions that already exist but seem underutilized so far because of overdependence in market-driven practices. This offers a new insight on how theories can inform policy making, through conceptual “bridging” and reconciliation. The debate on the purpose of higher education is placed under the context of the most recent developments of increasing social inequalities in the western world and its relation to the mass model of higher education and the relevant policy decisions for a continuous increase in participation. This article suggests that the current policy focus on labor market driven policies in higher education have led to an ever growing competition transforming this social institution to an ordinary market-place, where attainment and degrees are seen as a currency that can be converted to a labour market value. Education has become an instrument for economic progress moving away from its original role to provide context for human development. As a result, higher education becomes very expensive and even if policies are directed towards openness, in practice, just a few have the money to afford it. A shift toward a hybrid model, where the intrinsic purpose of higher education is equally acknowledged along with its instrumental purpose should be seen by policy makers as the way forward to create educational systems that are more inclusive and societies that are more knowledgeable and just.

Georgios Giotis

This entry examines how wage-setting institutions (WSIs) shape wages across advanced economies. It focuses on four core mechanisms—minimum wages, collective bargaining, wage coordination, and wage centralization—drawing on theoretical insights, empirical evidence, and cross-country comparisons. The analysis shows that minimum wages safeguard low-paid workers but have heterogeneous employment effects depending on their level and enforcement. Collective bargaining raises average wages and compresses wage inequality, though it can reduce flexibility and create insider–outsider dynamics. Wage coordination stabilizes wage growth, prevents inflationary spirals, and fosters equity, while wage centralization promotes solidarity wages and macroeconomic discipline but may limit adaptability. Using The Organization for Economic Co-operation and Development (OECD) and Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts (ICTWSS) data, the study highlights institutional diversity, ranging from coordinated Nordic models to fragmented liberal systems, and identifies trends toward “organized decentralization”. Policy implications suggest that WSIs should be viewed not as rigidities but as adaptable frameworks that can balance efficiency, equity, and stability when carefully designed. The conclusion emphasizes that the future of wage-setting lies in leveraging institutional complementarities to respond to globalization, technological change, and shifting labor market conditions.

Hao Huang, Shuaihang Yuan, Geeta Chandra Raju Bethala et al.

Policy learning focuses on devising strategies for agents in embodied artificial intelligence systems to perform optimal actions based on their perceived states. One of the key challenges in policy learning involves handling complex, long-horizon tasks that require managing extensive sequences of actions and observations with multiple modes. Wavelet analysis offers significant advantages in signal processing, notably in decomposing signals at multiple scales to capture both global trends and fine-grained details. In this work, we introduce a novel wavelet policy learning framework that utilizes wavelet transformations to enhance policy learning. Our approach leverages learnable multi-scale wavelet decomposition to facilitate detailed observation analysis and robust action planning over extended sequences. We detail the design and implementation of our wavelet policy, which incorporates lifting schemes for effective multi-resolution analysis and action generation. This framework is evaluated across multiple complex scenarios, including robotic manipulation, self-driving, and multi-robot collaboration, demonstrating the effectiveness of our method in improving the precision and reliability of the learned policy.

Xiu Yuan, Tongzhou Mu, Stone Tao et al.

Recent advancements in robot learning have used imitation learning with large models and extensive demonstrations to develop effective policies. However, these models are often limited by the quantity, quality, and diversity of demonstrations. This paper explores improving offline-trained imitation learning models through online interactions with the environment. We introduce Policy Decorator, which uses a model-agnostic residual policy to refine large imitation learning models during online interactions. By implementing controlled exploration strategies, Policy Decorator enables stable, sample-efficient online learning. Our evaluation spans eight tasks across two benchmarks-ManiSkill and Adroit-and involves two state-of-the-art imitation learning models (Behavior Transformer and Diffusion Policy). The results show Policy Decorator effectively improves the offline-trained policies and preserves the smooth motion of imitation learning models, avoiding the erratic behaviors of pure RL policies. See our project page (https://policydecorator.github.io) for videos.

S. B. Makeeva

The article presents the history of the demographic development of one of the Chinese northeastern provinces. Various processes of socio-political, trade, economic, foreign policy and spatial-regional transformations of the PRC in the second half of the XX century influenced the demographic processes of the Chinese border province of Heilongjiang. The purpose of the article is to consider the historical features, factors and reasons for the depopulation of the population of the Heilongjiang province bordering Russia. As a result of studying the natural-climatic, institutional-political and modernization-industrial factors of the historical evolution of Heilongjiang Province, it has been established that the current decline and aging of the population, the decline in the birth rate, the migration of labor resources from the province to other regions of China is a consequence of the reduction of state-owned enterprises, the implementation of a strategy of regional uneven development in 19781999, low investment attractiveness, long-term innovation and technological adaptation of Heilongjiang Province to the rapid pace of Chinas economic development. In the early 1990-ies, when the Soviet Union collapsed and the economy of a neighboring state was in difficult conditions, proximity to Russia did not bring economic growth to Heilongjiang. On the contrary, it was the heavy industry that provided the leading positions for Northeast China in the middle of the XX century that became an obstacle to the economic development of Heilongjiang. In the 1990-ies the reform of state-owned enterprises led to the dismissal of workers who, having lost their jobs, left Heilongjiang province. The decline in the growth rate of the old industrial base in the Northeast of the PRC has had an impact on the fact that Heilongjiang Province has gradually turned from the territory of the main influx of population (19501960-ies) into the territory of the largest outflow of population (2010-ies to the present).

Maryna Tatar

Purpose. The purpose of the article is the assessment of the countries’ food security level and its connection with the agricultural sector results. Methodology / approach. The methodology for calculating the food security level is proposed by international organizations, national authorities, and individual researchers. Due to the fact that food security is a complex flexible concept and cannot be limited to the determination of one separate indicator, we propose to calculate a complex general indicator of food security level using the integral taxonomic estimation method and compare its results with those which provided by international organizations, in particular the Global Food Security Index developed by Economist Impact and supported by Corteva Agriscience and Food Security Index developed by Deep Knowledge Analytics. Results. The article proposes the calculation of countries’ food security level using the integrated rating evaluation method and comparing its results with the results provided by different international organizations, identification of problematic local components of food security, and improving food security mechanism. Correlation coefficients and multivariate regression of dependence of global food security index on affordability, availability, quality and safety, sustainability and adaptation are presented. Functions of subjects of different levels of the hierarchy during interaction to ensure food security are considered. Components of food security ensuring mechanism, which will lead to innovations in food security, are proposed. The obtained results show that the availability of large fertile land and labor resources in the country, and the presence of favorable natural and climatic conditions for farming are insufficient for the high food security level, so it is also necessary to ensure food infrastructure in the country, the concern of the authorities for the citizens standard of living, ensuring political stability, etc. Originality / scientific novelty. The level of food security is calculated and compared with the results of international organizations, using the maximum set of publicly available indicators, which include systems supporting food production, food distribution and supply chains, and food consumption indicators. The indicators that have the greatest impact on the food security level were identified, which will make it possible to influence these indicators timely to ensure a sufficient and acceptable food security level. Practical value / implications. Timely research of ensuring food security, which depends mainly on agricultural  products and is implemented through the possibility of purchasing food, taking into account its price, purchasing power, and availability in the appropriate quantity and quality will lead to social stability, meeting the food necessity, the country's independence from imports, the development of its food production, the creation of reserves to stabilize food security in an emergency, unforeseen circumstances in the future. The results of the research can be useful both for agricultural enterprises and for the authorities, which must pursue a balanced state agricultural policy, take care of farmers’ financing, timely resource provision, and ensure a stable, accessible, sufficient, safe, and balanced nutrition level of the population.

Hasan Yüksel

When analyzing the literature, studies on labor and cinema are seen to have skyrocketed over the last years. Audiences encountered the movie Iftarlik Gazoz, starring Cem Yilmaz and Berat Efe Parlar, in 2016. This study’s ultimate purpose is to analyze the main dynamics that shape the labor markets in Türkiye based on this movie. The movie uses the flashback method to elucidate the dramatic life story of Adem, a successful primary school student, and at the same time to provide significant hints about the life circumstances of the era. The movie takes place in a small Aegean town quite dominated by silent conservatives and involves the political and sociological conditions of the pre-1980s with a fundamental focus on labor markets. Adem’s family does farm labor, and he supports himself with his own labor. He is a hardworking pupil who likes reading. Upon dropping out of primary school in the 5th grade, he went on to work in the summer as an apprentice under Cibar Kemal Usta, the producer of traditional Turkish mineral water. Meanwhile, Adem had been exposed to the socialist indoctrination process by Hasan, the son of the village headman who had abandoned his undergraduate education as a result of student demonstrations. Adem wants to study and learn, and his elder brother, like Hasan, gives him books and works for Adem’s education. After the 1980s military coup, everything turned upside down, and Adem paid the price just like others. The study uses content analysis as its method. As a result of the content analysis, the following four basic themes emerged: the Akhi tradition (master-apprentice relationship), agricultural capitalism and its laborers, trade unionism and labor consciousness, and the conflict between capitalism and socialism. The first section of the study provides information about the literature review. The second section emphasizes the themes, features, and analysis methods in the movie. The last section of the study frames the findings and their analysis that have come to the fore as a result of deciphering the conversations.

Lucian Trestioreanu, Wazen M. Shbair, Flaviene Scheidt de Cristo et al.

With the growing adoption of Distributed Ledger Technologies and the subsequent scaling of these networks, there is an inherent need for efficient and resilient communication used by the underlying consensus and replication mechanisms. While resilient and efficient communication is one of the main pillars of an efficient blockchain network as a whole, the Distributed Ledger Technology is still relatively new and the task of scaling these networks has come with its own challenges towards ensuring these goals. New content distribution concepts like Information Centric Networking, of which Named Data Networking is a worthy example, create new possibilities towards achieving this goal, through in-network caching or built-in native multicasting, for example. We present and evaluate XRP-NDN Overlay, a solution for increasing the communication efficiency for consensus-validation based blockchains like the XRP Ledger. We experiment by sending the XRP Ledger consensus messages over different Named Data Networking communication models and prove that our chosen model lowers the number of messages at node level to minimum necessary, while maintaining or improving blockchain performance by leveraging the possibilities offered by an overlay such as specific communication mechanisms.

Erin N. Mayfield, J. Jenkins, E. Larson et al.

Achieving an economy-wide net-zero emissions goal by mid-century in the United States entails transforming not only the physical energy system, but also the energy workforce. In this study, we develop and demonstrate a labor model, tailored to the context of energy system transitions, and coupled with geospatially-resolved, supply-side energy system activity projections. We find that a net-zero transition supports an annual average of approximately 3 million direct jobs or $200B in wages during the first decade, and approximately 4-8 million direct jobs or $200B-$500B during the 2040s. The modeled supply-side energy workforce represents of 1.5% of the total U.S. labor force in 2020, increasing to 2.5-5% by mid-century. Boom-and-bust cycles arise, with employment and wage losses in declining fossil fuel sectors offset (in aggregate) by increases in low carbon resource sectors. We further estimate training, education, and experience requirements, finding that the diversity of workforce development needs will be similar to historical transitions, but at a much larger scale over a sustained time period. Labor pathways are influenced by policy-mediated factors such as technology selection, pace of infrastructure expansion, infrastructure siting and investment decisions, oil and gas exports, workforce development, labor productivity, and extent of domestic manufacturing. We show that most states have the potential to experience long-term expansion in the supply-side energy workforce, but substantial state-level variation is possible in labor pathways depending on resource availability, siting decisions, and political bargaining.

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.

Jiawei Xu, Cheng Zhou, Yizheng Zhang et al.

We consider the problem of policy transfer between two Markov Decision Processes (MDPs). We introduce a lemma based on existing theoretical results in reinforcement learning to measure the relativity gap between two arbitrary MDPs, that is the difference between any two cumulative expected returns defined on different policies and environment dynamics. Based on this lemma, we propose two new algorithms referred to as Relative Policy Optimization (RPO) and Relative Transition Optimization (RTO), which offer fast policy transfer and dynamics modelling, respectively. RPO transfers the policy evaluated in one environment to maximize the return in another, while RTO updates the parameterized dynamics model to reduce the gap between the dynamics of the two environments. Integrating the two algorithms results in the complete Relative Policy-Transition Optimization (RPTO) algorithm, in which the policy interacts with the two environments simultaneously, such that data collections from two environments, policy and transition updates are completed in one closed loop to form a principled learning framework for policy transfer. We demonstrate the effectiveness of RPTO on a set of MuJoCo continuous control tasks by creating policy transfer problems via variant dynamics.

Ryan Yang, Tom Silver, Aidan Curtis et al.

A longstanding objective in classical planning is to synthesize policies that generalize across multiple problems from the same domain. In this work, we study generalized policy search-based methods with a focus on the score function used to guide the search over policies. We demonstrate limitations of two score functions and propose a new approach that overcomes these limitations. The main idea behind our approach, Policy-Guided Planning for Generalized Policy Generation (PG3), is that a candidate policy should be used to guide planning on training problems as a mechanism for evaluating that candidate. Theoretical results in a simplified setting give conditions under which PG3 is optimal or admissible. We then study a specific instantiation of policy search where planning problems are PDDL-based and policies are lifted decision lists. Empirical results in six domains confirm that PG3 learns generalized policies more efficiently and effectively than several baselines. Code: https://github.com/ryangpeixu/pg3

Ashwin Khadke, Hartmut Geyer

Policy Decomposition (PoDec) is a framework that lessens the curse of dimensionality when deriving policies to optimal control problems. For a given system representation, i.e. the state variables and control inputs describing a system, PoDec generates strategies to decompose the joint optimization of policies for all control inputs. Thereby, policies for different inputs are derived in a decoupled or cascaded fashion and as functions of some subsets of the state variables, leading to reduction in computation. However, the choice of system representation is crucial as it dictates the suboptimality of the resulting policies. We present a heuristic method to find a representation more amenable to decomposition. Our approach is based on the observation that every decomposition enforces a sparsity pattern in the resulting policies at the cost of optimality and a representation that already leads to a sparse optimal policy is likely to produce decompositions with lower suboptimalities. As the optimal policy is not known we construct a system representation that sparsifies its LQR approximation. For a simplified biped, a 4 degree-of-freedom manipulator, and a quadcopter, we discover decompositions that offer 10% reduction in trajectory costs over those identified by vanilla PoDec. Moreover, the decomposition policies produce trajectories with substantially lower costs compared to policies obtained from state-of-the-art reinforcement learning algorithms.

Klimentova Elvira, Dubovitski Alexander, Yurina Elena et al.

The research is aimed at typologizing the regions of Russia in terms of unemployment with a view to improving regional economic policy. The typology of regions was done using the method of groupings. This enabled the authors to distinguish between rural areas including the level of employment. The authors revealed that the major negative trend in the labor market was the decrease in the number of agriculture jobs, which caused the release of labor and the increased unemployment rates in rural areas. Grouping the regions based on the indicator of employment of the rural population in agricultural sector allowed the authors to identify three types of regions (with high, medium and low unemployment rates) for further use as a criterion for differentiating the state policy of regulating the labor market in rural areas (active and passive).

Christof Ferreira Torres, Antonio Ken Iannillo, Arthur Gervais et al.

In recent years, Ethereum gained tremendously in popularity, growing from a daily transaction average of 10K in January 2016 to an average of 500K in January 2020. Similarly, smart contracts began to carry more value, making them appealing targets for attackers. As a result, they started to become victims of attacks, costing millions of dollars. In response to these attacks, both academia and industry proposed a plethora of tools to scan smart contracts for vulnerabilities before deploying them on the blockchain. However, most of these tools solely focus on detecting vulnerabilities and not attacks, let alone quantifying or tracing the number of stolen assets. In this paper, we present Horus, a framework that empowers the automated detection and investigation of smart contract attacks based on logic-driven and graph-driven analysis of transactions. Horus provides quick means to quantify and trace the flow of stolen assets across the Ethereum blockchain. We perform a large-scale analysis of all the smart contracts deployed on Ethereum until May 2020. We identified 1,888 attacked smart contracts and 8,095 adversarial transactions in the wild. Our investigation shows that the number of attacks did not necessarily decrease over the past few years, but for some vulnerabilities remained constant. Finally, we also demonstrate the practicality of our framework via an in-depth analysis on the recent Uniswap and Lendf.me attacks.

Matthew L. Olson, Roli Khanna, Lawrence Neal et al.

Counterfactual explanations, which deal with "why not?" scenarios, can provide insightful explanations to an AI agent's behavior. In this work, we focus on generating counterfactual explanations for deep reinforcement learning (RL) agents which operate in visual input environments like Atari. We introduce counterfactual state explanations, a novel example-based approach to counterfactual explanations based on generative deep learning. Specifically, a counterfactual state illustrates what minimal change is needed to an Atari game image such that the agent chooses a different action. We also evaluate the effectiveness of counterfactual states on human participants who are not machine learning experts. Our first user study investigates if humans can discern if the counterfactual state explanations are produced by the actual game or produced by a generative deep learning approach. Our second user study investigates if counterfactual state explanations can help non-expert participants identify a flawed agent; we compare against a baseline approach based on a nearest neighbor explanation which uses images from the actual game. Our results indicate that counterfactual state explanations have sufficient fidelity to the actual game images to enable non-experts to more effectively identify a flawed RL agent compared to the nearest neighbor baseline and to having no explanation at all.

E. Vinokurov

This paper assesses the current results of the establishment of the Eurasian Economic Union (EAEU). On the one hand, the EAEU has not been an impeccable “success story”. The EAEU's progress has slowed after initial rapid progress. On the other hand, it has achieved much. The EAEU is best viewed not as an exception to general rules of regional economic integration, but rather as a functioning customs union with its own successes and stumbling blocks, enriched by several additional quite developed areas of economic integration. This paper reviews the state of Eurasian institutions, the single market for goods and services, the state of mutual trade and investment flows among member states, ongoing work to eliminate non-tariff barriers, problems pertaining to the efficient coordination of macroeconomic policies, progress toward establishing an EAEU network of free trade areas, the state of the common labor market, and the dynamics of public opinion relative to Eurasian integration in the five member states.