Heterogeneous Workers Research Articles

The Labor Market and Growth Implications of Skill Distribution: A Dynamic General Equilibrium Model with Skill Heterogeneity

This paper develops a dynamic general equilibrium model which explicitly incorporates the skill distribution of heterogeneous workers. Workers are distributed heterogeneously in their individual skill level and can be endogenously sorted into different tasks using different technologies. In doing so, we study in depth the labor market and growth implications of the changes in skill distribution. Specifically, we consider two changes in the skill distribution in a given population, (i) the increased density in the upper tail (skill upgrading), and (ii) the increased density both in the lower and upper tails (skill polarization). It is shown that, though the labor market implications for individual workers are likely to be largely different and complex (skill polarization even leads to nonlinear labor market changes), both changes in the skill distribution may increase steady-state real investment and enhance growth so that all workers gain with time.

Relationship between human capital and entrepreneurship orientation from the intellectual capital perspective of innovative literacy

PurposeThis study measures the relationship between human capital and innovative literacy from the perspective of intellectual capital. For this purpose, the relationship between human capital and innovative literacy was first investigated to measure intellectual capital. Subsequently, the moderating effect of entrepreneurial orientation on the influence of innovative literacy on human capital was also analysed.Design/methodology/approachThis study analyses the relationship between innovative literacy, human capital and entrepreneurial orientation through structural equation modelling – the study sample comprised 457 participants in Türkiye.FindingsThe results suggest a positive relationship between human capital, a sub-component of intellectual capital and innovative literacy. Innovative literacy can influence intellectual capital and increase value. Our finding further confirms that entrepreneurial orientation has no moderating effect on the same relationship.Research limitations/implicationsDespite the observed correlation between IL and HC growth, this study had some limitations. First, the generalisability of the findings is limited because the sample was selected from individuals with a high level of education in Türkiye. Despite these limitations, this study has important theoretical and practical implications for developing countries. Türkiye is a developing country, and the selected sample is the most critical database in the country for an Innovative Literacy Scale. However, future research could focus on whether there is a potential source of bias and collect and compare data from heterogeneous workers. In addition, research on existing research frameworks in other countries may consider varying levels of education and business sectors. This research aims to be a pioneering initiative towards the advancement of IL. The question of whether IL should be considered equivalent to or a subset of HC, which has been previously proposed as a dimension of IC, can be clarified through a thorough examination of what IL means.Practical implicationsIn a theoretical framework, transforming human capital into value through innovations derived from innovative literacy activities will significantly increase the company's intellectual capital. Organizations in which innovative literacy play an important role achieve organizational goals, strengthen commitment and contribute to sustainability through the emergence of new potential innovative individuals. This research also contributes significantly to the existing literature. Initially regarding theoretical implications, this study examines the concept of innovative literacy in the existing literature on intellectual capital, human capital and entrepreneurial orientation. Additionally, this study offers a new perspective on intellectual capital.Social implicationsThe findings of this research also provide managerial outcomes. Initially, the assessment of concepts, research and development capabilities and efficient knowledge management are indicators of innovative literacy proficiency at the individual level. Human capital is a subcomponent of intellectual capital and refers to knowledge, skills and experience. Innovative and literate team members should be developed in order to strengthen the intellectual capital structure of an organization.Originality/valueThis study contributes to understanding innovative literacy from an intellectual capital perspective using the Innovative Literacy Scale to reveal important dimensions that influence innovative literacy. Using a measurement tool with new sub-dimensions not included in the extant literature on intellectual capital is unique. This study suggests that scholars should include innovative literacy – a distinct subset of intellectual capital – in their body of knowledge on human capital. Our findings have the potential to help meet the needs of human resource departments, researchers, educational institutions, public institutions and enterprises.

HMAE: a high-fidelity multi-agent simulator for economic phenomenon emergence

Economic models based on multi-agents are increasingly attracting attention and can provide a new perspective for exploring the causes behind social phenomena at the individual level. Existing research usually adopts society-level learning methods, and more research on micro-level heterogeneity among individuals is needed. For this, we propose a high-fidelity multi-agent economy (HMAE) model based on evolutionary game theory, including three types of agents: workers, firms, and the government. In particular, we characterize worker heterogeneity regarding laziness factors, work endowments, and commuting distances. These agents continuously and iteratively update their strategies by randomly exploring and imitating their neighbors to maximize their utility value. We simulated the evolution process of agent behavioral decisions through experiments and found that individual heterogeneity can significantly affect the decisions of workers and firms. These phenomena are consistent with some economic evolution trends in real life, and our research can provide an analytical tool for analyzing the causes of emerging economic phenomena.

The leadership gap between full-time and part-time female employees

Employers interpret high numbers of contractual working hours of part-time employees as a signal for high work engagement, qualifying them for a leadership position. However, signals do not work equally well in all environments. We suggest that the value of a signal depends on corporate culture, being relatively low in companies with strict work regimes where employees are expected to be available and visible. We test this prediction combining data on female employees and their employers. Our analyses show that the positive effect of contractual hours on leadership positions varies systematically with the difference between the contractual working hours of full-time and part-time employees. The smaller the working time difference between a full-time and a part-time employee, the more likely it is that the part-timer is in a leadership position. In addition, the more a firm relies on overtime and requires strict presence at work, the larger is the statistical association between high contractual hours and leadership positions at individual level. In a world where work-life balance is increasingly important, this research provides new insights into the heterogeneity of part-time workers and the design of corporate cultures and policies to create sustainable work environments.

What Lies behind the Returns to Schooling: The Role of Labor Market Sorting and Worker Heterogeneity

Abstract Do more educated workers earn higher wages partly because they have access to high-paying firms and occupations? We rely on linked employer-employee data to combine the estimation of AKM models with the decomposition of the returns to schooling. We exploit exogenous variation in education driven by changes in compulsory education. We show that education provides access to better-paying workplaces and occupations: 30 percent of the overall return to education operates through the workplace channel and 12 percent through the occupation channel. The remainder is associated exclusively with the individual. Match quality plays a modest role in the returns to education.

Monopsony Power in the Labor Market: From Theory to Policy

Labor markets are not perfectly competitive: Monopsony power enables employers to pay workers less than the marginal revenue product of labor. We review three theoretical frameworks explaining monopsony power. Oligopsony models attribute it to strategic interactions among a limited number of firms. Job differentiation models cite imperfect job substitution and heterogeneous worker preferences. Search-and-matching models point to search frictions hindering instantaneous access to all available jobs. We then develop a theory-informed discussion of the empirical evidence on antitrust policies, policies that reduce barriers to job switching, and policies countering monopsony's effects on workers. Preventing mergers and regulating noncompetition agreements can increase wages by preserving competition among employers. Minimum wages can mitigate the effect of monopsony power by increasing wages without reducing employment. The insights garnered from both theoretical models and empirical evidence offer a road map for crafting policies that can enhance competition in the labor market.

Monetary non-neutrality in a multisector economy: The role of risk-sharing

We show that the degree of risk-sharing among heterogeneous workers is a key determinant of monetary non-neutrality in a multisector sticky-price model. In this framework, workers are employed across different sectors, earning distinct wages. The limited ability of workers to fully insure against labor income risks results in strategic complementarity in firms' price-setting decisions with respect to aggregate shocks and strategic substitutability with respect to idiosyncratic shocks. These pricing interactions lead to sluggish adjustments of the price level in response to monetary and other aggregate shocks, causing significant fluctuations in the output gap while maintaining large responses of individual prices to idiosyncratic shocks. We illustrate these results across three stylized asset market scenarios: complete markets, non-contingent bond-only markets, and financial autarky.

Trigonometric-based mechanisms hybridized African vulture optimization algorithm for multi-manned disassembly line balancing involving worker heterogeneity and collaboration

Trigonometric-based mechanisms hybridized African vulture optimization algorithm for multi-manned disassembly line balancing involving worker heterogeneity and collaboration

WBSP: Addressing stragglers in distributed machine learning with worker-busy synchronous parallel

Parameter server is widely used in distributed machine learning to accelerate training. However, the increasing heterogeneity of workers’ computing capabilities leads to the issue of stragglers, making parameter synchronization challenging. To address this issue, we propose a solution called Worker-Busy Synchronous Parallel (WBSP). This approach eliminates the waiting time of fast workers during the synchronization process and decouples the gradient upload and model download of fast workers into asymmetric parts. By doing so, it allows fast workers to complete multiple steps of local training and upload more gradients to the server, improving computational resource utilization. Additionally, the global model is only updated when the slowest worker uploads the gradients, ensuring the consistency of global models that are pulled down by all workers and the convergence of the global model. Building upon WBSP, we propose an optimized version to further reduce the communication overhead. It enables parallel execution of communication and computation tasks on workers to shorten the global synchronization interval, thereby improving training speed. We conduct theoretical analyses for the proposed mechanisms. Extensive experiments verify that our mechanism can reduce the required time to achieve the target accuracy by up to 60% compared with the fastest method and increase the proportion of computation time from 55%–72% in existing methods to 91%.

Faster, taller, better: Transit improvements and land use policies

We study the interaction between transit improvements and land use policies. Bengaluru, one of India’s largest cities, inaugurated a metro system in 2011 but has extremely low building heights, even near metro stations. We build a rich dataset and a quantitative spatial model in which heterogeneous workers choose among different commuting modes. We find that the metro increases citywide output and welfare, even net of costs. However, the net gains are several times larger with transit-oriented development (TOD), i.e., when height limits are relaxed near stations. Moreover, TOD and the construction of the metro are complementary policies.

Heterogeneity and wage growth of full-time workers in Japan: An empirical analysis using micro data

In this paper we examine the driving forces of fluctuations in wage growth of full-time workers in Japan, taking into account the heterogeneity of wage structures among the workers and using micro data including those from the Basic Survey on Wage Structure. To this end, we first divide full-time workers into two classes with distinct wage structures, based on a finite mixture model estimated using various characteristics of the workers and the firms they work for. We find that the two classes correspond to what previous studies have called an "internal labor market," where labor is reallocated within firms and wages follow a seniority-based system under long-term employment practices, and an "external labor market," where labor moves across firms and wages are mainly determined by supply and demand factors in the market. We next analyze the effects of economic factors on individual full-time workers' wage growth rates. We show that in the internal labor market, neither labor market conditions at the industry and firm-size level nor the output gap at the macro level have influenced the wage growth rates in recent years at least until 2021, while higher potential growth has increased them. By contrast, in the external and the overall labor markets for full-time workers, improvements in labor market conditions and the output gap have accelerated the wage growth rates, even in recent years.

Model and heuristics for the multi-manned assembly line worker integration and balancing problem

This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products.

A Study Comparing Waiting Times in Global and Local Queuing Systems with Heterogeneous Workers

A virtual marketplace or service-providing system must ensure minimal task response times. Varying working rates among the human workers in the system can lead to longer delays for certain tasks. The waiting time in the queue is crucially affected by the queueing architecture used in the system, whether global or local. Studies generally favor global queue systems over local ones, assuming similar processing rates. However, system behavior changes when workers are heterogeneous. In this research, we used simulation to compare the waiting times of tasks assigned to three categories of processing rates in both architectures and with various routing policies in local queues. We found that when using random tie-breaking, there was a correlation between waiting time duration and the proportion of tie-breaking events. Performance is improved when controlling these events using scheduling awareness of the workers’ processing rates. The global queue outperforms local queues when the workers are homogeneous. However, the push mechanisms that control the assignment processes and heterogeneity-aware algorithms improve local queue system waiting times and load balance. It is better than global queues when tasks are assigned to medium and fast workers, but it also enables specific slow workers’ assignments.

Low-carbon policy and employment: heterogeneity of workers with different skills

Low-carbon policy and employment: heterogeneity of workers with different skills

Urban Transit Infrastructure and Inequality

Abstract We propose a quantitative spatial model featuring heterogeneous worker groups and their travel to consume non-tradable goods and services. We consider the opening of the Downtown Line (DTL) in Singapore, which connected regions where high-income households have residential amenities to where non-traded sectors are productive. Leveraging transit farecard data, we show that high-income workers saw large welfare gains but low-income workers gained little. Everyone enjoyed improved access to consumption opportunities, but low-income jobs in non-tradables moved to less attractive workplaces. Abstracting from consumption travel understates the disparate impact across worker groups three-fold.

STATISTICAL DISCRIMINATION AND DURATION DEPENDENCE IN A SEMISTRUCTURAL MODEL

AbstractThis article develops a job‐search model with unobserved worker heterogeneity and learning about worker types from unemployment duration. The model features negative duration dependence that stems from unobserved heterogeneity, skill depreciation, and statistical discrimination. We estimate job‐finding rates implied by our model using microlevel data from the Current Population Survey. We find that removing interview costs counterfactually, thereby eliminating statistical discrimination, substantially increases the job‐finding rates of the long‐term unemployed. The performance of low‐skill workers at the interview stage with discriminating firms plays a key role in explaining our counterfactual result.

Too Many Meetings? Scheduling Rules for Team Coordination

Workers in knowledge-intensive industries often complain of having too many meetings, but organizations still give little thought to deciding when or how often to meet. We investigate the efficiency and robustness of various coordination scheduling rules. We consider workers who are engaged in a common activity (e.g., software programming) that can be divided into largely independent, parallel production tasks, but that necessitates periodic coordination. Coordination enables workers to address issues they have encountered in their independent work but takes time away from production. Using a stylized game-theoretic model, we show that small teams allow a more fluid, that is, worker-driven, approach to scheduling coordination, such as preemptive coordination (or production), under which any worker can impose coordination (or production). In larger teams this becomes inefficient. Several approaches can mitigate this effect. One option is to allocate the decision rights to produce or coordinate to the most productive worker. A more general version is to implement a voting-based scheme, where a minimum number of workers from a predetermined subset choose to coordinate. A third approach is to modify the preemptive coordination and production rules by adding time-based controls, to reserve some minimal amount of productive time or to enforce coordination after some point. Finally, a fixed-interval meeting schedule works well for very large teams. Our research helps formalize the tension between meeting (coordinating) and producing and indicates how to adapt team coordination scheduling rules to the degree of worker heterogeneity and team size. This paper was accepted by Jay Swaminathan, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.03227 .

Computation and Communication Efficient Federated Learning With Adaptive Model Pruning

Federated learning (FL) has emerged as a promising distributed learning paradigm that enables a large number of mobile devices to cooperatively train a model without sharing their raw data. The iterative training process of FL incurs considerable computation and communication overhead. The workers participating in FL are usually heterogeneous and the workers with poor capabilities may become the bottleneck of model training. To address the challenges of resource overhead and system heterogeneity, this paper proposes an efficient FL framework, called FedMP, that improves both computation and communication efficiency over heterogeneous workers through adaptive model pruning. We theoretically analyze the impact of pruning ratio on training performance, and employ a Multi-Armed Bandit based online learning algorithm to adaptively determine different pruning ratios for heterogeneous workers, even without any prior knowledge of their capabilities. As a result, each worker in FedMP can train and transmit the sub-model that fits its own capabilities, accelerating the training process without hurting model accuracy. To prevent the diverse structures of pruned models from affecting the training convergence, we further present a new parameter synchronization scheme, called Residual Recovery Synchronous Parallel (R2SP). Besides, our proposed framework can be extended to the peer-to-peer (P2P) setting. Extensive experiments on physical devices demonstrate that FedMP is effective for different heterogeneous scenarios and data distributions, and can provide up to 4.1× speedup compared to the existing FL methods.

The unequal effects of trade and automation across local labor markets

We quantify the joint impact of the China shock and automation of labor, across US commuting zones (CZs) in the period 2000–2007. To this end, we employ a multi-sector gravity model of trade with Roy-Fréchet worker heterogeneity across sectors, where labor input can be automated. Automation and increased import competition from China are both sector-specific; they lead to contractions in a sector’s labor demand and a decline in relative income for CZs more specialized in that sector, amplified by a voluntary reduction in hours worked and an increase in frictional unemployment. The estimated model fits well with the aggregate performance of manufacturing subsectors and with the variation across CZs in changes in average income, the hourly wage, hours worked, the employment rate and employment in manufacturing. By itself, the China shock has stronger distributional effects than automation, but its impact on aggregate gains is less than a third of automation’s impact.

Inequality and technological change

We study how technological change affects between‐ and within‐education‐group inequality in the United States. We develop a model with heterogeneous workers and firms in which the demand for skills is characterized by firms' recruiting behavior. We use the model to quantify the relative contribution of two types of technological change that affect the relative demand for skilled labor: technological change in firm‐specific productivity and technological change in labor productivity. We find that technological change in labor productivity, in the form of higher returns to skill in production, is the main driver of the increase in between‐ and within‐group inequality. Technological change in firm productivity, in the form of higher firm productivity dispersion, plays a less important role in explaining rising inequality, except for the increase in within‐group inequality for workers without a college degree.