Labor Allocation Research Articles

Language diversity, gender inequality, and aggregate productivity in Canada

AbstractIdentifying sources of barriers to occupational mobility is central to evaluating the efficiency of the labor market. In this paper, we present an augmented Roy model in which workers self‐select into occupations, subject to labor market barriers that are specific to their socio‐linguistic group. Our findings provide evidence of differences in labor market outcomes across gender and linguistic groups in Canada. We argue that these differences could be attributed to barriers to labor mobility and that the reduction of these disparities would result in higher aggregate productivity in the country. In the augmented Roy model, the frictions result in inefficient allocation of labor across occupations. The study quantifies the change in aggregate productivity that would result from reducing the friction. The elimination of the frictions increased aggregate output on average by 6.2% and 4.4% in 1991 and 2011, respectively. This finding highlights the importance of reducing language barriers and gender inequality in the labor market. We provide policy recommendations for mitigating the disparities in socioeconomic outcomes between gender and linguistic groups.

Digital Technology, Factor Allocation and Environmental Efficiency of Dairy Farms in China: Based on Carbon Emission Constraint Perspective

The emission of carbon pollutants stemming from dairy farms has emerged as a significant obstacle in mitigating the effects of global warming. China, being a prominent nation in the field of dairy farming, encounters significant challenges related to excessive component input and elevated environmental pollution. Digital technology presents an opportunity to enhance the factor allocation of dairy farms and thus increase their environmental efficiency. This study utilizes survey data from 278 dairy farms in China to examine the effect of digital technology on the allocation of land, labor, and capital variables in dairy farms. The IV-Probit model, IV-Tobit model, treatment effect model, and two-stage least square technique are employed to empirically analyze these impacts. Simultaneously, the intermediate effect model was employed to examine the mediating function of factor allocation in the effect of digital technology on environmental efficiency. The findings indicate that digital technology has the potential to greatly enhance land transfer and land utilization rates in dairy farms. Additionally, it has been observed that digital technology may lead to a decrease in both the proportion and time of labor input. Furthermore, digital technology has the potential to decrease short-term productive input while simultaneously enhancing long-term productive input within dairy farming operations. Digital technology has been found to have an indirect yet beneficial influence on environmental efficiency. This is mostly achieved through the facilitation of resource allocation, specifically in terms of land, labor, and capital aspects. The article presents a set of policy recommendations, including the promotion of extensive integration of digital technology within dairy farms, the facilitation of optimal allocation of production factors in dairy farms, and the implementation of specialized training programs focused on digital technology.

The Impact of the Digital Economy on Transformation and Upgrading of Industrial Structure: A Perspective Based on the “Poverty Trap”

Breaking the “poverty trap” has gradually become the core topic of economic research. The transformation and upgrading of industrial structure is considered an essential means to break the “poverty trap”. How to use the digital economy effect to change the allocation of capital and labor factors and realize the transformation and upgrading of industrial structure is a significant issue in this paper. The study focuses on examining the development of China’s digital economy between 2013 and 2021, uses the entropy method to measure it, and conducts an empirical study through a fixed-effects model and an intermediary-effect model to investigate the influence and mechanism of the digital economy on industrial structure transformation and upgrading. The results indicate the following: Firstly, the digital economy plays a crucial role in facilitating the transformation and upgrading of industrial structure, and this conclusion was still robust even after controlling for a series of factors affecting the transformation and upgrading of industrial structure and correcting the endogenous estimation deviation by using instrumental variables. Secondly, through the heterogeneity analysis of regions with different economic development levels, it was found that compared with economically developed regions, economically backward regions need to pay more attention to the development of the digital economy. Thirdly, the examination of the mechanism revealed that the digital economy has realized the transformation and upgrading of industrial structure by optimizing the allocation of capital and labor. In this paper, Schumpeter’s innovation theory is regarded as a new perspective to break the “poverty trap” and realize the transformation and upgrading of industrial structure, filling the gap in related research in this field. This study provides a suggestion for economically backward areas to break the “poverty trap” and provides theoretical support and practical guidance for the sustained economic growth of the whole country.

Judicial independence and corporate employment: Evidence from China

We investigate how firms respond to strengthening of judicial independence by examining employment decisions following staggered judicial independence reform in China. We provide robust evidence that the reform leads to salient promotion in employee numbers. Alleviated financing frictions, increased labor demand and improved information quality are three plausible channels that allow independent judicial system to promote corporate employment. Further, we find the reform improves firms’ labor investment efficiency. We estimate that employment effect translates into economically important outcomes in innovation outputs and firm performance. Our paper provides new insights into the real effects of judicial independence on labor allocation and the economy.

Intrahousehold preference heterogeneity and demand for labor‐saving agricultural technology

AbstractEvaluations of agricultural technologies rarely consider the implications of how adoption may alter the labor allocation of different individuals within a household. We examine intrahousehold decision‐making dynamics that shape smallholder households' decision to use mechanical rice transplanting (MRT), a technology that disproportionately influences demand for women's labor. To study the adoption decision, we experimentally estimate the willingness to pay for MRT services both at the individual and household level. We find that women value MRT more than men, especially when they participate in transplanting on their own farms. This preference heterogeneity is evident in the unconditional differences between women's and men's valuation and differences conditional on their individual observable characteristics. Despite having stronger preferences for MRT, women have less influence on the household's technology adoption decision than men. This differential influence over the MRT adoption decision reflects the intrahousehold power structure: in households where women have less control over assets, they also have less influence over the MRT adoption decision. Our results highlight how technological changes interact with unobserved, gender‐based intrahousehold power relations to influence agricultural production decisions and, by extension, the gendered allocation of labor and welfare of women.

Perspectives on trade and structural transformation

ABSTRACT This paper surveys macroeconomic and microeconomic perspectives on the role of international trade in structural transformation. We start by describing canonical frameworks that have been used to quantify how trade influences sectoral shares of employment and value added. We then pivot to survey micro-empirical evidence on the impact of changes in trade on the allocation of labor across sectors and productivity at the firm level. In this, we put special emphasis on the role of participation in global value chains and inward foreign direct investment in mediating these effects. Next, we evaluate evidence on the barriers to trade faced by low-income countries, with special attention to recent work that measures these costs taking firm dynamics into account. We conclude by discussing how these micro-perspectives can be integrated into macro models to advance our understanding of structural change.

Digital Monitoring and its Effects on Organizational Performance

In every successful organization, the critical factors of time, cost, and quality preservation are paramount. Effectively managing and controlling these factors necessitates the implementation of strategic measures. Specifically, the reduction of wastage emerges as a key approach to conserving time, cost, and quality. Achieving this goal hinges on the optimal utilization of organizational resources, which entails precise planning, allocation, monitoring, and control. While various methods for planning and resource tracking exist across organizations, this study focuses on strategies employed within the manufacturing industry. These strategies have demonstrated greater efficiency compared to traditional methods. Moreover, the study proposes the integration of Internet of Things (IoT) technology to address this challenge effectively. The research recommends the use of IoT technology as a comprehensive solution. Prior studies have often utilized the JIT method solely for resource utilization or TPM method solely for resource management. In contrast, this research advocates for the individual application of these methods to plan each resource meticulously. Specifically, the JIT method is proposed for material utilization, the TPM method for equipment utilization, and the Kaizen method for labor allocation. Furthermore, it emphasizes the integration of IoT with these lean methods. While some researchers have explored IoT, they have not fully integrated it with lean methods and techniques. The synergy of lean production methods and IoT technology offers an ideal opportunity for optimizing the utilization of organizational resources. Through these techniques, organizational resources can be efficiently planned and allocated to the production process. IoT provides valuable tools such as sensors, which can be installed at various resources, facilitating real-time data transmission to managers. This enables remote monitoring from office settings and timely data acquisition, thus addressing the challenge of optimal organizational resource utilization effectively.

How does broadband internet affect firm-level labor misallocation: The role of information frictions

This study examines an understudied channel through which information and communication technology (ICT) affects labor markets: specifically, its role in enhancing labor allocation efficiency by mitigating information frictions. To investigate this causal relationship, we take advantage of the natural experiment created by the arrival of broadband internet in China in 2000. We employ a difference-in-differences (DiD) estimation strategy, supplemented by instrumental variables (IV) derived from the average incidence rates of lightning and a theoretically optimal backbone network construction plan. Our results show that the arrival of broadband internet markedly alleviates information frictions in labor markets, leading to a significant reduction in firm-level labor misallocation. The effects arising from the decline in information frictions ease the labor shortage problem faced by firms and are more significant in areas with more developed information-sharing networks. Lastly, we estimate the lower bound of the effect of changes in misallocation on treated cities' aggregate productivity, which is 6.3%.

Long-Run Labor Costs of Housing Booms and Busts

Abstract We show large flows of workers into the real estate agent (REA) occupation during the early 2000s from virtually all parts of the skill, wage, and education spectrums. We find those entering REA in Metropolitan Statistical Areas (MSAs) with house price bubbles end up in occupations paying significantly less in the long-run as compared to similar REA entrants in non-bubble areas. Even in 2017, when house prices and employment return to their pre-crisis levels, REA entrants in Bubble MSAs are in occupations earning about 6% less. These results point to lasting effects of labor allocation decisions in response to distorted price signals.

Labor elasticities, market failures, and misallocation: Evidence from Indian agriculture

AbstractThis article presents evidence of misallocation across households in rural Indian agriculture. I show that household demographics predict own farm labor demand for smallholder farmers but not non‐smallholder farmers. A simple model of labor allocation predicts a clear consequence of this duality: smallholder farmers will reallocate labor across plots less in response to price changes than non‐smallholders. Detailed household panel data confirms this theoretical prediction. Three additional facts suggest that a lack of off‐farm labor opportunities may be partly responsible for the behavior of smallholders, leading smallholders to over allocate labor to agricultural production. First, smallholders report fewer hours of involuntary unemployment when their own crop prices increase. Second, yield is substantially higher for smallholders on plots of the same size. Finally, estimated marginal revenue products of labor are consistently lower for smallholders.

Women’s Contingent Work and Allocation of Domestic Labor in South Korea

Women’s Contingent Work and Allocation of Domestic Labor in South Korea

Inherent mechanism of digital technology application empowered corporate green innovation: Based on resource allocation perspective

Confronted with the treacherous digital wave and the aggressive environmental challenges, digital technology and green innovation are becoming critical tools for corporations to secure a sustainable advantage. The significance of identifying the role of digital technology application on corporate green innovation has been widely debated in the extant literature. Nevertheless, few researchers have investigated the inherent mechanism between them from the resource allocation perspective. From this research gap, we construct a theoretical model of the inherent mechanism by which digital technology application affects corporate green innovation, validate it using listed corporations in China from 2011 to 2020, and further investigate the differences in their inherent mechanism triggered by property rights and industry competition. We found that digital technology application is effective in promoting corporate green innovation. Stronger green innovation effect of digital technology application in state-owned corporations and those in highly competitive industries. The inherent mechanism between them manifest in optimizing the allocation of conventional labor, expanding the scale of non-conventional labor, and enhancing investment in R&D and digital infrastructure capital. We further explored that the impact of applying digital technology to optimize conventional labor allocation, expand non-conventional labor scale, and enhance investment in R&D and digital infrastructure capital is stronger for corporations in highly competitive industries than those in lowly competitive industries. The difference is that the role of the digital technology application in boosting capital investment in R&D does not differ across corporations with different property rights. Findings provide theoretical and empirical evidence on effectively developing the digital technology application's green innovative effects.

A Survey on Fair Allocation of Chores

Wherever there is group life, there has been a social division of labor and resource allocation, since ancient times. Examples include ant colonies, bee colonies, and wolf colonies. Different roles are responsible for different tasks. The same is true of human beings. Human beings are the largest social group in nature, among whom there are intricate social networks and interest networks between individuals. In such a complex relationship, how do decision makers allocate resources or tasks to individuals in a fair way? This is a topic worthy of further study. In recent decades, fair allocation has been at the core of research in economics, mathematics and other fields. The fair allocation problem is to assign a set of items to a set of agents so that each agent’s allocation is as fair as possible to satisfy each agent. The fairness measurements followed in current research include envy-freeness, proportionality, equitability, maximin share fairness, competitive equilibrium, maximum Nash social diswelfare, and so on. In this paper, the main concern is the allocation of chores. We discuss this problem in two parts: divisible and indivisible. We comprehensively review the existing results, algorithms, and approximations that meet various fairness criteria in chronological order. The relevant results of achieving fairness and efficiency are also discussed. In addition, we propose some open questions and future research directions for this problem based on existing research.

Recycled and non-recycled exhaustible resource: an optimal control strategy for input allocation

The United Nations aim to perform a transition toward a sustainable environment where people can live by decoupling economic growth from resource use. Through the definition of the Agenda 2030 and the corresponding sustainable development goals, this transition asks for a lower dependence on non-renewable resources and for the use of recycled materials in a finite term perspective. In this respect, we provide an optimal control model which searches for an efficient allocation of labor between non-recycling and recycling sectors exploiting a given non-renewable resource. The optimization process is carried out over a finite time horizon in accordance with the need of rapidly achieving the targets imposed by the ecological transition. By employing the classical tools of optimal control theory, a complete theoretical analysis of the model well-posedness is developed under the assumption of linear production in both sectors. The approach is applied in order to simulate a hypothetical test case.

Who has the time? A qualitative assessment of gendered intrahousehold labor allocation, time use and time poverty in rural Senegal

Achieving gender equality in agricultural development is fundamental to reductions in global poverty, hunger, and malnutrition. African women make important contributions to farming and food systems; however, their efforts are often hindered by inefficient and inequitable allocations of intrahousehold labor and time that render women time poor. Time poverty is a root cause of women’s marginalization in rural Africa and an important area of inquiry for feminist scholarship. While gendered time use and time poverty have been researched in many different contexts and countries in Africa, significant knowledge gaps remain. Most studies consider women’s time use divorced from gendered relations, and overlook children’s contributions. Other factors which may combine to influence women’s time burden but are often overlooked include seasonality, work intensity, household structure and composition, cultural norms, familial relationships and intrahousehold power dynamics. Further, the majority of research on gendered time use and time poverty in Africa uses quantitative methods applied to secondary data, which presents challenges for critically identifying and characterizing the confluence of various intrahousehold dynamics which impact women’s multiple roles, responsibilities, and consequently their work and time. This study adds important nuance to the existing body of research by offering an in-depth, qualitative assessment of intrahousehold labor allocation, time use, and time poverty amongst women, men, and children living in multi-generational, largely polygamous households reliant on peanut-farming in the Kaolack region of Senegal. Data collection took place in February 2020, with 111 individuals in three villages. We find that individual workload correlates with gender and age, but is further determined by the demographic composition of the household, the roles assumed by the individual and other family members, and the individual’s place within the social hierarchy. Women and girls in Kaolack are clearly at more risk of time poverty due to their dual responsibility for reproductive and productive work, especially during the rainy season. Furthermore, women’s workload in particular changes over the life course as they assume different roles in different life stages. As a result, women with older daughters and, especially, daughters-in-law are significantly less time poor than other women.

Renewable energy adoption and rural livelihoods in Ethiopia

AbstractThe introduction of new policies promoting decentralized energy technologies is likely to have profound effects across all the nexus activities, including agricultural production, input use, and labor allocations. Thus, this paper analyzes the potential synergies and trade‐offs created by the adoption of renewable energy technologies along the water–energy–food security nexus in Ethiopia. We use a mathematical programming‐based household model to compare the impacts of fossil‐based and renewable energy use on rural households’ livelihoods. Our findings show that only a 10% subsidy to the price of biogas digester considerably changes the energy mix of all types of households and increases the use of decentralized modern energy sources. Household crop production patterns are not changed substantially as a consequence of the biogas subsidy, despite the competition over resources between crop and energy production. Nonetheless, the subsidy policy can lead to family labor reallocation from collecting fuelwood to agricultural activities. Moreover, the biogas subsidy can improve household incomes. Specifically, the findings indicate that 10% biogas subsidy can lead to 0.93% and 3.44% increases in the net incomes of wealthier and poorer households, respectively, compared to the business‐as‐usual scenario, that is, also has a pro‐poor dimension. Sensitivity analyses are carried out and it appears among others that more subsidy of the price of biogas digester leads to an increase in the net income of the two household types. Overall, the benefits generated by the biogas subsidy in terms of increases in net household incomes outweigh the total costs of the subsidy program. The findings indicate the importance of the subsidy policy to improve rural households’ welfare.

Early-Season forecasting of citrus block-yield using time series remote sensing and machine learning: A case study in Australian orchards

This study presents a comprehensive evaluation of seasonal, locational, and varietal variations in canopy reflectance responses in 315 commercial citrus blocks from three major growing regions in Australia. The dataset includes three different citrus types (Mandarin, Navel, Valencia) and 26 varieties. The aim is to utilize this combined information to better understand yield variation and develop improved forecasting models. Landsat satellite data spanning from October 2006 to February 2021 (1419 tiles) were used to derive reflectance values, and calculate four vegetation indices (NDVI, GNDVI, LSWI, and GCVI), for each citrus block. These indices were then analyzed alongside corresponding yield data, which consisted of 3660 individual yield records dating back to 2007. Two temporal resolutions were incorporated as predictors: spatio-temporal vegetation index time series (TS) aggregated every two months and annual time series of historical block-yield records. Six statistical and machine learning algorithms were calibrated using a leave-one-year-out cross-validation approach (LOYO CV) and validated for one-year forward prediction over a five-year period (2017–2021). The results highlight significant yield variations across years, alternate bearing patterns, and spatio-temporal changes in reflectance profiles influenced by seasonal conditions, varietal characteristics, and locations. The support vector machine (SVM) algorithm with a radial basis function kernel consistently outperformed other algorithms, indicating a non-linear relationship between citrus yield and predictors. The SVM model achieved an RMSE of 15.5 T ha−1, R2 of 0.88, MAE of 12.1 T ha−1, and MAPE of 29% in predicting block-yield across farms, varieties, and seasons. These prediction accuracy metrics demonstrate an improvement over current forecasting methods. Notably, the proposed approach utilizes freely available imagery, provides forecasts between two to nine months before harvest, and eliminates the need for infield counting of fruit load for image calibration. This approach provides an improved method for understanding seasonal yield variation and quantifying citrus block-yield, offering valuable insights for growers in harvest logistics, labor allocation, and resource management.

Impact of labor and energy allocation imbalance on carbon emission efficiency in China's industrial sectors

Greenhouse gas emission is the focus of global climate change concerns. The change in industrial structure can impact carbon emission efficiency (CEE) by affecting labor and energy input. However, there is an obvious imbalance of labor and energy allocation within China's industrial sectors. Here, we use the super-slacks-based model data envelopment analysis (Super-SBM-DEA) to calculate the CEE of 32 industrial sectors and adopt the Tobit model to analyze the impact of industrial allocation imbalance on CEE. The results show that the overall industry and manufacturing CEE is still at a low level, with an average CEE of 0.53. The industrial sectors with higher CEE are these sectors with advanced innovative technology and low energy consumption. The results of the Tobit model show that the imbalance of labor and energy allocation is the key factor limiting carbon emission efficiency improvement. Furthermore, the imbalance of labor allocation hurts the CEE of labor-intensive sectors. The coefficient of labor allocation imbalance (distL) is −2.483, and the inflow of labor can improve the CEE of non-labor-intensive sectors. The CEE of energy-intensive sectors is sensitive to the imbalance of energy allocation, the marginal impact of energy allocation imbalance (distE) is −2.296. Improving energy efficiency is a key task to reduce carbon emissions in sectors relying on energy input. But for non-energy-intensive sectors, optimizing energy allocation has a limited effect on reducing carbon emissions. This research can provide insights for emerging economies to coordinate carbon reduction and industrial transformation.

Efficient Workforce Planning with a Labour Allocation System

Abstract: The primary objective of this project is to develop a web-based application for the allocation of work to daily wage workers. Effective management of labour resources is crucial to the success of fieldwork. The assignment of labour to work constitutes one of the most vitally significant and successful processes in the management of labour resources. Consequently, estimating labour shortages and evaluating various labour resource allocation strategies can facilitate the allocation process. By utilising a system dynamics approach, a dynamic model is proposed for workforce allocation. The project is able to achieve this through the model that is presently provided in this study

Heterogeneity and threshold in the effect of agricultural machinery on farmers' relative poverty.

Machinery is commonly used in the modernization of agricultural industries and is a pivotal way to eliminate poverty among farmers. However, there are still disputes regarding the effects of agricultural machinery on farmers' relative poverty. Neither the heterogeneity nor the thresholds in agricultural machinery-led poverty reduction efforts have been discussed in depth. To address those gaps, this study considers farmers' livelihood factors and resource (in)divisibility to investigate how agricultural machinery affects farmers' relative poverty as well as the heterogeneity of and thresholds in that influence. This study collected data from 1118 Chinese farming households. 2SLS-IVTobit regression results show that a 1% increase in the overall level of agricultural machinery leads to a 3.3% increase in farmers' income and a 0.523% decrease in their relative poverty. Furthermore, the three pathways of cost-saving, production efficiency, and labor allocation efficiency are identified as explaining 25.4%, 21.9%, and 21.3% of relative poverty reduction, respectively. The heterogeneity of these effects across different farming stages (i.e., plowing, sowing, and harvesting) is also examined, and the results show that plowing machinery has the largest effect. Then, a threshold analysis is conducted, which shows that farmers are influenced more when the scale of their farms surpasses the threshold of 1.12 hm2. Theoretically, this study establishes an integrated model that depicts how agricultural machinery affects farmers' relative poverty through production (in)divisibility. Practically, this study recommends additional investment in agricultural machinery (especially plowing machinery), farmland integration, and taking targeted measures to facilitate resource divisibility.