Modelling long-term COVID-19 impacts on the U.S. workforce of 2029

While ensuring employment opportunities is critical for global progress and stability, workers are now subject to several disruptive trends, including automation, rapid changes in technology and skill requirements, and transitions to low-carbon energy production. Yet, these trends seem almost insignificant compared to labor impact of the COVID-19 pandemic. While much has been written about the pandemic’s short-term impacts, this study analyzes anticipated long-term impacts on the labor force of 2029 by comparing original 2029 labor projections to special COVID-adjusted projections recently published by the US Bureau of Labor Statistics. Results show that future demand for nearly every type of labor skill and knowledge will increase, while the nature of work shifts from physical to more cognitive activities. Of the nearly three million jobs projected to disappear by 2029 due to COVID, over 91% are among workers without a bachelor’s degree. Among workers with a degree demand shifts primarily from business-related degrees to computer and STEM degrees. Results further show that the socialness of labor, which is important for both innovation and productivity, increases in many more industries than it decreases. Finally, COVID will likely accelerate the adoption of teleworking and slightly decrease the rate of workforce automation. These impacts, combined with a shift to more cognitive worker activities, will likely impact the nature of workforce health and safety with less focus on physical injuries and more on illnesses related to sedentary lifestyles. Overall, results suggest that future workers will need to engage more often in training and skill acquisition, requiring life-long learning and skill maintenance strategies.

Skill-driven recommendations for job transition pathways

Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or production is moved abroad. Perhaps it is a global crisis, such as COVID-19, which shutters industries and displaces labor en masse. Regardless of the impetus, people are faced with the challenge of moving between jobs to find new work. Successful transitions typically occur when workers leverage their existing skills in the new occupation. Here, we propose a novel method to measure the similarity between occupations using their underlying skills. We then build a recommender system for identifying optimal transition pathways between occupations using job advertisements (ads) data and a longitudinal household survey. Our results show that not only can we accurately predict occupational transitions (Accuracy = 76%), but we account for the asymmetric difficulties of moving between jobs (it is easier to move in one direction than the other). We also build an early warning indicator for new technology adoption (showcasing Artificial Intelligence), a major driver of rising job transitions. By using real-time data, our systems can respond to labor demand shifts as they occur (such as those caused by COVID-19). They can be leveraged by policy-makers, educators, and job seekers who are forced to confront the often distressing challenges of finding new jobs.

GRAHAM’S THEORY OF INTERNATIONAL VALUES REVISITED: A RICARDIAN TRADE MODEL WITH LINK COMMODITIES

Frank D. Graham (1890–1949) presented an innovative multi-country, multi-commodity trade model that attached great importance to link commodities and quantity adjustments, not perfect specializations and price adjustments as emphasized by John Stuart Mill and Alfred Marshall. However, due to some shortcomings, this model was not sufficiently understood and has been forgotten. This study reconstructs Graham’s theory of international values by rectifying the shortcomings. Through this reconstruction, the following is clarified. First, in multi-country, multi-commodity trade models, the existence of link commodities is general and perfect specializations seldom appear; therefore, quantity adjustments are normally performed in the face of demand shifts. Second, notwithstanding unchanging sectoral productivity at a national level, national wage rates can vary greatly according to the patterns of the international division of labor. Third, while the domestic relative wage rate increases with an increase in a home country’s productivity of link commodities, it does not increase with an increase in the productivity of commodities produced only in the home country.

GFPMX: A Cobweb Model of the Global Forest Sector, with an Application to the Impact of the COVID-19 Pandemic

The GFPMX projects forest area and stock, consumption, production, imports, exports, and prices of industrial roundwood, fuelwood, sawnwood, wood-based panels, wood pulp, and paper and paperboard in 180 countries, and currently from 2018 to 2070. The core principle of the model is the cobweb theorem, according to which markets are not necessarily in equilibrium, but take some time to adjust to shocks—such as demand shifts—leading to oscillatory dynamics of prices and quantities. This paper presents the model’s structure and the estimation of its parameters from international statistics on production, trade, forest area, and forest stock. This is followed by an application of the GFPMX to the impact on the global forest sector of the economic recession caused by the COVID-19 pandemic.

Graham’s Theory of International Values Revisited: A Ricardian Trade Model with Link Commodities

F. D. Graham (1890–1949) presented an innovative multi-country, multi-commodity trade model that attached great importance to link commodities and quantity adjustments, not perfect specializations and price adjustments as emphasized by J. S. Mill and A. Marshall. However, due of some shortcomings, this model was not sufficiently understood and has been forgotten. This study reconstructs Graham’s theory of international values by rectifying the shortcomings. Through this reconstruction, the following is clarified. First, in multi-country, multi-commodity trade models, the existence of link commodities is general and perfect specializations seldom appear; therefore, quantity adjustments are normally performed in the face of demand shifts. Second, notwithstanding unchanging sectoral productivity at a national level, national wage rates can vary greatly according to the patterns of the international division of labor. Third, while the domestic relative wage rate increases with an increase in a home country’s productivity of link commodities, it does not increase with an increase in the productivity of commodities produced only in the home country.

Investor response to vaccine signposts sectoral shifts

Significance Millions of people and companies predict the future every microsecond through their equity investments. Investors’ behaviour following the news of the vaccine success offers an indication of which sectors may change permanently, and how the global economy may look one to two years out. Impacts The post-pandemic economy will be biased towards larger companies with the capital to survive a year or more of lost business. Inequality will rise as, while some sectors and their employees will benefit from demand shifts, many jobs and firms will be lost elsewhere. As people adopt new habits (eg, more entertainment at home) many may change permanently; firms will be challenged to follow these patterns.

Self-Operated Store or Franchised Store? Optimal Decisions for Online-to-Offline Supply Chain with a Demand Shift

Mutual shifts in offline and online demand have become the norm in supply chain operations. The online-to-offline (O2O) supply chain system consists of a platform vendor, a physical store, and a product. The platform vendor sells the product directly online and governs either the centralized decision-making of a self-operated store or the decentralized decision-making of a franchised store offline. In this study, supply chain decision models with and without demand shifts are constructed to obtain optimal wholesale and selling prices and to maximize profit. The coordination mechanism under decentralized decision-making is designed to optimize the O2O supply chain, and the validity and applicability of the model are verified by numerical simulation. Results show that, regardless of whether a store is self-operated or franchised, the total profit of the system increases, and online and offline prices depend on a range of demand shifts. With an increased proportion of online demand shifts, the offline selling price and total profit of the system increase, whereas the online selling price and profit of the platform vendor decrease under decentralized decision-making. When the fixed transfer payment fee is within a certain range, a two-part-tariff contract can effectively coordinate the supply chain. This study not only contributes to the theoretical literature on O2O supply chain systems but also provides practical decision-making support for managers.