Were the US workers in “essential” sectors well paid?

PurposeWhen the coronavirus disease 2019 (COVID-19) pandemic seriously hit the USA, a lot of cities/states announced their lockdowns, in some cases forbidding employees to go to work. But workers in the so called “essential sectors” were exempt from the order, and on the contrary were required to remain on the job in order to maintain the services and functions considered vital to the community. If they have not been paid well in comparison to those in the other sectors, there would be a stronger case for granting them a special hazard pay during the pandemic. This paper aims to design a way to measure the “importance” or being “essential” of the different sectors in the economy, and then investigates whether the actual pay of the workers in these sectors is consistent with the measured importance.Design/methodology/approachAt least two policy issues emerged from such an arrangement: (1) How can one define the “essential sectors” objectively instead of the authorities preparing a list according to their administrative procedure? (2) How well have been the workers in the essential sectors paid before the pandemic strike? The concept of a revised Leontief forward linkage effect will be used in an input–output model to gauge the relative “importance” of the different sectors in the US economy. Then the measured importance will be compared with the average compensation of the employees in these sectors.FindingsIt is found that for some sectors such as agriculture, retail trade, and repair and installation of machinery and equipment the ratio of workers' compensation relative to the national average is substantially lower than the relative importance of the sectors employing them. That is, many of them have been substantially underpaid in spite of their importance.Research limitations/implicationsThe scope of this study is limited to one country, the USA, but the methodology can be applied to other countries as well.Originality/valueThis study is an original research that contributes to an improved understanding of the importance of the workers engaged in different sectors in the USA during COVID-19.

Catching My Anger: How Political Elites Create Angrier Citizens

Anger is a common feature in contemporary American politics. Through the process of affect linkage, we argue that one way the electorate becomes angrier about politics is by observing angry displays from political elites. Affect linkage occurs when a person’s emotional state of mind changes to match the emotions displayed by someone else. Using an online experiment in which subjects are randomly exposed to an angry or unemotional debate between a Democrat and Republican running for Congress, we show that exposure to an angry in-party politician significantly increases the amount of anger, disgust, and outrage expressed by co-rank-and-file partisans. This increase in aversive emotions, moreover, increases the likelihood that citizens report the intention to vote, and this affect linkage effect is most pronounced in those who are most likely to stay home on election day: the weakest partisans. Interestingly, angry rhetoric by political elites does not have any effect on out-partisans, suggesting that anger via emotional contagion does not cross party lines.

The Economic Effects of China’s Distribution Industry: An Input-Output Analysis

This study contributes by analyzing the economic effects of China’s distribution industry based on China’s 2012 and 2017 input-output data. It analyzes changes in the forward and backward linkage effect over a five-year period in accordance with the Chinese government’s distribution industry policy. The coefficients of the effects of the Chinese distribution industry, using Input-Output Tables and a comparative analysis of the sensitivity of dispersion, were determined. In terms of the coefficient of influence, most of the sectors that ranked high in 2012 are related to manufacturing, except for lodging and catering. The sensitivity and influence coefficients indicate that the top-ranked sectors in 2012 were more affected by the raw materials and energy essential for manufacturing development than by the services sector.

A New Method for Interindustry Linkage Analysis Based on Demand-Driven and Multisector Input-Output Model and Its Application in China’s Manufacturing and Producer Services

Interindustry linkage analysis is an important interdisciplinary research field of technical economic and complex systems, and the results can be used as critical bases for making strategies and policies of economic development. This study reviews the previous methods for measuring interindustry linkages and their disadvantages and puts forward a new method for interindustry linkage analysis in a complex economic system on the basis of demand-driven and multisector input-output model. Firstly, it makes a further decomposition of the Leontief inverse matrix in the economic sense and decomposes the gross output of one industrial sector or its sub-industries into three components. Then, it analyzes the structural features of output and measures the interindustry linkages between two industrial sectors with three indices: interindustry linkage effect, interindustry linkage contribution, and interindustry linkage coefficient. Compared with the previous measurements, the method in this study has three obvious advantages: it integrates the sectoral internal effect and external linkage effect at the same time; it can not only measure the interindustry linkage effects between two given industrial sectors but also clearly describe the composition ratio of the direct and indirect interindustry linkage effects; and it adopts, respectively, the absolute flow value, relative flow value, and unit relative value to measure the linkages comprehensively. Finally, this study takes China’s input and output in 2017 as an application case to analyze the structural features of output of its manufacturing and producer services and measure the interindustry linkages between them.

A Comparative Study of the Development of Technology-Intensive Industries: Korean and Romanian Automobile Industries

The automobile industry is a technology-intensive industry that has the potential to create successes in many other related industries. This paper analyzes the approaches taken during the developmental processes of the automobile industries in Romania and Korea. This paper identifies the causes of their rapid growth and compares the experiences of the two nations particularly with respect to the approaches they took during the developmental stages of their automobile industries. Automobile industries in these two countries, Dacia and Hyundai in particular, contributed to economic growth in terms of employment, income generation and development of advanced technologies via the linkage effect. After comparing the merger and acquisition approach in Romania with the technology licensing approach in Korea in light of the government policies which pursued industrialization since the 1960s, it provides policy implications for developing countries which try to develop technology-intensive industries such as the automobile industry.