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This paper explores the evidence of a long-run co-movement between aggregate unemployment insurance spending and the labor force participation rate in the USA. The unemployment insurance (UI) program tends to expand during an economic downturn and contract during an expansion. UI may incentivize unemployment and may also facilitate better matching in the labor market. Statistical evidence of the presence of a co-movement will thus shed new light on their dynamics.

This research applies time-series econometric approach using monthly data from 1959:1 to 2020:3 to test threshold cointegration and estimate a threshold vector error-correction (TVEC) model. The estimates from the TVEC model investigating the nature of short-run dynamics.

The Enders and Siklos (2001) test find evidence of threshold cointegration between the two indicating the presence of long-run co-movement. The estimates from the TVEC model investigating the nature of short-run dynamics find evidence that the growth in aggregate UI spending and the growth in labor force participation rate adjust simultaneously to maintain the long-run co-movement above the threshold in the short run. The author also observes the same short-run dynamics for the growth in aggregate UI spending and the growth in the labor force participation rate for females.

This model is bi-variate by construction and does not address causality.

The author argues that the UI program positively impacts the female labor market outcomes, for example, better matching. This finding may explain the upward trend in the labor force participation rate for females in the USA.

The research findings may justify the transfer programs for minority and immigrants.

This is first research that analyzes the UI programs impact on the labor force participation using a macroeconometric approach. To the best of the author's knowledge, this is the first study in this genre.

This paper aims to study the type of short-time work (STW) schemes implemented in Spain to preserve jobs and workers’ incomes during the COVID-19 crisis and the corresponding labour market outcomes.

A dynamic macroeconomic model of job creation and destruction of the search and matching type in a dual labour market.

The model shows that the availability of STW schemes does not necessarily prevent a large increase in unemployment and job destruction. The quantitative effects depend on the degree of subsidization of payroll taxes and on the design of the policy. A scenario with a moderate degree of subsidization and where the subsidy is independent of the reduction in hours worked is the least harmful for both welfare and fiscal deficit. The cost of such a strategy is a higher unemployment rate. Concerning heterogeneous effects, the unemployed are the ones who experience the strongest distributional changes.

The effectiveness of STW schemes in dual labour markets using a search and matching model in the context of the COVID-19 crisis has not been analysed elsewhere. The literature has emphasized the importance of dynamics, labour market institutions and workers’ heterogeneity to understand workforce adjustment decisions in the face of temporary shocks to de- mand especially when firms’ human capital is relevant. These elements are present in the model. In addition, this paper computes welfare and distributional effects and the cost of these policies.

The purpose of this article is to develop a conceptual framework that sets out the linkages that exist between digitalisation and active labour market policies (ALMPs).

Based on a narrative literature review, this article seeks to connect two research streams, namely that relating to ALMPs and that relating to digitalisation in the public sector. This exercise requires an understanding of both how the context of digitalisation in the public sector has evolved in relation to technological change and the identification of specific ALMPs that are more sensitive to digitalisation.

Starting from the identification of ideal-types of ALMPs, “employment assistance” can be considered the type of policies most sensitive to digitalisation, looking at main forms of interventions as career guidance, profiling and job-matching tools. The first tool is closer to a technological domain of “remotisation”, while the second is closer to that of “automatisation”.

Achieving an understanding of the different degrees of sensitivity to digitalisation for various types of ALMPs is relevant for policy-making purposes to identify potential priority areas of strategic investment to enhance this sector.

The authors present an understanding of the current state of the digitalisation of public employment services. The literature review itself allowed the authors to conclude that, despite the interests in the public and academic debate, the existing research relating to the digitalisation of public employment services remains scant. At the same time, the article points towards fertile areas for further analysis.

This article aims to help ensure high-quality subject access to Swedish lesbian, gay, bisexual, transgender, queer and intersexual (LGBTQI) fiction, and aims to identify challenges that librarians consider important to address, on behalf of themselves and end users.

A web-based questionnaire comprising 35 closed and open questions, 22 of which were required, was sent via online channels in January 2022. By the survey closing date, 20 March 2022, 82 responses had been received. The study was intended to complement an earlier study targeting end users.

Both this study of librarians and the previous study of end users have painted a dismal image of online search services when it comes to searching for LGBTQI fiction. The need to consult different channels (e.g. social media, library catalogues and friends), the inability to search more specifically than for the broad LGBTQI category and suboptimal search interfaces were among the commonly reported issues. The results of these studies are used to inform the development of a dedicated Swedish LGBTQI fiction database with an online search interface.

The subject searching of fiction via online services is usually limited to genre with facets for time and place, while users are often seeking characteristics such as pacing, characterization, storyline, frame/setting, tone and language/style. LGBTQI fiction is even more challenging to search because indexing practices are not really being standardized or disseminated worldwide. This study helps address this important gap, in both research and practical applications.

The sustainable transition towards the circular economy requires the effective use of artificial intelligence (AI) and information technology (IT) techniques. As the sustainability targets for 2030–2050 increasingly become a tougher challenge, society, company managers and policymakers require more support from AI and IT in general. How can the AI-based and IT-based smart decision-support tools help implementation of circular economy principles from micro to macro scales?

This chapter provides a conceptual framework about the current status and future development of smart decision-support tools for facilitating the circular transition of smart industry, focussing on the implementation of the industrial symbiosis (IS) practice. IS, which is aimed at replacing production inputs of one company with wastes generated by a different company, is considered as a promising strategy towards closing the material, energy and waste loops. Based on the principles of a circular economy, the utility of such practices to close resource loops is analyzed from a functional and operational perspective. For each life cycle phase of IS businesses – e.g., opportunity identification for symbiotic business, assessment of the symbiotic business and sustainable operations of the business – the role played by decision-support tools is described and embedding smartness in these tools is discussed.

Based on the review of available tools and theoretical contributions in the field of IS, the characteristics, functionalities and utilities of smart decision-support tools are discussed within a circular economy transition framework. Tools based on recommender algorithms, machine learning techniques, multi-agent systems and life cycle analysis are critically assessed. Potential improvements are suggested for the resilience and sustainability of a smart circular transition.

By observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.

In the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.

It is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.

The Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.