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The authors provide a novel interpretation of the relationship between skill demand and labour market concentration based on the training rationale.

The authors use a novel data set on Italian online job vacancies during 2013–2018 to analyse the relationship between labour market concentration and employers' skill demand. The authors construct measures of market concentration and skill intensity in the local labour market. The authors regress the measures of skill demand on market concentration, controlling for sector, occupations and other features of the labour market. The authors also use the Hausman–Nevo instrument for market concentration.

The authors show that employers in a highly concentrated labour market demand competencies associated with the ability of workers to learn faster (e.g. social skills) rather than actual knowledge. They also require less experience but higher education. These results are consistent with the hypothesis that employers in more concentrated labour markets are more prone to train their employees. Instead of looking for workers who already have job-specific skills, they look for workers who can acquire them faster and efficiently. The authors provide a theoretical framework within which to analyse these aspects as well as providing a test for the relevant hypotheses.

In addition to cross-countries differences in labour market regulations, the authors' findings suggest that policy authorities should consider the local labour market structure when studying workforce development programmes aimed at bridging the skill gap of displaced workers. Moreover, the authors show that market concentration can have relevant implications for human resource (HR) managers by affecting their recruitment behaviour through the demand for skills. In fact, concentrated markets tend to favour firms' collusion and anti-competitive behaviour that could strongly affect HR management practices.

The authors' paper innovates on the literature in a number of ways. First, the authors provide evidence of local labour market concentration in Italy. Second, the authors provide evidence of skill demand at the local level using a detailed skill taxonomy that goes beyond the classical distinction between high and low skills. Third, and most importantly, the authors provide evidence of the relationship between skill demand and labour market concentration. By analysing detailed skills and competencies, the authors take one step beyond understanding the features of labour demand in monopsonistic markets.

Purpose: This chapter addresses the skills shortages in Kosovo’s labour market, emphasising the service sector. The labour market economy is very dynamic, and Kosovo, with the youngest population in Europe, also has the highest unemployment level among youths. Therefore, we aim to analyse the mismatches of the skills demand in the labour market.

Methodology: The scientific methods used in this chapter are quantitative methods applying analytical and critical approaches based on economic theory. In this chapter, we analysed secondary data from Labour Force Surveys (LFS) and official reports such as the World Bank and UNDP. We have also conducted primary research with the employees of SMEs in the service sector, with specifically related questionnaires for descriptive issues.

Findings: The logit model used in this research has shown goodness of fit and yielded significant results. Based on the empirical findings, we have found a need for some main soft skills such as communication skills, language skills, ICT skills, and additional training to help gain employability skills. These findings suggest that there is a need for more skills in the service sector, significantly impacting the employees’ job performance and the job seeker’s level of employability.

Significance: Noticeably, countries that are still in the transition process face inequalities in the labour market and have a very high level of unemployment. The findings can be used in analysing demand-side management of the labour market and mismatching of skills in transition economies by policy makers.

Introduction: Organisations all over the world are experiencing skill gaps. One of the key factors contributing to the shortage of competent workers is the inability to find candidates that fit the profile. Most of the time, the market does not offer what organisations require.

Purpose: This research focuses on skill shortages and labour market rigidity in the information technology (IT) sector. It discusses the impact of labour shortage and strategies to overcome these challenges.

Need of the Study: The study is required to reduce the skill shortage in the IT sector and inflexibility in the labour market.

Methodology: The data are collected from secondary sources, that is, books, journals and other internet sources.

Findings: The labour market volatility is impacted by several external factors leading to rigidity and talent shortages. Different forecasts within the IT industry, manufacturing, media and telecommunications indicate large-scale labour shortages. The growing influence of digitalisation further creates challenges for organisations during the hiring process as the identified skill gaps for IT professionals are also identified.

Practical Implications: Labour market rigidity affects the labour market. Shifts in labour supply and demand do not always impact wages. Methods are suggested on how to reduce the rigidity in the labour market and, in turn, decrease the skill gaps.

In this paper, the authors attempt to understand how labour market attachment during the ages of 30–59 influences individuals' transition out of the labour market.

Using high-quality Swedish register data, the authors follow individuals born in 1950 and observe their labour market attachment during mid-life and their exit from the labour market.

The authors find evidence that labour market attachment in different stages of the career is differently related to exit from the labour market. At the age of 30, as well as between the ages 50–59, low attachment is related with earlier exit from the labour market. On the contrary, low labour market attachment during the ages 40–49 is related with later exit from the labour market. However, regardless of age, lower labour market attachment increases the risk of work-related benefit receipt in the exit year. The authors also find evidence that gender, migration status and childhood socioeconomic disadvantages may represent obstacles to longer working lives, while high education is a consistent factor in avoiding early exit from the labour market.

This study provides insights on the link between labour market attachment in different stages of the career and the exit from the labour market as well as work-related benefits dependency in the year of exit.

This paper is a dedication to Professor Ngo Van Long who introduced the idea of Kant–Nash equilibrium. The author extends this analysis to the study of adult and child labor markets.

This is a game theoretic analysis of the market for adult and child workers when some firms behave in the neoclassical Nashian way and some firms follow a Kantian social norm.

The presence of Kantian firms in the output market in addition to Nashian lowers industry output and labor demand. This raises the possibility that Kantian behavior in the output market could lower wages sufficiently and increase the incidence of child labor. If firms engage in Kantian behavior in the labor market by not hiring child workers, adult wage rises but could lower child wage as children if they work can only work for Nashian firms. When labor demand is sufficiently high, more Kantians could raise adult wage above subsistence and eliminate child labor supply.

This is the first paper to apply Kant–Nash equilibrium to the labor market. The result that Kantian behavior could have an unintended negative spillover effect in other markets is new. The paper keeps alive the ideas of Professor Long, which hopefully will stimulate further work and build on his ideas.

The efficient functioning of the labour market is an important factor that affects long-term economic growth. The interaction of supply and demand on the labour market is influenced by institutions which change the motivations and behaviour of economic actors and, ultimately, the flexibility of the labour market. There is no consensus in the literature on the effect these institutions have on labour market outcomes. This chapter focuses on a set of selective labour market institutions (employment protection legislation, minimum wages, unemployment benefits, labour taxation, trade unions and active labour market policies), compares their relevance to other European Union (EU) countries and through the lens of the Beveridge curve it tries to evaluate their impact on effectiveness of the Czech labour market. The international comparison shows that most of the considered institutions/regulations do not reach such importance (except employment protection legislation) and that they have a significant negative effect on labour market outcomes. Even the model of the Beveridge curve does not indicate that the Czech labour market is characterised by rigidities that would impair the effectiveness of a matching process at the aggregate level.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

This study deals with the main issues concerning the interplay between homeownership and labour market outcomes, namely (1) the relation between homeownership and labour market outcomes, at both the individual level and the aggregate level, and (2) the relation between homeownership and human capital.

This paper is both theoretical and empirical. A search and matching model of the labour market is developed to explain the strong relation between mortgage markets and wages. A regional panel analysis in Italy is used to verify the interplay between homeownership and wages.

Homeownership is not, by itself, a condition for receiving higher wages, but rather higher wages increase the probability to become a homeowner, since they positively affect the probability of acquiring a mortgage from the bank. Eventually, wages cause homeownership, but the reverse may not be true.

The paper focuses on the labour market, while the housing market model is restricted to the mortgage market.

The positive effect of homeownership on wages is hard to theoretically formalise and is not empirically proven. Before investigating a (potential) bidirectional relationship between homeownership and labour market outcomes, therefore, the related literature should assume a new theoretical link between homeowners and wages.

The result that “homeownership is not, by itself, a condition for receiving higher wages” has positive implications for human and social development. If homeownership could lead to better labour market outcomes, indeed, socio-economic inequalities would increase in the society, because homeownership would be the starting point of a “lucky” circle that increases the well-being of people who are already wealthy.

First, this study clearly explains why the microeconomic result that homeowners are more likely to be employed than tenants is consistent – at the aggregate level – with a negative relation between homeownership and better labour market outcomes. Second, the related literature has largely ignored the social implications of the topic. A potential bidirectional relation between homeownership and (better) labour market outcomes, indeed, could imply an increase in the well-being of people who are already wealthy.

This study investigated the gender wage gap in Nigeria by analysing two waves of household surveys (in 2003–2004 and 2018–2019) in order to understand the dynamics or polarisation of the labour market in Nigeria in terms of the gender wage gap over time.

The study applied an extension of Oaxaca–Blinder decomposition that relies on the re-centred influence function (RIF) regressions to analyse the gender wage gap at all points along the wage distribution.

The results unambiguously show that there is a significant gender wage gap in Nigeria at all points along the wage distribution, such that for the two surveys used and after nearly two decades, men still earn more than women. That is, the log wage difference between males and females is statistically significant at all points between the 10th and the 90th quantiles. In 2003–2004 period, the authors found that most of the wage difference was significantly accounted for by the wage structure effect, whilst the composition effect was negative and only significant at the bottom of the wage distribution. Since the 2018–2019 period, the authors found that there has been a visible change such that most of the gender wage gap is now accounted for by the composition effect at all points along the wage distribution. Another interesting finding is that there has been a general decline in the gender wage gap along the entire wage distribution, such that inequality was higher in 2003–2004 than in 2018–2019. This decline is bigger at the top than at the bottom of the wage distribution. The authors also found that, contrary to some of the studies on the wage gap, the raw gaps for the two surveys appear to show inverted U-shape, but the gap has fallen quickly since the 2018–2019 period. Thus, the authors found strong evidence of a “sticky floor” compared to a “glass ceiling” effect in both periods, and this becomes more pronounced over time. In terms of the contributions of individual covariates on gender pay gap in Nigeria, the authors found that urban residence, unionisation, education and occupation variables exhibit major influence. However, the effects of covariates on the composition and wage structure components of the wage gap have changed over time.

The major policy implication of these findings is that to address the gender wage gap in Nigeria, policy should focus more on how labour is rewarded and improving human capital for women.

This study is a novel paper in Nigeria that has investigated the gender wage gap in Nigeria by extending the focus of literature in three ways. First, the authors applied an extension of Oaxaca–Blinder decomposition that relies on the RIF regressions to analyse the gender wage gap at all points along the wage distribution. Second, the authors used sample selection bias to account for the non-randomness of participation in wage employment. And third, the authors applied similar analysis to two waves of household surveys (in 2003/2004 and 2018/2019) in order to understand the dynamics or polarisation of the labour market in Nigeria in terms of the gender wage gap over time.

This paper aims to develop a vision for the future identifying how digital nomadism affects the labor markets in the tourism industry.

The qualitative research method was used. The research data were collected using a semistructured interview form developed by the researcher. The sample consists of twenty people working in the tourism industry as tour guides, travel agency owners, accommodation sector employees and professional managers. The content analysis method was used to analyze the data.

It was found that employees in the tourism industry are familiar with digital nomadism, interact with employees working as digital nomads and may prefer the digital nomad way of working, while employees in the accommodation sector cannot work as digital nomads due to the nature of their work. It is shown that digital nomadism can be applied to tour guides and travel agency owners.

The data was collected from employees of the accommodation sector, travel agencies, tour guides and employees of the Turkish tourism labor market. It is recommended that the tourism labor markets adapt to the digitalized world and adjust their working models in this context.

This is one of the first studies on the impact of digital nomadism on the tourism labor markets.