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This study aims to investigate the impact of job loss on the mental health of individuals in Tunisia during the COVID-19 crisis.

In this research, the authors use the counterfactual decomposition technique and the potential outcome approach. In the first part, the authors calculated mental health indicators for all individuals included in the sample based on the World Health Organization-5 items. The individuals were then grouped into two subpopulations: the first group included those who had lost their jobs and the second group included individuals whose status in the labor market had remained unchanged. In the second part, the authors used the Blinder and Oaxaca decomposition to explain the mean difference in the mental health scores between the two groups and determine the factors contributing to this difference.

The empirical results identified symptoms of depressed mood, decreased energy and loss of interest in several individuals. Based on these three symptoms, the authors were able to classify individuals into three types of depression: mild, moderate and severe. In addition, it appeared that job loss had significantly contributed to the worsening mental health of the individuals.

Although the psychological impact of the COVID-19 outbreak among health-care professionals has been the subject of other studies in health literature on Tunisia, to the best of the authors’ knowledge, no research has addressed the impact of job loss on the mental health of Tunisian workers. Thus, this study fills this gap in the literature.

The study aims to examine the patterns of time allocated to paid employment activities by women in India as well as change in time allocating pattern of women over the period 1998 to 2019. In doing so, it attempts to highlight gender-asymmetry of time use and heterogeneity in time use of women residing in urban and rural areas as well as variations in time use by marital status, motherhood and age.

Using unit-level data from two available Time Use Surveys (TUS) namely the Pilot Survey TUS 1998 and first nationally representative TUS 2019, the authors use Tobit model to estimate determinants of women’s time in employment. To explain the change in time spent on paid work by women over the two decades, the authors use counterfactual quantile regression decomposition.

The gender asymmetry in time allocation is stark, with women spending one fifth time compared to men paid employment activities. Over the two decades of interest, women’s time spent on employment activities in a day has reduced by half from around 4 h to 2 h, largely driven by rural women’s time. Regression results suggest the emergence of a “U-shaped” relationship between time spent on paid work and education of women. The counterfactual decomposition results suggest that women are spending lesser time on employment activities in 2019 than in 1998 across the time distribution.

This paper contributes to a novel understanding of time use by women in a developing country by analysing the changes in time use over two decades as well as distributional sensitivity to observed characteristics. The study informs about the intensive margins of female employment by incorporating dynamics of socio-economic development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2022-0164.

This paper explores the wages of White, Black, Hispanic, Asian, Native American and “other race” women and men once differences in basic characteristics among these 12 groups are accounted for. The authors aim to extend comparisons beyond those of women and men of the same race or the various races within a given gender.

To undertake the conditional analysis, first, the authors propose a simple re-weighing scheme that allows to build a counterfactual economy in which workers' attributes for all gender–race/ethnicity groups are the same. Second, the authors use a well-known re-weighting scheme that involves logit estimations.

Only Hispanic men, Native American men and Asian women have conditional wages around average. Black men and, especially, White, Black, Hispanic, Native American and “other race” women have conditional wages clearly below average, whereas those of Asian and White men are well above average. The wage differential between a privileged and a deprived group is disentangled into the premium of the former and the penalty of the latter, which brings a new perspective to what has been done in the literature based on pairwise comparisons. In this intersectional framework, the authors document that gender penalizes more than race.

This paper examines intergroup earnings differentials using a methodology that allows to examine 12 gender–race/ethnicity groups jointly, which is this work's distinctive feature. The authors' intersectional framework allows to picture the effect of gender and race/ethnicity more broadly than what the literature has shown thus far.

In this article, the authors study the gender pay-gap (GPG) among graduates in Italy (2011 cohort) who were employed four years after graduation. The authors focus on individuals who are new entering in the labour market or who match a low level of experience with a high level of education.

Aimed at estimating the amount of the differential between male and female average wages, the authors have applied the Oaxaca–Blinder (O–B) decomposition. The results identify the presence of a GPG at the very beginning of graduates’ careers given that, shortly after graduation, women receive lower salaries than men, even after controlling for several characteristics (individual, academic, job and local labour market). The authors completed the analysis with the reweighted O–B decomposition using the recentered influence function (RIF) and the Juhn, Murphy and Pierce and Machado and Mata decomposition approaches.

The results show that the GPG is already present at the very beginning of graduates’ careers, and it increases when correcting for women’s lower level of participation in the labour market. The authors also identified sticky floor and the glass ceiling effects due to the existence of a relevant high GPG both at the bottom and the top of the graduates’ wage distribution.

By focussing attention particularly on graduates, this paper adds to the existing literature a deeper understanding not only of individuals who have recently entered the labour market, but also those who are highly skilled but have little on-the-job experience. In fact, the authors are looking at a particular sample (graduates who are all transitioning from university to work during the same period) with small heterogeneity which allows the authors to compare very similar young men and women graduates and gain a deeper understanding of GPGs in early careers while controlling for confounding and hidden sources of variability.

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 study aims to identify and explain a possible gender pay gap in the creative industry. By using the salary information of Hollywood actors, this paper restricts the analysis to a relatively homogenous group of workers. In addition, actors' human capital endowments and past performance can be measured precisely. The factors that impact the salaries of movie stars are likely to influence the pay of other high-wage employees, such as athletes and executives.

This paper uses a rich panel data set including 178 female and male actors in 973 movies released between 1980 and 2019. Using a random-effects model and the Blinder–Oaxaca decomposition approach, this paper distinguishes between a fraction of the gender pay gap that can be explained and another fraction that cannot be explained. Hence, only the unexplained residual typically obtained by estimating two standard Mincer-type earnings functions is due to discriminatory pay practices.

This study reveals a pay difference between female and male actors. Gender-specific representation in leading roles and systematic differences in performance measures can explain this pay difference. While female actors' underrepresentation in leading roles reflects consumer tastes and, therefore, reflects discriminatory attitudes, no evidence can be found for direct pay discrimination in Hollywood's movie business.

To the best of the authors’ knowledge, this is the first Hollywood study to relying on a rich panel data set that includes various measures of the human capital characteristics of the different individual actors. This paper's theoretical contribution lies in applying classic labor economics reasoning to explain pay determination in Hollywood's movie business.

The article aimed to identify and analyze the income differences across the income distribution between homosexuals and heterosexuals by occupational groups in Brazil.

PNAD-C microdata was used in two periods (2013–2015 and 2016 to 2019), highlighting the different economic, social and political contexts in Brazil. Recentered influence function and quantile income decomposition were estimated to verify the difference and income discrimination according to the guideline the worker’s sexuality.

For some cases homosexual workers earn more and in others, homosexuals earn less than heterosexuals. The differences in remuneration according to sexual orientation were smaller in positions that demand low qualification and competence. The quantile income decomposition between 2013 and 2015 revealed the positive effect of discrimination was the generator of income disparities between homosexuals and heterosexuals, with greater impact for the 10th and 90th quantiles and on groups that require small levels of complexity and education. Between 2016 and 2019, there was the presence of both effects, but the explained effect was the promoter of wage disparities in most occupational groups.

Given the dataset, it was only possible to work with proxies of homosexual couples.

There has been little research linking the themes of discrimination based on sexual orientation and occupational groups, and so far, it does not exist similar in Latin America. This study found that sexual orientation influences remuneration according to the occupational group that the worker belongs to, affecting income and, consequently, occupational choice. This connection of issues will contribute to new insights into discrimination based on sexual orientation, as well as more effective public policies aimed at reducing discrimination against homosexuals.

The authors investigate the effect of weather and mobility on the spread of the Covid-19 pandemic.

The authors first estimate the effective reproduction number (Rt) as a proxy of the spread of the Covid-19 pandemic and then study the relationship between the latter and weather and mobility in a panel data framework. The authors use US daily infections data between February and September of 2020 at the county level.

The authors find that lower temperatures are associated with a higher Rt, and this effect is greater at temperatures below 0°C. In addition, mobility reductions related to certain types of locations (retail and recreation, transit stations and workplaces) are effective at reducing Rt, but it is an increase in the time spent in parks that most helps reduce the spread of the pandemic.

The estimates imply that a 20°C fall in temperature from summer to winter would increase Rt by +0.35, which can be the difference between a well-controlled evolution and explosive behavior of the spread of the virus. Applying these coefficients estimated with US county data to aggregate series from other countries helps explain the resurgence of the pandemic in the Northern Hemisphere during the winter of 2020. The results show that mobility reduction and social distance are best policies to cope with the Covid-19 outbreak. This strong policy lesson will help facing similar outbreaks in the future.

This study aims to analyze and compare the relationship between international trade in global value chains (GVC) and greenhouse gas (GHG) emissions for Brazil and China from 2000 to 2016.

The input-output method apply to multiregional tables from Eora-26 to decompose the GHG emissions of the Brazilian and Chinese productive structure.

The data reveals that Chinese production and consumption emissions are associated with power generation and energy-intensive industries, a significant concern among national and international policymakers. For Brazil, the largest territorial emissions captured by the metrics come from services and traditional industry, which reveals room for improving energy efficiency. The analysis sought to emphasize how the productive structure and dynamics of international trade have repercussions on the environmental dimension, to promote arguments that guide the execution of a more sustainable, productive and commercial development strategy and offer inputs to advance discussions on the attribution of climate responsibility.

The metrics did not capture emissions related to land use and deforestation, which are representative of Brazilian emissions.

Comparative analysis of emissions embodied in traditional sectoral trade flows and GVC, on backward and forward sides, for developing countries with the main economic regions of the world.

This study attempts to identify and explicate the unique segmentation of the increasingly growing virtual reality (VR) user market based on the user experience. Consequently, it collects five hundred forty-five online survey questionnaires through the Prolific platform and deploys cluster analysis to identify mutually exclusive groups of VR users. The research variable, user experience, contains 16 indicators explained by four dimensions. As a result, this study is able to unveil three mutually exclusive markets which are labeled as (1) beginner, (2) aficionado, and (3) utilitarian. The unique features of these three groups are further compared based on their VR tour behaviors. In the conclusion section, it offers managerial implications for devising novel marketing strategies.