Risk Of Unemployment Research Articles

Intergenerational transmission of unemployment after apprenticeship graduation: does parental socioeconomic background still matter?

A smooth transition from apprenticeship to standard employment is a key step in the professional biographies of apprenticeship graduates. In this study, the transition of apprenticeship graduates from households that receive unemployment benefits are considered. These graduates are thought to be disadvantaged because their parents’ socioeconomic background is assumed to influence their employment outcomes through processes of intergenerational transmission and cumulative disadvantage. Based on administrative data from the Sample of Integrated Welfare Benefit Biographies (SIG) provided by the Institute for Employment Research (IAB), this analysis offers deeper insights into parental socioeconomic background and the individual factors that affect the risk of unemployment following the completion of an apprenticeship. In the case of an unsuccessful direct transition to standard employment, the factors influencing the duration of the first unemployment are also assessed. The results show that, as with individual characteristics, parents’ education level has a significant effect on the graduates’ risk of unemployment. The duration of the household’s benefit receipt, on the other hand, significantly influences the duration of the first unemployment in the case of an unsuccessful transition following an apprenticeship.

Mental health conditions in patients with systemic lupus erythematosus: A systematic review and meta-analysis.

The reported prevalence of mental health conditions (MHCs) in people with systemic lupus erythematosus (SLE) ranges widely. Whether MHCs are associated with increased risk of SLE or the outcomes of the disease is unclear. This paper aimed to conduct an umbrella and updated meta-analysis of MHCs in people with SLE and to identify whether MHCs are associated with the risk of SLE or patient outcomes. We comprehensively searched PubMed, Web of Science, and Embase databases to identify relevant studies published before June 2023. Random-effect models were used to calculate the pooled prevalence and risk ratios for each MHC. 203 studies with 1485094 individuals were included. The most MHCs observed in patients with SLE were sleep disturbance (59.7% [95% CI, 52.4%-66.8%]) among adults and cognitive dysfunction (63.4% [95% CI, 46.9%-77.9%]) among children. We found that depressive disorders (RR = 2.30, 95% CI = 1.94-2.75) and posttraumatic stress disorder (RR = 1.93, 95% CI = 1.61-2.31) in the general population were significantly associated with an increased likelihood of developing SLE. Furthermore, concurrent MHCs were linked to unfavorable outcomes in patients with SLE, such as decreased quality of life, increased risk of unemployment, and other somatic comorbidities. Our study demonstrated a high prevalence of MHCs among patients with SLE. Individuals with pre-existing mental disorders exhibited an elevated susceptibility to developing SLE, and patients presenting with MHCs were at increased risk of experiencing suboptimal health and functional outcomes. Therefore, evaluating and preventing MHCs should be considered as an integral component of the comprehensive treatment strategy for SLE.

Risks of Unemployment in the Future for Workers as India's Labour Sectors Embrace Automation, Robots, and Artificial Intelligence

This article examines the immediate concerns of unemployment that workers in India face due to implementation of automation, robotics, and artificial intelligence (AI) become more prevalent in the labour sectors. The swift progress of technology poses a danger to conventional manual labour positions, resulting in a large scale loss of jobs and unstable economic conditions. The impacts of automation are most likely to affect marginalized communities, aggravating already existing disparities. To lessen(minimalize/reduce) the negative impacts of mass unemployment, industry stakeholders, governments, and civil society must adopt proactive steps. These are necessary because of the social and political implications of this issue. India's workforce may move towards a more sustainable and fair future by supporting inclusive economic development, encouraging entrepreneurship, and investing in vocational training.

Navigating bias? An assessment of access to, use of, and returns to social capital in the school-to-work transition of descendants of immigrants

Research in several advanced economies has found that the descendants of immigrants tend to experience persistent difficulties in entering the labour market. This article tests whether social capital contributes to the disadvantage of descendants of immigrants in the school-to-work transition when compared to their native-background peers in Sweden. The study uses the CILS4EU survey, which provides information on friendship ties measured at age 15 and labour market outcomes at age 19. This allows for an analysis of networks formed before labour market entrance, an extensive control setup, and a comparison of measures of outgoing, incoming, and reciprocated friendship ties. The results show that the descendants of immigrants have access to less social capital measured as employed friends, but that they are as likely as natives to use their contacts to obtain a job. The returns to social capital are similar in terms of unemployment risk, but descendants of immigrants have a lower payoff when it comes to earnings. The study concludes that social capital contributes to, but is not the main driver of their labour market disadvantage in the school-to-work transition.

Research on public policy plan of unemployment risk caused by artificial intelligence

At present, artificial intelligence has been widely used in many fields of economy and society. The development of artificial intelligence has rich implications for the times and is closely related to unemployment. Technical unemployment, structural unemployment, asymmetric unemployment, and sudden unemployment are the realistic forms of unemployment caused by the development of artificial intelligence. With the rapid development of artificial intelligence (AI) technology, unemployment risk has become a problem that cannot be ignored. In order to meet this challenge, the supply path of public policy is particularly important. This paper will discuss how to effectively alleviate the unemployment risk caused by artificial intelligence through the supply of public policies from five aspects: policy support, education and training, employment service, social security, and regulatory supervision.

Determinants of adolescents' depression, anxiety, and somatic symptoms in Northwest Ethiopia: A non-recursive structural equation modeling.

In low and middle-income countries, adolescent mental health is not only a major public health challenge but also a development concern. Depression and anxiety are the most common mental health disorders and somatic symptoms often co-exist with them. Adolescents with common mental health problems are associated with an increased risk of suicide, future unemployment, and poor quality of life. However, little is known about the mental health of adolescents in Ethiopia. Thus, this study aimed to assess the determinants of depression, anxiety, and somatic symptoms among adolescents in Northwest Ethiopia, in 2022. An institution-based cross-sectional study was conducted from June 8 to 24, 2022. Two-stage stratified random sampling was used to select 1407 adolescents in Northwest Ethiopia. Structured and standardized self-administered questionnaires were used to collect the data. Non-recursive structural equation modeling was employed to assess the direct, indirect, and total effects of predictors. Adjusted regression coefficients and corresponding 95% confidence intervals were used to interpret the strength of the association. The prevalence of depression, anxiety, and somatic symptoms were 28.21% (95% CI: 25.8, 31%), 25.05% (95%CI: 22.8, 27.5), and 25.24(95% CI: 23, 27.6%) respectively. Alcohol use had a significant positive effect on depression [β = 0.14, 95% CI: 0.073, 0.201], anxiety [β = 0.11, 95% CI: 0.041, 0.188], and somatic symptoms [β = 0.12, 95% CI: 0.062, 0.211]. Stress had a significant positive effect on depression [β = 0.76, 95% CI: 0.642, 0.900], anxiety [β = 1.10, 95% CI: 0.955, 1.264], and somatic symptoms [β = 086, 95% C: 0.700, 1.025]. Depression had a direct positive effect on anxiety [β = 0.74, 95% CI: 0.508, 1.010]. In this study, the prevalence of depression, anxiety, and somatic symptoms was moderate. Alcohol use and stress were significantly related to depression, anxiety, and somatic symptoms. The bidirectional relationship between anxiety and depression was significant. Therefore, public health interventions should focus on the bidirectional relationship between depression and anxiety, as well as on identified factors to reduce the burden of mental illness in adolescents.

Does Self‐employment Pay? The Role of Unemployment and Earnings Risk

AbstractThis paper documents the role of unemployment and earnings risk in reconciling evidence in payoff differentials between self‐employment and paid‐employment. Using Spanish administrative data, we characterize the distribution and dynamics of earnings and document lower and less dispersed earnings in self‐employment. We consider alternative hypotheses and highlight the role of lower unemployment risk in self‐employment. We decompose earnings risk dynamics by estimating a life‐cycle earnings process. Indeed, the self‐employed experience lower returns but also face lower volatility and persistence of shocks throughout their life‐cycle. Our results challenge the conventional view that self‐employment necessarily entails higher risk and highlight that accounting for differences in labour earnings risk is important to reconcile the payoff differentials between self‐employment and paid‐employment.

Strategic Press Release When Employee Unemployment Risk Is Better Insured

Using the staggered changes in unemployment insurance (UI) benefits across states in the United States as an exogenous shock to employees’ costs of unemployment and the hiring firm’s costs of disclosure, this study investigates whether and how a firm’s relationship with its employees impacts its strategic disclosure through press releases. We find that firms increase (reduce) bad (good) press releases after their employees’ UI benefits become more generous. This finding is consistent with the notion that larger UI benefits reduce the costs of employee unemployment risk borne by hiring firms and thus reduce firms’ costs to release bad news items. Interestingly, we find that the large increase in UI benefits is associated with more discretionary, but not nondiscretionary, bad press releases. The findings are robust when we exclude earnings-related press releases from our sample. Further evidence shows that the increase in negative press releases is mainly driven by news regarding earnings, products-services, marketing, credit ratings, assets, and legal issues, which are more closely related to employee perceptions of unemployment risk. JEL classification: G10; M41; J31; J65.

Does country of resettlement influence the risk of labor market marginalization among refugees? A cohort study in Sweden and Norway.

This study aimed to compare the risk of labor market marginalization among refugees across different host countries of resettlement and examine the moderating role of birth country and length of stay on these associations. Cohorts of refugees and native-born individuals aged 19-60 in Sweden (N=3 605 949, 3.5% refugees) and Norway (N=1 784 861, 1.7% refugees) were followed during 2010-2016. Rates (per 1000 person-years) of long-term unemployment, long-term sickness absence, and disability pension were estimated for refugees and the host populations. Cox regression models estimated crude and adjusted (for sex, age, educational level, and civil status) hazard ratio (HRadj) for refugees compared to their respective host population, with 95% confidence intervals (CI). Analyses were also stratified by birth country and length of stay. Refugees in Norway and Sweden had a higher incidence of labor market marginalization compared to their host population. Refugees in Sweden had a comparatively lower relative risk of long-term unemployment but higher risk of disability pension (HRadj 3.44, 95% CI, 3.38-3.50 and HRadj 2.45, 2.35-2.56, respectively) than refugees in Norway (HRadj 3.70, 3.58-3.82 and HRadj 1.57, 1.49-1.66, respectively). These relative risks varied when stratifying by birth country. A shorter length of stay was associated with a higher risk of long-term unemployment and a lower risk of disability pension, with a stronger gradient in Sweden than in Norway. The relative risk of labor market marginalization varied by the refugees' birth country but followed similar trends in Sweden and Norway. Although speculative, these findings may hint at non-structural factors related to the refugee experience playing a more important role than host country structural factors for the risk of labor market marginalization among refugees. Future research, including host countries with more variability in structural factors, is required to further investigate these associations. The higher risk of long-term unemployment among refugees with shorter length of stay indicates a need for more efficient labor market integration policies for newly-arrived refugees.

How will I break AI? Post-Luddism in the AI age: Fuzzy MCDM synergy

This study proposes a fuzzy multi-criteria model to assess the risk of unemployment among professionals in the communication sector in Turkey, prompted by the rapid development and evolution of artificial intelligence (AI) technologies. The method integrates Fuzzy The Decision Making Trial and Evaluation Laboratory (F-DEMATEL) and Fuzzy Logarithm Methodology of Additive Weights (F-LMAW) procedures. Data were collected from 20 experts representing professions such as public relations, advertising, journalism, and design through a 12-question survey. In the analysis, the F-DEMATEL procedure was initially employed to determine attitudes towards AI technologies, followed by the application of the F-LMAW procedure to assess the magnitude of AI's impact on occupational groups. Findings reveal a nuanced stance: while professionals acknowledge the necessity of AI for their work, they are unwilling to accept unemployment due to more advanced AI. This newly identified structure, termed Post-Luddism, highlights concerns over technological unemployment, particularly pronounced in professions like journalism where job prospects are limited and creative thinking is paramount. In other communication fields, the intensive use of technology mitigates fears of AI harm. However, even in journalism, there exists a propensity to perceive AI as detrimental. These insights shed light on communication professionals' apprehensions and attitudes towards AI's effects. Policymakers and stakeholders can leverage this understanding to formulate strategic measures, considering the divergent perspectives among professional groups regarding AI, towards mitigating potential unemployment risks and fostering AI-adaptive strategies.

Age Differences in Unemployment Risk and Reemployment Outcomes in Late Working Life in Sweden

ABSTRACT Participation of older workers in the labor market depends, among other things, on older workers employment chances. This study examines age differences regarding risk of unemployment and reemployment outcomes in late working life in Sweden. Using Swedish registry data, we analyzed the probability of unemployment as well as work-related activity following unemployment (wage- or self-employment; exit; downward mobility) of all people born between 1954 and 1968 (aged 49–63) and registered in Sweden between the years 2012 and 2018. Results show that although risk of unemployment does not differ significantly across age groups, younger age groups are more likely to be reemployed as wage-employed while older age groups are more likely to be reemployed as self-employed or exit working life. After an unemployment period, older employees are more likely to have a lower wage than during their previous employment or become part-time unemployed. We conclude that different age groups have unequal chances in late working life in terms of reemployment, risk of exit, and risk of downward mobility following unemployment. Policies for extending working life and promoting inequality should include measures for increasing employability of older workers such as anti-discriminatory laws and dealing with skills mismatch.

Attitudes towards immigration and unemployment risk cleavages: Untangling the economically rooted group conflict framework

Abstract How do increasing economic risk cleavages amongst natives shape growing negativity towards immigration? Group conflict theory suggests that tension between immigrant and native groups arises as a reaction to the actual or perceived loss of economic privilege by the majority group members. Yet, such an economically rooted formation of sentiments towards immigration is widely debated. This article aims to clarify and more precisely assess the economic threat mechanisms of inter-group conflict, remedying limitations in earlier work. Distinct from the economic threat effects due to immigration, here, I argue and show that being in a relatively worse-off position amongst natives is a separate channel increasing adverse reactions to immigration. To examine this relationship, I use high-quality longitudinal household panel data Socio-Economic Panel from Germany from 1999 to 2016. Results from the German case provide evidence suggesting that even when controlling for exposure to a higher risk of being substituted by immigrants and a higher risk of being fiscally burdened by foreigners, there is a robust effect of exposure to increasingly higher unemployment risks compared to other native workers in the host society raises adversity towards immigration. This effect is independent of geographic differences and actual exposure to the economic impact of immigrants. Overall, this article reconciles existing accounts of economically motivated group conflict. It brings forward a comprehensive theoretical framework and empirical evidence to the study of worsening reactions towards immigration in these past decades.

Measuring Unemployment Risk

In this note, we introduce a measure of unemployment risk, the likelihood of a worker becoming unemployed within the next twelve months. By using nonparametric machine learning applied to data on millions of workers in the US, we can estimate how unemployment risk varies across individuals and over time.

Worker and workplace determinants of employment exit: a register study

BackgroundWorkers with chronic illness are in higher risk of unemployment. This article investigated the worker and workplace characteristics associated with labour market inclusion for workers with a diagnosed chronic illness.MethodsLinked...

Unemployment, household arrangements, and socioeconomic inequalities in Brazil

This article examines the role of households in the distribution of unemployment risks in Brazil. We analyze several indicators that summarize the entry into the labor market across different household arrangements and descriptive statistics calculated for each position within these arrangements. We then use a logistic regression model to calculate the likelihood of open or potential unemployment. For women, living with children correlates with a greater likelihood of open or potential unemployment, while the opposite is true for men due to the unequal distribution of family responsibilities. The likelihood of open or potential unemployment is higher for people living with elderly people. Finally, the level of household income has a greater effect on women than onmen, possibly due to the female transition from inactivity to employment in households with fewer resources.

Social contacts, neighborhoods and individual unemployment risk

PurposeThe aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.Design/methodology/approachWe use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.FindingsOnce controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.Originality/valueAlthough many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

Dynamics of labor and capital in AI vs. non-AI industries: A two-industry model analysis.

There is an imbalance in the development of artificial intelligence between industries. Compared to non-AI enterprise, AI- enterprise will save labor, enhance innovation capabilities, and improve production efficiency. By constructing a two-industry model of AI and non-AI enterprise, this paper finds that with the development of artificial intelligence in the same industry, the AI enterprise will occupy a dominant position, attracting labor and capital from the non-AI enterprise into the AI enterprise. In different industries, the development of artificial intelligence improves the production efficiency of the enterprise. However, due to the price effect, non-AI enterprise benefits more. Labor and capital flow from AI enterprise to non-AI enterprise. In order to promote the improvement of production efficiency in the whole society, the government can tax non-AI enterprise and subsidize them to AI enterprise. Taxation promotes the degree of automation and the improvement of production efficiency, but it has only a short-term effect on the development of AI. At the same time, taxation inhibits the development of non-AI enterprise, and there is a high risk of unemployment. When both industries use artificial intelligence for production, the labor share and the capital share of the two industries will tend to the same value. The convergence of technology measures is conducive to increasing labor income share and reducing income inequality, but it is not conducive to innovation.

Analysis and Forecast of China's Unemployment Rate

The unemployment rate is an important economic indicator that measures the proportion of the unemployed labor force. The natural unemployment rate is the normal unemployment rate based on economic fluctuations. Analyze the unemployment rate to determine its root causes. By forecasting the unemployment rate, people can obtain an estimate of the future conditions of the labor market. Not only can the government make policy adjustments based on this, people can use this prediction to make wise career choices and planning, or to learn the necessary skills. The risk of unemployment is closely related to everyone, especially now during the economic downturn due to the impact of global catastrophic events such as COVID-19. Understanding the unemployment rate is an important part of analyzing the characteristics of the current labor market. If we can make more connections about the labor market and even make rough predictions about future trends, college students will be able to make future career choices that are more suitable for them. This study predicts the unemployment rate in the next nine years based on China's unemployment rate from 2012 to 2022, which will fluctuate within a fixed range. The government can increase spending (such as on education) and use monetary and finance polices to ensure that unemployment does not exceed forecasts.

Financial Technology and Poverty Alleviation in Indonesia During the COVID-19 : Impact Evaluation Analysis

The COVID-19 pandemic has brought significant changes, especially to each country's economic and financial sectors. Economic growth in Indonesia experienced a contraction entering mid-2021. This also impacted limiting economic activity, decreasing household consumption, unemployment risk, and increased poverty. In addition, there are changes in people's behavior, such as digital financing systems, non-cash payment systems, and online buying and selling transaction systems. Efforts to improve the economy are encouraged by stimulating people's economic productivity through adaptation to digital technology developments, especially using digital finance. However, the development of digital finance needs to be supported by public financial literacy and inclusion so that it can positively alleviate poverty. This study aims to analyze the impact of financial technology lending on poverty in Indonesia during the COVID-19 pandemic using instrumental variable analysis (IV) for 2019-202. The results of the study show that fintech lending has a negative effect on the poverty rate. However, it is not significant when other variables are added. E-commerce and the use of credit cards have a negative and significant impact on the poverty rate in Indonesia. In maximizing the role of Fintech in Indonesia, support and cooperation from the government, financial institutions, and various relevant stakeholders are needed.

Analysis of the Status of Digital Economy in China's Economy

Digital economy is the hot point of the worlds financial and economic system. The combination of usage of financial technologies and innovation of that have a lightly prospect of the financial development. To know about the impact of digital economy on Chinese regional economic promotion, this essay will question two queries: What is the status of digital finance in the past and current China economy? What aspects of risks need to be avoided in developing process of digital economy? It will combine some cases and data in China firstly and then analysis them as well as giving conclusion and suggestion in the end. Finally, this paper gets a conclusion that digital economy will be the important part of not only Chinese economy but also the world economy. In order to build up an excellent environment for that, there are some factors that have to been paid attention to, including personal information leakage, financial fraud, technical unemployment risk, national essential data leakage and market monopoly.