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This paper aims to identify the level of contribution of different levels of education to remaining in unemployment as well as the transition from unemployment to employment in Egypt.

In this paper, transition probabilities matrix differentiated by gender, age groups, educational levels, marital status and place of residence based on worker flows across employment, unemployment and out of labor force states during the period 2012–2018 using Egypt Labor Market Panel Survey of 2018. The results point to the highly static nature of the Egyptian labor market. Employment and the out of labor force states are the least mobile among labor market states. This is because employment state is very desirable and the out of labor force is the largest labor market states, especially for females. Also, this study examines the impact of different educational levels separately on remaining in unemployment and transition from unemployment to employment state using eight binary logistic regression models.

The main results of transitions from unemployment to employment are relatively large for males, elder-age, uneducated workers as well as workers who are not married and urban residents, and the results of the logistic regression models consistent with the transition probabilities matrix results, except for few cases. Based on the above findings, there is enough evidence to accept the null hypothesis that no education has a positive significant impact to transition unemployed individuals from unemployment to employment, while less than intermediate as well as higher education have a negative significant impact to transition unemployed individuals from unemployment to employment.

This paper proposes to address the problem of the unemployment among highly educated which is much higher compared with illiterates and try to understand the impact of different levels of education separately on the transition from unemployment to employment, to help the policymakers to eradicate the gap between education and the demand of the labor market in Egypt.

This study aims to assess the role of financial inclusion (FI) in moderating the incidence of entrepreneurship on energy poverty in Ghana.

The assessment is made by using pooled data and two-stage least squares. The exposition builds from the 7th (GLSS7) and 6th (GLSS6) rounds focusing on the Ghana Living Standards Survey (GSS, 2014, 2019) that is collected by the Ghana Statistical Service (GSS) from 10 principal regions in the country.

The findings show that entrepreneurship has an unconditional positive incidence on energy poverty while the interactive incidence between entrepreneurship and FI on energy poverty is negative. The corresponding FI policy thresholds that should be exceeded in order for FI to effectively moderate entrepreneurship for negative outcomes in energy poverty are between 0.154 and 0.280 index for the full sample; 0.187 index for the rural subsample; 0.200 and 0.333 index for the male sample. Thresholds are not computed for the rural and female subsamples because at least one estimated coefficient that is needed for the computation of such thresholds is not significant. Policy implications are discussed.

This study has complemented the existing literature by assessing how FI can be used to influence the nexus between entrepreneurship and poverty in Ghana.

This paper explores the effects of fiscal policy in an economy with reciprocity in labor relations and fair wages, consumption taxes and a common income tax rate in place.

To this end, a dynamic general-equilibrium model with government sector is calibrated to Bulgarian data (1999–2018). Two regimes are compared and contrasted – the exogenous (observed) vs optimal policy (Ramsey) case. The focus of the paper is on the relative importance of consumption vs income taxation, as well as on the provision of utility-enhancing public services. Bulgarian economy was chosen as a case study due to its major dependence on consumption taxation as a source of tax revenue.

(1) The optimal steady-state income tax rate is zero; (2) the benevolent Ramsey planner provides the optimal amount of the utility-enhancing public services, which are now three times lower; (3) the optimal steady-state consumption tax needed to finance the optimal level of government spending is 18:7%.

This is the first study on optimal fiscal policy with reciprocity in labor relations.

External institutional policy and its impact on corporate social responsibility (CSR) have been widely discussed by researchers, but its effect still remains controversial. This study aims to use the minimum wage policy as an illustrative example to analyze its impact on the corporate social responsibility (CSR) of tourist enterprises. Furthermore, the research seeks to examine the boundary conditions that influence the minimum wage’s effect on CSR.

This paper takes the data of 42 listed tourism companies from 2010 to 2020 in China as samples and uses the mixed OLS regression method and the fixed effects panel model to examine the effect of the minimum wage on CSR.

Findings show that increasing wages has a significantly negative impact on their total CSR investment. Also, low-operating-capacity enterprises and private enterprises will react more adversely when faced with increasing minimum wages. And found that the increase of minimum wage has no significant negative impact on the strategic social responsibility of tourism enterprises; however, it has a significantly negative impact on their tactical social responsibility. In addition, as far as employees’ rights and interests are concerned, the minimum wage increase has effectively increased employee salaries, but the nonsalary benefits of the employees have significantly decreased.

The contribution of this paper not only expands the research on the antecedents and boundary mechanisms of CSR but also clarifies the specific effect of the rise of the minimum wage on corporate social responsibility; it further deepens the impact of institutional policy factors on CSR, which also opens new perspectives for policy evaluation and provides a theoretical basis for government policymakers.

This study aims to discuss the behavioral economics and Islamic economic joint criticisms against the conceptual and economic political view of the mainstream.

The purpose of this study is to examine the effectiveness of mainstream economic policies in addressing unemployment. Furthermore, it critically assesses the mainstream perspective on unemployment within the contexts of Islamic economics and behavioral economics, separately. The commonalities and disparities between the approaches of Islamic economics and behavioral economics regarding unemployment are evaluated. Subsequently, the conventional viewpoint on unemployment is scrutinized from the combined standpoint of Islamic economics and behavioral economics. This article employs a theoretical approach to address these concerns.

Although there are some differences, the recommendations and values of Islamic Economics and behavioral economics in the context of unemployment are almost the same. And, more importantly, both approaches are similar in their emphasis on the ineffectiveness and distance from human values of mainstream economic policies.

This article is the first to examine unemployment from the joint perspectives of Islamic economics and behavioral economics. It is also the first article to criticize the mainstream view of unemployment from the common framework of these two approaches.

The aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.

We 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.

Once 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.

Although 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.

The aim of this study is to analyze which socioeconomic factors (economic, demographic, and political) most commonly affect the social expenditure of the European Union (EU) and Organization for Economic Co-operation and Development (OECD) countries.

A panel data fixed-effects model is employed for 34 OECD and 23 EU countries between 2000 and 2020.

Results indicate that, in all country groups, economic factors have the most significant influence on social expenditures, with income being the primary determinant, particularly in EU countries. The negative impacts of unemployment and inflation underscore the importance of counter-cyclical measures adopted by countries to maintain stability in their social expenditures. The most influential demographic factor is found as the old-age-dependency ratio. While the rule of law affects social expenditure positively, government effectiveness and female labor force participation affect it negatively. The positive effect of Konjunkturforschungsstelle (KOF) indexes shows the globalization effect, which can be attributable to the compensation hypothesis.

Governments enforce inclusive and sustainable policies to boost economic activities and GDP, thus combating inflation and unemployment and regulating the labor market and socioeconomic problems about aging populations and women’s economic participation to control social expenditures. The rule of law and institutional quality will also boost economic growth.

This study focuses on the effects of social expenditures in a broader view within the framework of the three main factors (economic, demographic, political) and attempts to determine the key factors that account for the differences in social expenditure between the OECD and EU countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0384

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

The advent of artificial intelligence (AI) in the accounting landscape marks a significant shift, promising gains in efficiency and accuracy but also eliciting concerns about job displacement (JD) and broader socio-economic implications. This study aims to provide an in-depth understanding of how AI’s integration in accounting contributes to JD, reshapes decision-making processes and reverberates across economic and social dimensions. It also offers evidence-based policy recommendations to mitigate adverse outcomes.

Leveraging a cross-sectional survey disseminated through Facebook, this research used snowball sampling to target a diverse cohort of accounting professionals. The collected data were subjected to meticulous analysis through descriptive and regression models, facilitated by SmartPLS 4 software.

The analysis revealed a significant correlation between AI’s increasing role in accounting and a heightened rate of JD. This study found that this displacement is not isolated; it has tangible repercussions on decision-making paradigms, economic well-being, professional work dynamics and social structures. These insights corroborate existing frameworks, including, but not limited to, theories of technological unemployment and behavioural adjustments.

Although providing valuable insights, this study acknowledges limitations such as the restricted sample size, the cross-sectional nature of the survey and the inherent biases of self-reported data. Future research could aim to extend these initial findings by adopting a longitudinal approach and potentially integrating external data sources.

As AI technology becomes increasingly ingrained in accounting practices, there is an urgent need for coordinated action among stakeholders. Policy recommendations include focused efforts on talent retention, investment in upskilling programs and the establishment of support mechanisms for those adversely affected by AI adoption.

By synthesising a range of theoretical perspectives, this study offers a comprehensive exploration of AI’s multi-dimensional impacts on the accounting profession. It stands out for its nuanced examination of JD and its economic and social implications, thereby contributing to both academic discourse and policy formulation. This work serves as an urgent call to action, highlighting the need for strategies that both exploit AI’s potential benefits and protect the workforce from its disruptive impact.

This paper empirically investigates the relationship between financial availability and crime by measuring it across five dimensions: banking, securities, insurance, private lending and digital inclusive finance.

The study utilizes 2011–2017 data from prefecture-level cities as a representative sample. Moreover, these findings remain robust after addressing endogeneity through the use of the historical distance between cities and the railroad network as an instrumental variable.

The findings demonstrate a significant negative relationship between financial accessibility and crime rates. Heterogeneity exists in the inhibitory effect of different types of financial accessibility on crime, with banking finance exhibiting a stronger inhibitory effect compared to private lending. Areas affected by natural disasters and infectious diseases exhibit a stronger inhibitory effect of financial accessibility on crime rates, particularly in areas with severe shocks of natural disasters and epidemics. This effect is attributed to the low financing threshold and easy access to private lending, which plays a more effective role than bank finance when people face extreme risks.

There should be stricter regulations imposed on private lending markets and the introduction of more rational legislation aimed at guiding a healthy development within these markets; such measures serve as effective and complementary means for individuals from all walks of life to access credit financing.

The regulation of financial resources by the government should always prioritize ensuring the accessibility of financial policies to cater to the needs of the majority population.

This study is for the first time in an emerging economy context, the causal relationship between financial accessibility and crime. To provide a more comprehensive measure of financial accessibility in a region, this paper proposes a five-dimensional methodology.