Search results

This study assesses the probability of an OECD member country exhibiting high persistence in unemployment duration, considering income inequality, productivity, accumulation of human capital and labor income share in Gross Domestic Product (GDP) between the years 2013–2019.

To achieve the purpose of the study, a probabilistic analysis with panel data is employed, focusing on 20 OECD countries segmented into two groups: those with high persistence and low persistence in unemployment duration. Probit and Logit models are estimated, marginal changes are analyzed and the models are evaluated in terms of their classification accuracy. Finally, trends in probabilities over time are examined.

This paper exhibits that countries with higher human capital index, greater labor income share in GDP, and more relevant productivity for well-being reduce their probabilities of experiencing high persistence in unemployment duration. It is observed that Mexico (MEX), Greece (GRC), Italy (ITA), and Turkey (TUR) have elevated probabilities of experiencing high persistence in unemployment duration in the future, while Costa Rica (CRI), Estonia (EST), Slovakia (SVK), Czech Republic (CZE), Lithuania (LTU), Poland (POL), and Israel (ISR) show a marked downward trend in these probabilities. Lastly, countries like the United Kingdom (GBR), Denmark (DNK), Sweden (SWE), Norway (NOR), Netherlands (NLD), Germany (DEU), United States (USA), and Canada (CAN) present minimal risk of experiencing high persistence in unemployment duration in the future.

The measurement of the relationship between development outcomes and persistence in unemployment duration has been scarce. Generally, the literature has focused on the analysis of development and unemployment without delving into the duration of unemployment, let alone persistence in duration.

This paper provides a solid foundation for the formulation of policies aimed at promoting sustainable employment and inclusive economic growth.

Based on the findings of the study, two key development policies are proposed. Firstly, the implementation of investment programs in Human Capital to increase productivity is recommended. Resources should be directed towards initiatives that improve the necessary skills and competencies in the labor markets of OECD countries, especially in strategic economic sectors with higher production linkages. Additionally, incentivizing the application of active labor policies is proposed. This entails prioritizing policies aimed at increasing the labor income share in GDP through progressive fiscal reforms that strengthen social safety nets and ensure fair labor standards. Implementing employment programs targeted at vulnerable groups, such as long-term unemployed individuals, youth, female heads of households and marginalized communities, is also recommended to eliminate structural barriers to labor market participation and reduce disparities in unemployment persistence. Adopting these policies can help mitigate the risk of high unemployment duration persistence and foster sustainable and inclusive long-term economic growth.

This is the first study to analyze the probabilities of both developing and developed countries experiencing high persistence in unemployment duration. It specifically evaluates these probabilities over a period of time and also estimates potential outcomes if real investments were made to enhance their human capital, productivity and employability.

In this research, we explore the dynamics among measures of income inequality in the USA, male and female unemployment rates, and growth in government transfer using time series data.

This research adopts a macro-econometric approach to estimate a structural VAR model using time series data.

Our structural impulse responses found that growth in government transfer increases unemployment rates for both males and females. Female income inequality declines with increased government transfer. When the female income ratio rises, we observe that government transfer outlays fall over the forecast horizon. Variance decomposition finds that growth in government transfers is impacted by the male unemployment rate relatively more than the female unemployment rate. This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research investigates the dynamics among income inequality, government transfer, and unemployment rates. There is a dearth of research articles that adopt a macro-econometric in this area.

Asian countries have had persistent unemployment levels. The purpose of this paper is to investigate the impact of government spending on unemployment. Furthermore, this paper investigates the moderating role of institutional quality on the government spending–unemployment nexus.

Using data from 35 Asian countries from 2000 to 2022, the dynamic ordinary least squares and fully modified ordinary least squares technique is used to tackle with aforementioned issue. In addition, pooled mean group estimation is applied to verify the robustness of the findings.

The results show that an increase in government expenditure and better institutions reduce the unemployment rate. Interestingly, the negative impact of government expenditure on unemployment will enhance and intensify with better institutional quality. Furthermore, trade openness and foreign direct investment decrease unemployment in Asian countries. The results are robust to various specifications.

Findings from this study provide important implications for governments. Governments should use public expenditure efficiently and enhance and improve institutional quality to reduce unemployment.

To the best of the author’s knowledge, this study pioneers the investigation of the moderating role of institutional quality in the relationship between government expenditure and unemployment in Asian countries.

This paper aims to investigate the impact of governance quality on total unemployment in general and female unemployment in particular in the Middle East and North Africa (MENA) region, comparing the post-Arab Spring period to the pre-Arab Spring era.

A fixed-effects model was used to analyze data from 15 MENA countries from 2002 to 2019.

Our results generally indicate that following the Arab Spring, an enhancement in governance quality is linked with a reduction in unemployment in the MENA region, specifically in the Levant and GCC regions, with this reducing effect being stronger for female unemployment compared to total unemployment. Yet, this trend does not hold in North Africa, where government improvements do not result in better employment.

This study uniquely uncovers the different effects of governance quality on unemployment across sub-regions and sheds light on its significant implications on female unemployment. The findings offer valuable insights for policymakers interested in the relationship between governance quality and economic outcomes in the region.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2022-0826

The purpose of the study is to investigate the impact of artificial intelligence (AI), machine learning (ML), and data science (DS) on unemployment rates across ten high-income economies from 2015 to 2023.

This study takes a unique approach by employing a dynamic panel data (DPD) model with a generalised method of moments (GMM) estimator to address potential biases. The methodology includes extensive validation through Sargan, Hansen, and Arellano-Bond tests, ensuring the robustness of the results and adding a novel perspective to the field of AI and unemployment dynamics.

The study’s findings are paramount, challenging prevailing concerns in AI, ML, and DS, demonstrating an insignificant impact on unemployment and contradicting common fears of job loss due to these technologies. The analysis also reveals a positive correlation (0.298) between larger government size and higher unemployment, suggesting bureaucratic inefficiencies that may hinder job growth. Conversely, a negative correlation (−0.201) between increased labour productivity and unemployment suggests that technological advancements can promote job creation by enhancing efficiency. These results refute the notion that technology inherently leads to job losses, positioning AI and related technologies as drivers of innovation and expansion within the labour market.

The study’s findings suggest a promising outlook, positioning AI as a catalyst for the expansion and metamorphosis of employment rather than solely a catalyst for automation and job displacement. This insight presents a significant opportunity for AI and related technologies to improve labour markets and strategically mitigate unemployment. To harness the benefits of technological progress effectively, authorities and enterprises must carefully evaluate the balance between government spending and its impact on unemployment. This proposed strategy can potentially reinvent governmental initiatives and stimulate investment in AI, thereby bolstering economic and labour market reliability.

The results provide significant perspectives for policymakers and direct further investigations on the influence of AI on labour markets. The analysis results contradict the common belief of technology job loss. The study’s results are shown to be reliable by the Sargan, Hansen, and Arellano-Bond tests. It adds to the discussion on the role of AI in the future of work, proposing a detailed effect of AI on employment and promoting a strategic method for integrating AI into the labour market.

This study investigates the effect of business cycles on school enrollment in Turkey. During recessions, school enrollment might increase as opportunity cost of schooling declines, yet it might also decrease because of reduced income households have for education. Which effect dominates depends on the context. We empirically explore this in a context displaying canonical features of developing countries.

Using the Turkish Household Labor Force Survey data for a period covering the Great Recession, we estimate the effect of unemployment rate separately for enrollments in general and vocational high schools and in undergraduate programs. To understand the cyclicality, we use a probit model with the regional and time variations in unemployment rates. We also build a simple theoretical model of work-schooling choice to interpret the findings.

We find that the likelihood of enrolling in general high schools and undergraduate programs declines with higher adult unemployment rates, but the likelihood of enrollment in vocational high schools increases. Confronting these empirical findings with the theoretical model suggests that the major factor in enrollment cyclicality in Turkey is how parental resources allocated to education change during recessions by schooling type.

Our finding of pro-cyclical enrollment in academically oriented programs is in contrast with counter-cyclicality documented for similar programs in developed countries, which highlights the importance of income related factors in developing-country contexts. Our heterogeneous findings for general and vocational high schools are also novel.

We investigate the impact of private credit expansion and contraction on the unemployment rate in Economic Community of West African States (ECOWAS) countries.

Credit expansion and contraction are measured using a three-level criterion. The fixed effect panel regression model was used to estimate the impact of private credit contraction and expansion on the unemployment rate in ECOWAS countries.

Private credit contraction significantly increases the unemployment rate in ECOWAS countries. Private credit expansion does not have a significant effect on the unemployment rate. Real GDP growth has a significant negative effect on the unemployment rate which supports the prediction of the Okun’s Law while the inflation rate has a positive and insignificant effect on the rate of unemployment in ECOWAS countries which contradicts the prediction of the Phillips curve.

Policymakers in ECOWAS countries need to be cautious when introducing policies that lead to private credit contraction as it could increase unemployment. Policymakers in ECOWAS countries should also find the “threshold” below which private credit contraction will worsen the unemployment rate and introduce policy measures to ensure that private credit contraction does not fall below the threshold.

The literature has not examined the factors leading to tight labor markets or unemployment in West African countries.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-12-2023-0939.

This study assesses the relevance of foreign aid to the incidence of capital flight and unemployment in 20 countries in sub-Saharan Africa.

The study is for the period 1996–2018, and the empirical evidence is based on interactive quantile regressions in order to assess the nexuses throughout the conditional distribution of the unemployment outcome variable.

From the findings, capital flight has a positive unconditional incidence on unemployment, while foreign aid dampens the underlying positive unconditional nexus. Moreover, in order for the positive incidence of capital flight to be completely dampened, foreign aid thresholds of 2.230 and 3.964 (% of GDP) are needed at the 10th and 25th quantiles, respectively, of the conditional distribution of unemployment. It follows that the relevance of foreign aid in crowding out the unfavourable incidence of capital flight on unemployment is significantly apparent only in the lowest quantiles or countries with below-median levels of unemployment. The policy implications are discussed.

The study complements the extant literature by assessing the importance of development assistance in how capital flight affects unemployment in sub-Saharan Africa.

This study finds whether there exists any correlation between the rates of technological progress, unemployment and labour productivity among a total of 21 world economies that are categorized as developed, developing and least developed by the United Nations. An attempt has also been made to check the reliability of the model through regression analysis. Time series analysis has been conducted over 19 years, from 2000 to 2018. The Solow Residual Method based on the Cobb Douglas Production function has been used and modified to find the rate of contribution of technological progress towards Gross Domestic Product (GDP) for each country. Correlation analysis has been conducted to measure the degree of correlation between the variables and trend analysis has been used to identify the exact directions in which the variables are moving. Further, regression analysis has been conducted to check whether the identified strength of the relationship between the dependent and the independent variables can be well justified or not. There is an unsustainable economic development when the contribution of technology to a nation's GDP increases in tandem with an increase in the rate of unemployment. A country is said to have sustainable economic development when the rate of contribution of technical advances to GDP growth drops or if it grows but with a lower unemployment rate.

The purpose of this paper is to empirically analyze the impact of social inclusion factors and foreign fund inflows on reducing gender-based unemployment in India.

A time series data set for the period of 1991–2021 has been considered, and an autoregressive distributed lag methodology has been applied to measure the short- and long-run impact of social inclusion and foreign fund inflows on reducing gender-based unemployment in India.

According to the study’s findings, both social inclusion and foreign fund inflows are critical factors for reducing male unemployment. However, in the case of female unemployment, only social inclusion factors play an important role, whereas foreign fund inflows have no role in it.

Analyzing the factors that affect gender-based unemployment has always been a grey area in literature. There are very few studies that capture gender-based unemployment in India, making this study a novice contribution. Second, it examines the relationship between foreign fund inflows, social inclusion and unemployment, which is another novel area of investigation. Finally, this study provides comprehensive and distinct results for both male and female unemployment that can help policymakers devise gender-based unemployment policies.