This paper investigates the impact of violence against women (VAW) on a woman worker’s likelihood of employment in the public sector. It argues that women may prefer to work in the public sector rather than the private sector if they perceive the former as safer. To empirically test this hypothesis, we combined data on crimes against women reported by the National Crime Records Bureau (NCRB) with individual-level information from the Periodic Labour Force Survey (PLFS). The paper employs a probit model with Heckman’s two-step sample selection method. The findings indicate that an increase in crimes against women in a district raises their probability of employment in the public sector. This effect is particularly strong for women from urban areas and female-headed households. The results suggest that effective enforcement of sexual harassment regulations in the private sector can have a positive impact on overall female employment. Also, firms may attract and retain talented women by implementing sexual harassment policies in an effective and transparent manner.
We examine the drivers and impacts of Indian immigration to the European Union (EU) in two countries and sectors: the information and communication technology (ICT) sector in The Netherlands, and the agricultural sector in Italy. We find that Dutch migration policy for skilled migrants promotes labour market flexibility and means that—in contrast to more restrictive schemes where skilled migrants may be tied to one particular job—migration may have spill over benefits beyond the company where the migrant is first employed to the wider sector. In Italy, regularisation and family reunification allowed migrants who would otherwise have remained in at best insecure and precarious conditions (and would mostly have been unaccompanied men) to establish themselves and their families and to be become gradually more integrated in the Italian economy and labour market. This has also allowed upward occupational and sectoral mobility.
This study investigates the impact of innovation on labour welfare in Indian organisations, highlighting the mediating roles of productivity and sustainability. Using a cross-sectional survey of 338 employees across manufacturing, services, technology and agricultural sectors, the analysis employs structural equation modelling (SEM) with partial least squares (PLS) to examine the relationships among innovation, productivity, sustainability and labour welfare. Findings indicate that innovation significantly enhances labour welfare both directly and indirectly. Productivity emerges as the strongest mediator, demonstrating that efficiency gains, improved output quality and effective resource utilisation are key channels through which innovation benefits employees. Sustainability practices, including environmental, social and governance (ESG) adoption and socially responsible initiatives, also mediate this relationship, though to a lesser extent. The results underscore that innovation alone does not automatically improve labour welfare; its positive effects depend on how organisations integrate productivity and sustainability initiatives. These insights provide guidance for managers and policymakers to promote inclusive, equitable and high-performing workplaces in India.
The primary objective of this study is to explore the impact of inflation and unemployment on the economic growth of ASEAN countries. This investigation employs panel data and utilises the Autoregressive Distributed Lag (ARDL) model for estimation and result analysis. The study employs the test for cointegration to establish the presence of a long-term relationship in the model. Consequently, both long-term and short-term ARDL models are estimated. The long-term results reveal a significant and negative impact of inflation on economic growth in ASEAN countries, while unemployment exhibits a negative direction consistent with Okun’s Law, but does not attain statistical significance in the long run. In the short term, unemployment and inflation are found to have different effects on economic growth in ASEAN countries. Based on these findings, it is recommended that authorities should prioritise credible inflation-targeting policies, while the government should create opportunities to enhance the skills and capacity of the population.
Migration from the Northeastern hill states to Indian cities has increased substantially in recent decades, yet evidence on the labour market outcomes and ‘integration’ experiences of these migrants remains limited. This study examines the outcomes of labour migration from the hilly states of the Northeast in Delhi, a major destination that hosts a large concentration of migrants from the region. The study is based on a primary survey of migrants from the hilly Northeastern states working in Delhi. Using descriptive analysis and Hierarchical Linear Models (HLMs) to analyse employment, income, remittance behaviour, and migrant social integration, we examine the migration process and outcomes. The findings show that education, work experience, social networks, and job-search channels play a crucial role in shaping access to employment opportunities in Delhi. The HLM estimates indicate that state-level differences explain only a small share of income variation, suggesting that migrants’ origin state identity has limited influence on earnings once they enter Delhi’s labour market. However, educational attainment, age, job-search channels, and work experience emerge as the primary determinants of monthly earnings. Further, household economic conditions at origin strongly influence remittance behaviour, with migrants from poorer households being more likely to remit. The study also highlights the importance of social and community networks during the COVID-19 pandemic. Overall, the findings underscore the central role of human capital and social networks in shaping migration outcomes among Northeastern migrants in Delhi.
The development of digital platforms constitutes part of the new ways of organising the labour process which reaffirms the logic of capitalism grounded in spatial (re)organisation. This paper examines how the platform economy’s labour process and labour geography intersect in shaping power relations and worker experiences, drawing from a South African context. The extractive rationalities of platforms, which privilege profit accumulation over interests of workers and communities, coupled with their limited spatial embeddedness within local institutional and cultural milieus, provoke contestations of the labour process and the associated spatial logics. These contradictions stimulate counter-strategies from below to redress the misalignment. This study argues that this response encapsulates grassroots creativity articulating the demand for the decolonisation of the platform delivery ecosystem, and the claim for digital sovereignty, and co-production of digital ecosystems anchored in local context and culture. Solidarity in this context must be reimagined. The study concludes that success in the delivery platform ecosystem hinges on the degree of spatial embeddedness in the local culture and context.
The goal of the present study is to find out the impact of climate change (CC) along with a few other variables like expenditure on education (Edu), health (Hea), social security and welfare (SSW), and internet penetration (IntPene) on productivity viz., labour productivity (LP) and total factor productivity (TFP). Based on a priori reasoning, we can expect these variables signifying environmental (CC), social (Edu, Hea, SSW), and technological (IntPene) changes to impact productivity in the case of India. Leveraging data from various national and international sources, this study is anchored in a time-series analysis from 1992 to 2017 The study uses an autoregressive fractionally integrated moving average (ARFIMA) statistical technique and prepares two models, one with LP as a dependent variable and another with TFP as a dependent variable bringing out the profound impact of the environmental (CC), social (Edu, Hea, SSW) and technological (IntPene) factors on productivity. Our results indicate that CC impacts LP negatively and significantly. The impact of Hea and IntPene on productivity is positive and significant. However, the impact of Edu on both LP and TFP turns out to be negative and significant. The paper underlines the need for a mix of adaptive and preventive approaches to address the negative impact of CC on productivity. Besides this, technical adaptations, infrastructure and regulatory interventions are also recommended to raise LP. Public expenditure on SSW is hurting both LP and TFP. Therefore, the productivity-enhancing effect of such SSW policies needs to be seriously evaluated both by proponents and by sceptics.
It hardly needs stressing that multiple dimensions pertaining to the world of work are organically intertwined with the nature and functioning of capitalism in its different phases; this paper engages with some of the critical linkages between neoliberal capitalism, which started gaining global ascendancy by the late 1960s–1970s, becoming hegemonic as the macroeconomic policy regime, and major features relating to the landscape pertaining to work across the globe. Although the broad trends relating to outcomes associated with the working people since the 1970s are marked by a degree of unevenness, across regions and countries, the fact of serious adversities is inscribed on almost each one of these. It is well documented that there have been, inter alia, incessant assaults on the working people across the globe, intensification of precarity, and undermining of the trade unions across sectors, during more than seven decades of neoliberalism. Massive acceleration of primitive expropriation mechanisms reflected in heightened extractivism, intensified grabbing of land and other natural resources, ever-increasing reckless profiteering from the planet Earth, and all that surrounds it, among other adverse and pressing challenges have become commonplace. Sure enough, increasing assaults on working people have not gone unchallenged and there have been powerful instances of innovative forms of resistance from working people at large. Without romanticising or exaggerating any of these positives, it is extremely important to take note of such efforts aimed at strengthening alliances and envisioning of new horizons.
During the post-economic reform period, India experienced rapid economic growth alongside a structural transformation in terms of sectors for both gross value added and labour allocation. The structural changes in labour allocation require a careful scrutiny, as in many cases, the reallocation of labour has been found to move in the wrong direction, leading to a dampening of overall productivity growth. With this question in mind, our study examines the reallocation of labour across industries in India vis-à-vis the labour productivity growth. For the analysis of growth in labour productivity, we adopt the decomposition method proposed by McMillan and Rodrik (NBER, Cambridge, 2011) and De Vries et al. (2015). This method enables us to demonstrate that during the post-economic reform structural transformation, labour allocation in India has been moving in the right direction. The study finds that the most dynamic industries during the post-economic reform period primarily belong to the service sector. Construction, however, despite being in the secondary sector, has ranked among the top industries contributing to employment generation with modest productivity growth.
The aim of the study is to examine the inter-linkage between internal migration, remittances, and households’ economic wellbeing by using asset accumulation as a wellbeing indicator of households. We obtained data from 245 migrant and 330 non-migrant households in rural Jharkhand through a three-stage stratified random sampling method. The results show that migrant families economically outperform their non-migrant counterpart economically over time, with both the regularity and amount of remittances exerting a significant positive effect on households’ wellbeing.
Self-employment is emerging as a dynamic alternative to traditional wage and unpaid labour, offering opportunities for individuals in the workforce—such as contributing family workers—to move from unpaid work to more flexible and autonomous economic activities. It significantly drives economic growth by creating new earning opportunities and reducing unemployment rates in developing countries. This study explores the dynamics of self-employment in Bangladesh, focusing on the key determinants driving the likelihood of being self-employed compared to unpaid worker. Using data from the 2022 Quarterly Labour Force Survey, this study employs a Multinomial Logit Model (MNL) for the analysis. The findings highlight that factors such as age, education, household wealth, household headship, and urban residence positively influence the choice of self-employment over unpaid labour. In contrast, factors such as being female, having disability, larger household size, greater land holding, and residing in Rajshahi, Rangpur, and Sylhet divisions reduce this likelihood. The findings suggest that education and wealth are particularly crucial for individuals engaged in self-employment, while gender disparities persist, with women facing considerable challenges in being engaged in self-employment vis-à-vis unpaid labour. Urban residence provides better opportunities for economic independence compared to rural regions.
The rise in open unemployment rates in India has been noted with concern in recent literature. An aspect of unemployment that has not received adequate attention in the Indian context is the duration of the spells of unemployment. We use nationally representative cross-section sample surveys for 2020–21, 2021–22, 2022–23, and 2023–24 to analyse the trends and correlates of unemployment spells in India. We find a significant increase in the incidence of long-term chronic unemployment during the study period. The burden of long-term unemployment is largely borne by the youth and the educated.
This paper investigates how female labour force participation (FLFP) is influenced by urbanisation, dependency ratio, working hours, and maternal mortality ratio (MMR) across countries with varying levels of Human Development Index (HDI). This study, driven by persistent global disparities in FLFP rates and their implications for gender equality and economic growth, seeks to explore the varied influences on FLFP and deliver policy-relevant insights. The study utilises a fixed-effect panel threshold model to analyse data from 51 countries over 34 years, identifying the HDI as a threshold variable that divides the countries into two distinct regimes, enabling nonlinear analysis. Results reveal that urbanisation reduces FLFP in countries below the threshold and has a positive effect in those above it. The dependency ratio inversely affects FLFP in countries above the threshold, likely due to the income effect, and positively affects it in countries below the threshold, possibly due to economic necessity. Because of concerns about work–life balance, long working hours discourage FLFP in both regimes. Maternal mortality ratio negatively impacts FLFP predominantly in countries below the threshold, highlighting health-related barriers to women’s economic participation. Based on these findings, it is argued that improving the healthcare system and flexible working hours are critical to increasing FLFP across countries, irrespective of HDI. On the other hand, policies that ensure gender-inclusive employment opportunities in countries below the HDI threshold and maintain work–life balance by reducing or sharing dependency burdens may help increase FLFP in countries above the HDI threshold.
In the recent past, rural Telangana’s unemployed, irregular, and underpaid workers have aimed their eyes on Gulf countries for employment opportunities, better jobs, regular employment, and higher salaries. This paper explicitly addresses the sociocultural-occupational characteristics of the emigrants who migrated to Gulf countries on the one hand, and the reasons for emigration, the magnitude of emigration, patterns of employment, working, and health conditions of the emigrants in the Gulf countries on the other. It examined the aftermath effects of the Gulf migration on left-behind families. The analysis was carried out based on the data collected in 2021 from four randomly selected districts of Telangana. It revealed that unemployment, dwindling local alternative livelihood options, and outstanding debts markedly forced emigrants to the Gulf Cooperation Council (GCC) countries. Measures to improve employment opportunities and new livelihood generation avenues in rural Telangana in an attempt to alleviate the vulnerabilities associated with the Gulf migration is the need of the hour.
Empowerment is a multidimensional process through which individuals acquire resources, assets, and agency to exercise control over their lives. Genuine empowerment extends beyond access to education and opportunities, requiring authority in decision-making and the pursuit of self-determined goals. The rapid growth of digital labour platforms has altered the nature of work by introducing algorithmic management, often accompanied by raising concerns of precarity and unequal access to empowerment opportunities. Using Naila Kabeer’s empowerment framework, the study examines whether platform work enhances empowerment relative to non-platform work, with a particular focus on sectoral, spatial, and gender disparities. The findings suggest that empowerment is unevenly distributed, with sectoral, spatial, and gender differences producing divergent experiences. By identifying the heterogeneity of empowerment outcomes, the study contributes to discussions on inclusive labour market strategies in the digital economy.
We study the distribution of women’s share of household earnings using data from the Indian Periodic Labour Force Survey (PLFS) for the year 2023–24. The aim of our study is to specifically look at whether couples systematically avoid situations in which a wife’s earnings surpass her husband’s, producing a cliff at 0.5 in the density function of wife’s share in household earning. We do find evidence for such a cliff, which is consistent with studies in many other countries. When looking at subpopulations, we find that the existence of a cliff depends on the nature of employment and level of education of husband and wife. Further we find that households on either side of the discontinuity differ significantly across many attributes. We use a logit model to look at the determinants of wives’ odds of out-earning their husbands, shedding light on the economic, social, and institutional factors that facilitate or impede gender-egalitarian earnings patterns.
In the strife-torn Manipur, violence broke out on May 3, 2023. Amidst public debates where the hill–valley dichotomy and migration/infiltration caught mass attention, the discourse on crowding Imphal Valley has surfaced and fuelled the controversy. Imphal Valley, originally comprising four districts and skirted by hills, has witnessed an increase in population (around fourfold since 1951), with density shooting up from 324 population/km2 in 1971 tp 730 in 2011. The present study aims to shed light on the discourse of crowding Imphal Valley through the lens of internal migration, alongside the hill–valley dichotomy. It estimates the hill-to-valley migration volume based on the 2001 and 2011 Censuses, and links it with the growing concentration of tribals in the Imphal Valley. Finally, it delves into the reasons for the crowding of the valley. The study estimates around 38,000 lifetime migrants in the Imphal Valley in the 2011 Census, and the majority, around 60 per cent or 23,000, are from hill districts. The most preferred destinations are Imphal Municipal Corporation and adjoining outgrowths in the valley. Frequent conflicts, the lack of job opportunities and a higher unemployment rate, poor economic conditions, wide regional development disparities, and the absence of comprehensive land regulation induce mass inter-district migration, and many are also leaving the state. Hill–valley integration with peaceful coexistence and decentralised policies should be integral to the state’s development drive.
This article offers a corrective to the narrow-mindedness of mainstream economics by critically examining how leading schools have treated and often dismissed the question of involuntary unemployment. Its central contribution lies in restoring involuntary unemployment to the analytical foreground through a comparative assessment that spans Classical, Walrasian, New Classical, New Keynesian, Keynesian, and Marxian–Kaleckian perspectives. The analysis demonstrates that while Classical, Walrasian, and New Classical frameworks seek to render the concept theoretically irrelevant, Marxian–Kaleckian approaches preserve and deepen its significance. New Keynesian economics, although formally retaining the concept, is shown to dilute the core insights of Keynes’s original analysis by reabsorbing unemployment into market-clearing logic. By mapping these divergent theoretical trajectories, the article highlights the rich yet neglected legacy surrounding involuntary unemployment. It argues that reintroducing these debates into teaching, research, and policy analysis is essential not only for understanding unemployment as an inherent feature of capitalist society but also for expanding the analytical boundaries of the economics discipline itself.
Integrating artificial intelligence (AI) as a revolutionary information technology (IT) across various economic sectors is imperative to achieve the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 8, by augmenting employment and economic growth. Therefore, this study examines the direct and moderating roles of AI in sectoral employment, promoting economic growth in India from 1985 to 2022. The empirical findings using the dynamic autoregressive distributed lag (DYARDL) approach posit that AI substantially augments India’s economic growth. However, the DYARDL and the robustness analysis using kernel-based regularised least squares reveal a positive but lower magnitude of coefficients for the moderating role of AI with sectoral employment on India’s economic growth. Thus, from a policy perspective, this study suggests careful formulation and implementation of policies to foster the broader application of AI and address the potential threat of AI to employment and economic growth in India.
Education expansion during the past decades did improve workers’ productivity and economic growth; however, it also raised concerns about the mismatch between the education acquired and the education needed by the occupation. Therefore, the objective of this study is to measure education mismatch in the labour market of Pakistan and explore its determinants from both supply and demand-side perspectives by using the Pakistan Social and Living Standards Measurement (PSLM) 2019–20 data. Our results indicate that overall more than 40
