Indian Journal of Labour Economics最新文献

There is no regular mandated increase in minimum wages for workers employed in the Bangladesh ready-made garment (RMG) industry. Workers in the past have relied on optional bonuses added to their monthly incomes to supplement their wages. However, a new minimum wage implemented in January 2019 in the Bangladesh RMG sector increased wages for many workers who are known to work under poor and exploitative working conditions. Qualitative in-depth interviews were conducted with fifteen currently employed RMG workers (female: 13, male: 2), which led to data saturation. The participants were purposively recruited from both export processing zone (EPZ) and non-EPZ factories located in Dhaka and Chattogram, the two largest cities of Bangladesh where the majority of RMG factories are situated. Transcribed interviews were analysed thematically. The findings revealed that working hours, production targets, work pressure, and workplace abuse have an impact on workers' health and well-being. In line with the Marxist notion of the "accumulation of capital", we argue that due to the profit maximization mindset of RMG owners and international brands, workers have not received the potential benefit of the newly implemented minimum wage as their conditions have been changed in other ways to offset the increase in salary. The article contributes to understanding how factory owners' profit maximization mindset dispossessed workers from receiving the real benefits of the newly implemented minimum wage and forced them to continue working within exploitative working environments. The study shows that the impact of minimum wages on poverty reduction is unlikely and outline the need for RMG labour market reform.

This study has tried to compare the earning and non-earning aspects of migrant workers from West Bengal engaged in different types of work in Karnataka and Kerala based on survey of 111 Bengali-speaking migrant workers and a number of in-depth interviews and FGDs. The study has found that most of the migrant workers landed in south India only after working in Kolkata, northern or western Indian cities. Lack of regular employment opportunities and low-wage rate in rural as well as urban West Bengal are the dominant reasons for their migration. Hostile social environment and increasing earning uncertainties in northern and western Indian cities along with higher-wage rate in south India are reasons for the migrant workers shifting to south India. On an average, they earn Rs. 1.7 lakhs annually and are able to send almost two-thirds of their earnings as remittances. Except the rag pickers in Bengaluru, all other migrant workers live without their families at destination locations. The living conditions of the migrant workers, especially the rag pickers, are poor. Continuous inflow of migrant workers from eastern and north-eastern India is now a challenge for the incumbent Bengali migrant workers in south India; however, majority of them are not willing to return to West Bengal in future. The pandemic and successive rounds of lockdown in destination and home states have unsettled their lives. Not only their income has fallen, getting job and movement across different destination locations has become uncertain too. They have now hardly any resource to cope up with this continuing uncertainty.

The Centre for Monitoring Indian Economy's (CMIE) Consumer Pyramid Household surveys have emerged as an important source of regular labour market data for India. Given the differences in methods in data collection between the CMIE and official employment sources, it becomes exceedingly important to establish some comparability between the government and the CMIE datasets. With the release of the official Periodic Labour Force Surveys for 2017-18, we now have an overlap between the official datasets and CMIE datasets. In this paper, we examine the extent of comparability of labour force estimates from these two datasets. We find that employment estimates for men are broadly comparable. However, for women, there is a consistent divergence, with CMIE estimates of women's workforce participation lower than that of NSS-PLFS. We find that irrespective of the reference period used in the PLFS estimation of employment statuses, there is no convergence with the CMIE employment estimate for women's employment. Moreover, the mismatch in CMIE-PLFS estimates occurs across all types of women's employment and irrespective of what reference period of employment (in official data) is used.

This paper is an attempt to assess India's performance in generating the required quantity and quality of employment for its growing population since independence in 1947. But the exercise is set in a longer period that covers India's population growth since the turn of the twentieth century (1901) in relation to its ability to generate employment. The half-a-century preceding independence, despite a slow population growth, was a disaster in generating employment and any signs of structural change. Detailed analysis of the issue since independence shows that there was indeed a demographic burden more than the world average as well as its comparator Asian countries such as China and Indonesia. While employment generation with reference to growth-employment elasticity-was quite impressive during the first four decades of independence, it almost collapsed ever since the adoption of neoliberal economic reforms in 1991, thus entering a phase of 'jobless growth', a phenomenon that is shared by China in a more vigorous form. This has led to what may be called an exclusion of working age people from not just employment but from labour force indicating the emergence of 'discouraged workers' in a larger set that we called underutilized labour. But what about those who are included in the workforce? Does it ensure an escape from poverty for those at the bottom? Our estimates show that the pace of reduction in the incidence of poverty is so slow that a significant share of households is still below the international definition of extreme poverty. We attribute this to the quality of employment characterized by a high incidence of informal sector employment as well as low wages measured by the share of workers not receiving a recommended subsistence wage. The absence of any kind of social security to an overwhelming share of workers adds to this situation of absolute poverty. Finally we examine the question of poverty from the point of manifold inequalities by dividing the households in the economy in terms of their employment, educational, rural-urban, and social group statuses for estimating predicted probability of being poor. The results bring into sharp focus the huge variation in predicted probability that shows households with low education, disadvantaged social group status, casual nature of employment, and living in rural areas at the bottom end of the scale. These results bring out the imperative for creating more employment with better quality.

Based on secondary data, this paper estimates the incidence of poverty by sectoral employment status of individuals and it explores the factors determining individual's joint probabilities of being poor and being engaged in the non-farm sector jobs (at micro-level). It also finds the impact (at macro-level) of rural non-farm sector employment on the incidence of rural poverty, and it identifies the subsectors of the non-farm sector, which help reduce the incidence of rural poverty in India. Using bivariate probit, recursive bivariate probit regression models, it finds that individual's human capabilities owing to better education and training and higher occupations of their head of the family significantly determine their probability of being employed in the non-farm sectors, which in turn help reduce their chance of being poor. The panel system generalized methods of moment result suggest that the provincial states of India, which have achieved higher level of non-farm sector NSDP growth along with the creation of jobs through an improved level of infrastructure (roads, railways, banking, and industries) base, have succeeded to reduce the incidence of rural poverty to substantially low levels. Based on these findings, it is argued that the incidence of rural poverty can be reduced on a sustainable basis through the development of rural manufacturing, and by promoting growth of modern service sectors like education, health, communication, real estate, and finance and insurance, along with the infrastructural development.

The Coronavirus pandemic has induced a huge economic crisis. The norms of social distancing and consequent lockdown to flatten the curve of this infection has brought economic activity across the globe to a standstill. A mass exodus of workers from major urban centres of India to their native villages started. Mental, financial and emotional agony inflicted due to job-loss, lack of job and livelihood opportunities led to this. A massive macroeconomic crisis for the country with serious ramifications has consequently exploded. The present study explores and captures the diffusion and discovery of information about the various facets of reverse migration in India using Twitter mining. Tweets provide extensive opportunities to extract social perceptions and insights relevant to migration of workers. The massive Twitter data were analysed by applying text mining technique and sentiment analysis. The results of the analysis highlight five major themes. The sentiment analysis confirms the confidence and trust in the minds of masses about tiding through this crisis with government support. The study brings out the major macroeconomic ramifications of this reverse migration. The study's findings indicate that a concentrated joint intervention by the State and Central Governments is critical for successfully tiding through this crisis and restoring normalcy. The subsequent policy measures announced by the government are being critically gauged. In addition, the authors have proposed measures to ameliorate this damage on the formal and informal sectors.

Given the informal employment relationship that marks the paid domestic work sector, this paper examines the important state interventions in India which follow the ILO convention on domestic work. The understanding that the sector is homogenous and thus could be regulated or managed through uniform intervention, whether legal or otherwise, has prevailed. This was even when existing studies have demonstrated the existence of segmented labour markets with varying employer, work and worker identities. The extension of the Minimum Wages Act to domestic workers, the draft National Policy on Domestic Work, and the Domestic Workers Sector Skill Council (DWSSC) set up under the National Skill Development Council of the Ministry of Skill Development & Entrepreneurship of Government of India, are examined in the paper in detail. The paper highlights how various state interventions have outlined the sector, the work, the workers and their everyday experiences and negotiations in terms of extending or framing these interventions. Examining the assumptions and objectives that have defined the formation of Domestic Workers Sector Skill Development council and its functioning, the paper argues that the attempt to corporatize the sector is a classic case of how the state tends to ignore the specificities that feature the sector leading to its poor impact.

The lockdown during the first phase of COVID-19 pandemic in India triggered an unprecedented humanitarian crisis. Labourers in the informal sector lost their jobs overnight and were stuck at their work places. The present study examines the risk of COVID-19 transmission among stranded migrant labourers and their livelihood challenges during  the lockdown. A telephonic survey was conducted during the lockdown of first wave of COVID-19 pandemic to collect information from the stranded migrant labourers. The non-probability snowball sampling technique and structured questionnaire were used to draw the sample. Simple frequency distribution and standard statistical methods were used to accomplish the study objectives. The factors of COVID-19 transmission such as poor housing, co-morbidities, poor practice of WASH and COVID-19 precautions were significantly high among the migrant labourers. The lockdown created livelihood crisis among them. For instance, ration shortage (86%), financial distress (82%), reduction of wages (13%), job loss (86%) and anxiety for COVID-19 infection (81%) were often seen. Many of the labourers did not receive any ration kits (30%) and financial assistance (86%) during lockdown. The governmental assistance to overcome the stranded migrant labourers' challenges during lockdown was less than desirable. India needs to frame a sustainable and effective policy for social security for labourers, particularly in emergency situations.

The COVID-19 pandemic has put pressure on the informal sector, especially in developing countries. Regarding the case study found in Yogyakarta Special Region (Indonesia), this research focuses on workers in the informal sector with the following objectives: (1) to assess the impacts of COVID-19 pandemic on informal workers' conditions, (2) to identify their strategies for surviving the crisis, and (3) to analyze the existing social safety net to support their livelihood. This study surveyed 218 respondents who worked in the informal, non-agricultural sector. The data were analyzed using descriptive statistical techniques. The results confirmed that most respondents underwent a decrease in working hours and incomes. In general, they have particular coping mechanisms to survive. The results also found that most respondents had high hopes for social assistance to stabilize their livelihood. Several government programs had been issued, either by improving policies before the pandemic or by creating new ones. However, there were many barriers and challenges to implementing them so that some recommendations had been suggested in this study to help the informal workers to become more resilient.

COVID-19 has disrupted the Indian economy. Government-enforced lockdown to restrict the spread of infection has impacted the household economy in particular. We combine aggregates from national income accounts and estimates from the microdata of a labour force survey covering more than 0.1 million households and 0.4 million individuals. The aggregate daily loss to households is USD 2.42 billion. While loss to earnings accounts for 72% of the total, the rest 28% is wage loss. Service-based activities account for two thirds of wage loss, and natural resource-based activities are responsible for most of the earning loss. The dominance of informal job contracts and job switching in labour markets intensifies this, with the most vulnerable group consisting of 57.8 million in casual engagement, who have a high degree of transition from one stream of employment to another on a daily basis.

Supplementary information: The online version contains supplementary material available at 10.1007/s41027-021-00352-8.