Job quality in India’s rural non-farm sector: Challenges and policy imperatives

By Amandeep Kaur, Sumit Kumar, S.P. Singh* 

The importance of rural non-farm sector notwithstanding, some issues concerning the sector are constantly under scrutiny, such as types of jobs, alternate opportunities, and changes in economic status after employment. The evolving nature of the rural sector also suggests that simply being employed in rural non-farm sector is insufficient for evaluating rural livelihoods; the quality and sustainability of employment are equally important. Those engaged in rural non-farm activities face various challenges including the seasonal and irregular nature of jobs, low wages, informal and insecure job opportunities, lack of health and unemployment insurance, and jobs without clear employer-employee relationship (Binswanger‐Mkhize, 2012; Jha, 2006; Lanjouw & Shariff, 2004; Start, 2001). 

Moreover, the solution of the agrarian distress by engaging in rural non-farm jobs is questionable again because of the type of the jobs and activities offered by the sector. Therefore, a study by Dr. Kaur along with Dr. Kumar and Dr. S.P. Singh focuses on the measuring the quality of employment in India’s rural non-farm sector and identifying the factors associated with it using the recent PLFS (Periodic Labour Force Survey) data. However, in the past researchers have made attempt to measure it by using an indicator, by using a range of indicators or by constructing a composite index (Expert Group on Measuring Quality of Employment, 2015; Ghose, 1999; Standing, 2002; Steffgen et al., 2020). 

Even though no attempts have been made to measure quality of employment of rural non-farm sector particularly in Indian context. Keeping in mind, the importance of non-farm sector, studying the quality of jobs in rural non-farm sector can assist in providing precise policy measure to improve the quality of employment in rural non-farm sector. The study focuses on measuring quality of employment in rural india using six indicators namely vocational training, informal employment, collective bargaining, multiple activities, employment in hazardous industries, and social security. 

Each individual indicator plays an important role in identifying quality of employment in rural India and specifically in rural non-farm sector. Based on these selected indicators Quality of job index is created which define four categories i.e. categorized into four groups: good quality, moderate quality, bad quality, and extremely bad quality.

According to the composite index of quality of employment (CIQE), the data indicates a worrying trend as quality of jobs has worsened from 2017-18 to 2023-24. This deterioration could be linked to the increase in informal jobs, low collective bargain, and lack of social security in jobs in rural India. 

These findings stress the need for urgent policy interventions targeted at improving the job quality of rural Indians. The proportion of good quality jobs have declined 6 percent to 4 percent in the year 2023-24, whereas a proportion of workers working in bad quality jobs in rural India has increased significantly by 26percent points from 2017-18 to 2023-24 along with proportion of workers in extremely bad quality jobs has increased from 2 percent to 12 percent in 2023-24 (refer Figure1).

To identify the factors influencing the increase in bad quality jobs, the authors have applied ordinal logit model to understand the nature and factors for specific category of jobs. Among the household variables, caste and religious minority significantly impact the quality of jobs in 2017-18 and 2023-24. This suggests that worker being from a marginalized social group like scheduled caste, scheduled tribe or backward caste have higher likelihood of being in a worse quality job as compared to good quality jobs. The historical experiences suggest that the households belonging to scheduled castes have inadequate access to capital and are usually not equipped with high level of skills and education which can make them unable to be absorbed in regular wage market and are more likely to get employment as casual labour in the low quality jobs (Thorat & Sabharwal, 2006). 

Only in the year 2017-18, household size significantly impact the quality of jobs. With increase in number of people in the household the odds of getting worse quality of jobs increases. In the year 2017-18 and 2023-24, keeping other things constant, having a graduate degree is significantly associated with a lower likelihood of being in a bad quality job. Same is true for workers with post-graduate degree. In the years 2017-18 and 2023-24, post-graduates are significantly less likely to be in bad quality jobs. Similarly, for workers having technical education have lower probability of working in bad quality jobs in rural India. It is evident from the findings that higher education and technical education continues to play a crucial role in getting better quality jobs in rural India. 

Gender is not found to a significant factor impacting quality of jobs in rural India. For both the years 2017-18 and 2023-24, the coefficient for females is negative and significant at the 1 percent level. This indicates that women are less likely to be in bad quality jobs vis-à-vis their male counterparts. This could suggest a protective effect for women in rural employment and whenever women tend to find that quality of job is poor then they might be leaving the job as compared to working in bad quality jobs as it is evident from descriptive statistics that around one-fourth of workers were female in the year 2017-18 and 2023-24. 

In both years, the coefficients for age and square of age of workers are statistically significant, suggesting that age have significant influence on job quality. The sign of age and age square indicate that it may follow inverted U-type relationship with probability of getting quality of jobs and age of the worker. 

The results show negative and statistically significant relationship between weekly wages (in thousand) and job quality for 2017-18 and 2023-24 which indicate that with increases in wages, likelihood of working in a worse quality job declines. The significance of weekly wages emphasizes the strong association of low pay and low-quality jobs in rural India. 

The quality of job prospects also varies with the type of occupation, elementary occupation such as cleaners and helpers, labourers in mining, construction and manufacturing and transport, kitchen helpers, street related activities, garbage collectors and sweepers has a positive and significant effect on quality of jobs. It indicates that workers in these elementary occupations are more likely to be in lower quality jobs vis-à-vis other occupations. 

Workers in the category of craft and trade workers such as working as building and related trade workers painters, builders, metal, machinery, moulders and weld workers, handicrafts, electrical workers, food processing and related trade workers etc. have higher and statistically significant odds of being in worse quality jobs, suggesting this occupation is associated with poor working conditions vis-à-vis other occupations in rural India. Similarly, service and sales workers like conductors, guides, cooks, waiters, hairdressers, beauticians, sales workers, shop salespersons, personal care workers etc. also have higher odds of being in lower job quality vis-à-vis other occupations. 

Furthermore, workers working as plant and machine operators, assemblers, drivers and mobile plant operators also have a statistically significant impact on job quality. 

The results of the ordered logistic regression indicate that several household level and individual level factors play a significant role in determining job quality in rural India. Key factors are caste, religion, education of the workers, gender and age of the workers, wages, and type of profession. The impact of education is particularly notable, with higher educational attainments and technical education improve the job quality. Furthermore, occupations like elementary occupations, craft/trade, operators, sales/service jobs are more likely to be associated with poor job quality in rural India (refer, Table - Source: Unit level data from Periodic Labour Force Survey (Government of India, 2019, 2024).

The findings emphasise that there are persistent inequalities in rural job markets especially with respect to caste, education, and nature of occupation. These findings emphasis that there is need for more budgetary consideration for focused and targeted policies to improve job quality. Recent efforts to enhance skills, education and vocational training should be strengthened by more allocation of budget this time. For instance, scaling up and expansion of Pradhan Mantri Kaushal Vikas Yojana (PMKVY) with other vocational programs for the youth at rural areas is required. More budget is required for Industry-academia linkages to ensure the training schemes are industry relevant and aligned with the market requirements. Institutional set up is required to build skill hubs in rural areas along with the cooperation of ITI and local institutions. 

Furthermore, more budget for Mudra Loans and microfinance programs for rural entrepreneurship, rural start-ups support facility in agro-processing, textiles, and handicrafts will help to promote better quality self-employment jobs. Moreover, provision of digital skilling will enable teleworking of rural youth, extension of broadband as well as mobile connectivity to encourage e-commerce, provision of online job platforms and digital platforms interconnecting the rural artisans to urban markets can help to resolve the quality of employment issues to greater extent. 

Therefore, establishing an ecosystem that supports diverse industries and improved job opportunities can increase the access and quality of employment in rural India. Policymakers must prioritize these issues to ensure sustainable and equitable employment in India's rural economy.

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*Respectively: Assistant Professor, Jaypee institute of Information Technology, Noida, Uttar Pradesh, Ph.d from IIT Roorkee; Assistant Professor, Guru Guru Granth Sahib World University, Fatehgarh Sahib; Professor and Head, Department of Humanities and Social Sciences, IIT Roorkee