The economic activity of women in families from different cultures

The presented analysis uses data from time-use surveys which were conducted in India and Poland in the late 1990s and early 2000s. The calculations made use of statistical information describing individual households and their members. The applied method of multiple regressions for cross-sectional data made it possible to take into account selected socio-demographic and economic characteristics of the analysed members of the population. The results obtained served for assessing the impact of such characteristics as marital status as well as children presence on the production activity of women. We present the time allocation of individuals with similar characteristics, but at different stages of their life cycles. Performing analogous estimations for Poland and India made it possible to directly compare the situation of women in these countries. Despite considerable differences in terms of social and cultural norms between the analysed societies, the situation of women living in them is in some respects similar. However, marked differences were also observed such as those related to economic activity depending on the level of education. Also, the influence of marriage on the allocation of time is different, as illustrated by comparing the situation of married women to those without a partner.

NCAER News: December 2024

NCAER News is a monthly newsletter where you can learn about NCAER’s research outputs, its latest events, and offerings.

Government has made welcome moves to create employment, challenge now is to improve quality of jobs

The Employment Linked Incentive scheme could be made more holistic by incorporating skilling and training aspects of work. Emphasis should be laid on increasing awareness, as well as digitising and simplifying processes and payments linked with it.

India has experienced job growth, albeit slowly and of poor quality. According to the employment-unemployment survey and periodic labour force survey (PLFS), between 2011–12 and 2023–24, the workforce grew at 2.2 per cent while the labour force (those employed and those seeking jobs) grew by about 2.3 per cent. The latest data shows that about 78 per cent of workers did not have a written job contract, about 76 per cent were not eligible for any social security benefits, and about 72 per cent did not have paid leave. Contractualisation of jobs is becoming the norm, where workers employed on contract in formal manufacturing increased from 38 per cent to 41 per cent during 2018–19 to 2022–23 (as per the annual survey of industries). The female worker population ratio remains lower than males, and the youth unemployment rate is relatively high compared to overall unemployment rate.

In light of the above, schemes targeting formal job creation are welcome. A key budget announcement this financial year has been the implementation of the Employment Linked Incentive (ELI) Scheme to create over two crore jobs in the country in two years. Under the ELI, there are three paths.

Scheme A offers one-month wage (up to Rs 15,000 in three instalments) to first time employees registered with EPFO. This is open to all formal sectors. Scheme B focusses on job creation in the manufacturing sector, by incentivising both employees and employers for the additional employment of first-time employees, based on their EPFO contributions during the first four years of employment. Scheme C reimburses employers up to Rs 3,000 per month for two years towards their EPF contribution, for each additional employee across all sectors.

The question is whether ELI can help attain the desired objective of creating new and sustained quality employment in the country for both males and females. The standout feature of ELI is to target employees registered with EPFO, that is, moving workers (earning a salary up to Rs 1 lakh per month) towards formality by giving them a pension. However, the schemes raise some critical questions:

One, the size of the incentive. Is the subsidy on the salary cost in Scheme A enough to create first-time quality jobs across sectors? Is the quantum of incentives in Scheme B enough to change the nature of employment relations from short-term to long-term in the manufacturing sector?

Two, benefits linked to employment length. Short-term-ness in employment relations is prevalent on the demand-side, but the supply-side of the workforce too is increasingly mobile and frequently changing jobs — requiring companies to hire on a continual basis. Even if firms offer a permanent contract, what is the guarantee that the worker will stay for long? Rather, a key complaint is that freshers join, gain some experience, and leave for alternate opportunities. Though it is not explicitly stated, but any ELI benefits, if linked to a guarantee of a certain length of employment, are potentially unlikely to be of any benefit to companies.

Three, benefits for experienced employees. On-the-job training is a cost to companies. Hiring first time employees without experience, especially for specialised jobs, may not appeal to firms. From that perspective, Scheme C is more viable and will help generate more quality jobs in the existing workforce. But in proportion to the salary, EPF benefits get smaller as the salaries increase for skilled and experienced workers.

Four, the existing informal workforce. The three schemes are ambiguous on the existing informal workforce. Can informal workers be enrolled in EPFO as first-time formal employees to receive ELI benefits? This could especially be relevant for new and experienced informal workers alike.

Whether or not to hire, whether to hire first-time employees or experienced professionals, and on temporary or permanent basis, are all firm-based decisions. However, incentivising women employment in India via ELI can have both economic and social impact. Women are regarded as stable and disciplined employees, who are also easier to retain. Mandating non-discriminatory job advertisements clubbed with subsidising the “cost” of women employment for firms, including their initial on-the-job training, can incentivise firms to hire more women employees. This could go a long way in overcoming gender biases and erasing societal-norms that have kept women away from non-traditional job roles, particularly in the manufacturing sector. It should be supported with measures to provide working women hostels and creches at workplaces – as was also announced in the budget.

While ELI is focused on the demand-side of the problem, it can also link with the supply-side by improving the employability of the youth. Financial incentives for job creation have been introduced in other countries like Germany and the UK as well, with an integral focus on this aspect. While there are other schemes introduced in the country to support internships and apprenticeships, the ELI scheme could be made more holistic by incorporating skilling and training aspects of work. For instance, if a firms’ own apprentices/interns are hired as first-time employees, the size of their incentive increases.

The efforts towards facilitating job creation are appreciated. Given the realities of the Indian context, tweaks in the existing schemes can perhaps help better address the persistent issues in India’s labour market concerning women employment, youth employability, and informal and contractual workers. Firms will choose to be a part of any such scheme if they are aware of it, if the scheme’s modalities are clear and transparent, if there is timely monetary disbursal, and if there are clear remedies for quick redressal. Therefore, along with the scheme’s design, emphasis should be laid on creating awareness, as well as digitising and simplifying processes and payments linked with the scheme.

Dayal is fellow, Bhandari is professor, and Sahu is fellow, National Council of Applied Economic Research. Views expressed are personal.

Green energy transition

Capturing regional disparities is crucial.

In COP29, the focus was on finance since countries require significant funding for energy transition. According to International Energy Agency, clean energy investment needs to reach $4.5 trillion a year by 2030 to limit global warming to 1.5°C. The share of renewables in gross electricity generation at the global level must reach 91 per cent by2050 from 28 per cent in 2020.

This calls for significant mobilisation of resources. The requirement of funds is estimated based on various kinds of models. But a major fallacy of the Indian models is that almost all of them are national models, and do not capture regional disparities in energy demand, resources, and policies. In India, with huge disparity in geography, topology, culture, socio-economic condition, and demography across regions, it is quite difficult to capture all the aspects in one macro-economic or energy system model for the nation.

For example, some States are endowed with various fossil fuel resources and that provides jobs to a significant number of workers, some with longer hours of sunshine suitable for development for solar energy, and some have long coastal areas suitable for development of wind or ocean energy. State-level modelling and planning are necessary to understand the challenges and assess the investment requirement. 

Regional modelling

Many countries are using multi-regional models for understanding the optimum way to arrive at green energy transition to meet emission targets. For example, even though the EU is a community, each nation in the bloc has devised its own energy transition plan based on strength/weakness of resource endowment and in sync with the overall EU’s target. Large countries like the US, China and Brazil have invested into building multi-sector (100-500 sectors), multi regional models (all major regions as separate entities) for effective policy analysis including that of energy transition.

Resource diversity in the EU or other countries are probably less than that of India. Yet, our pathway is based on a national plan without taking into account the regional diversity. Ideally, a bottom-up approach should have been the right one in our case and national plan should have been derived by aggregating the regional ones and examining whether these are in sync with the national one. Though data availability is an issue in India, it is necessary to capture the regional diversity.

NITI Aayog, in collaboration with the Ministry of Power and the Ministry of New and Renewable Energy, launched the ASSET (Accelerating Sustainable Solutions for Energy.

Transition) platform to assist in formulating State energy transition blueprints and implementation, identifying bankable projects, best practices, innovations in critical sectors like BESSs (battery energy storage systems), green hydrogen, energy efficiency, e-mobility, offshore wind, etc., in line with Viksit Bharat 2047.

An NCAER study, featuring State-level Integrated Assessment Model (IAM) based on soft-linking of macroeconomic CGE model and MESSAGEix model, finds that, for Kerala, $230.75 billion is required cumulatively between 2025 and 2050 to finance low carbon transition for mitigation without hampering economic growth, with an assumption of 2.5 per cent improvement in energy efficiency and 1 per cent productivity growth per annum. For Odisha, the requirement of investment is $395.33 billion cumulatively between 2025 and 2050.

These estimates do not include the loss-and-damage cost, and the finances required for adaptation. To support low-carbon, climate-resilient solutions in energy, transport and agriculture, there is a significant need to invest in the renewable energy sector, and that needs to be captured by the ‘bottom-up’ State-level models and planning. To address this issue, NCAER is developing multi-sector (147 sector) multi-regional model (30+regions) covering all the States.

Chetana is Fellow, and Sanjib is Professor, NCAER. Views are personal.

India Human Development Survey: December 2024

The IHDS Forum is a monthly update of socio-economic developments in India by the IHDS research community, based on the India Human Development Survey, jointly conducted by NCAER and the University of Maryland. While two earlier rounds of the survey were completed in 2004-05 and 2011-12, respectively. Fieldwork for the third round was undertaken in 2022-24 and the data is currently being cleaned and processed.

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