Abstract
The empowerment of women is critical for improving their status in society and, in turn, women’s access to economic and financial resources is vital for their empowerment. Despite a discernible improvement in India’s rural economy in recent years, the rural female workforce has been declining. One of the primary reasons is that in rural areas women lack access to land and productive resources which aggravates the problem. The objective of this article is to examine trends, patterns and drivers of female workforce participation in rural India captured through the lens of migration, social and religious factors, land rights, agricultural income, education and wages. The study found that female employment in rural India has been reducing, possibly, for the following reasons: firstly, women tend to work only during distress conditions; secondly, they find working conditions either unsafe or unsuitable; and thirdly, social norms restrict their entry into the job market. The study suggests that improving their access to land and productive resources, providing them decent work opportunities and prioritising their education and skills training will collectively help women in improving their socio-economic status.
Introduction
The role of women in the socio-economic transformation of a country is now globally recognised. Though some national governments have taken affirmative action in the past few decades to improve the socio-economic status of women, those living in rural areas, especially in developing countries, continue to be marginalised and underprivileged for several reasons. Empowerment of rural women refers to a situation in which women living in rural areas have adequate, independent and equal means of livelihood and other economic, social and political opportunities for growth and upward mobility (Haque, 2015). Empowerment of women is a necessity for improving their status in society and therefore women’s access to economic and financial resources is vital for their empowerment.
While India’s economy has grown over the past few decades, its female workforce participation rate (WPR) is registering a decline. In 2012, Indian women comprised 27.37 per cent of the country’s economically active population. Out of these, 60 per cent worked in agriculture, accounting for 35 per cent of the agricultural labour force. The contribution of women in farm production is estimated at 55–66 per cent of the total labour force. 1 Women by nature take on domestic household responsibilities, but such gender roles limit rural women’s participation in labour markets and confine them to lower paid and relatively precarious employment conditions. Particularly in rural areas, women face discrimination in accessing resources and services needed to improve their productivity, such as access to credit, secure land titles and education (FAO, 2011). If women can access the same productive resources as men, they can boost farm productivity significantly.
The falling female WPR in India can be due to various reasons. These include what is known as the income effect––as household income rises, women start withdrawing from agricultural activities––low education enrolment; a lack of job opportunities and uncertain forms of measurement––it is difficult to accurately gauge the participation of women in work because of the nature of their jobs––home-based work, subsistence agriculture and so on. Several studies have analysed the reasons why women have been forced to stay out of the labour market. A study by Sanghi, Srija and Shirke (2015) says that the main cause is an insufficient number of non-farm jobs as well as a lack of adequate infrastructure such as roads and connectivity. Jatav and Sen (2013) find that non-farm employment in rural areas is primarily distress-driven, and there are some significant entry barriers for rural workers in the non-farm sector in terms of education, age and gender. Their study also emphasises the role of the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS) in rural employment generation and the consequent process of feminisation of the casual workforce in the non-farm sector that has emerged over the last few years. However, their study also finds that the overall quality of rural employment, driven by distress factors has deteriorated in 2009–2010 over 2004–2005 in a significant way.
In their 2014 study, Mehrotra, Parida, Sinha and Gandhi use NSSO data to explore employment trends in India since the mid-1990s. Their findings indicate a structural transformation of the rural sector: An absolute fall in agricultural employment and a rise in non-agricultural employment; increasing participation in education; a decline in child labour; mechanisation of agriculture and better living standards in rural areas due to a growth in real wages which has led to a fall in workforce participation, especially of rural women. According to Mehrotra and Sinha (2015), improving skills for employability will help rural women in joining the labour force if non-agricultural jobs are growing. However, to release women from unpaid work in the household and join the paid labour force, it is essential to improve childcare facilities and other basic services, which again require raising the share of public expenditure in specific sectors and specific facilities. Hirway (2015) assigns the lack of access to paid work outside their households as a major reason for the low socio-economic status of women in India. This, in turn, is determined by factors such as a low-level of education and skills. Further, since women do not have access to paid employment opportunities outside, they are engaged in unpaid family and household work within their homes. This has other implications leading to gender disparity in wages and income. According to Kelkar (2011), despite significant agricultural growth, improvement in real wages and non-farm employment in rural areas in recent years, rural women are at a disadvantage because they are frequently discriminated against in their livelihood security, education and autonomy.
The gendered distribution of assets and resulting vulnerability of women substantially limits national efforts at overcoming poverty. A study by Neetha in 2014 suggests that social and cultural inequalities such as caste and religion have a strong bearing on female employment outcomes, even when the latter are determined by market forces as a result of globalisation. The markets seem to operate within existing structural inequalities of gender and caste/religion; and rather than altering these inequalities, it worsens and reinforces them.
Against this backdrop, the objective of this article is to examine trends, patterns and drivers of female workforce participation in rural India, captured through the lens of migration, social and religious factors, land rights, agricultural income, education and wages. This article is based on data from the NSSO Quinquennial Rounds, including the few recently released reports of the 68th Round (July 2011–June 2012) as well as data from the Labour Bureau, Census of India and Agricultural Census, 2010.
Trends and Patterns of Rural Female Occupation Structure
The WPR, defined as the share of employed persons to total population, is 39 per cent in India, with 40 per cent in rural areas and 36 per cent in urban areas. The WPR in rural areas is 54 per cent for males and 25 per cent for females. The WPR in rural areas shows a decline over the years, especially for females as can be seen in Table 1.
Workforce Participation Rate (per 1,000) for Persons of all Ages according to Usual Status (PS+SS)
The share of males and females in the total rural workforce shows that the share of the female workforce is much lower, 31 per cent, as compared to males, 70 per cent. We see that their share started to decline from the 61st Round (July 2004–June 2005) (Figure 1).
Industrial Classification of Rural Female Workers
The share of male and female workers according to industry categories in rural areas shows that out of the total female workers in rural areas, the share of those engaged in the primary (agriculture) sector has been the highest—an average of 80 per cent over different rounds. This is higher than the share of male primary workers—an average of 70 per cent over different rounds. The share of female workers in the secondary and tertiary sectors is lower than that of males. In the latest round of NSSO (68th Round), we can see that in rural areas, 59.4 per cent of the usual status (PS+SS) male workers and 74.9 per cent of female workers are engaged in the agricultural sector. Among male workers, 21.8 per cent and 18.8 per cent are engaged in secondary and tertiary sectors. The corresponding proportions for female workers are 16.7 per cent and 8.7 per cent, respectively. Further, the share of primary workers for both males and females has been declining over the years, while that of secondary and tertiary workers is increasing. This improvement in the rural workforce participation since 2004, especially in the secondary sector can be attributed to MGNREGS, which mandates that at least one-third of the beneficiaries should be women, and that men and women should be paid equally (Desai, 2013). But despite these opportunities available in the MGNREGS, the share of rural women in secondary and tertiary sectors (non-farm occupations) is lower than that of men (Table 2).
Percentage Distribution of Usual Status (PS+SS) Workers of all Ages by Industry of Work in Rural Areas
As regards the type of female workers in rural areas, the share of cultivators and agricultural labour is the largest. In the recent census, the share of female cultivators, both main and marginal, is declining while that of agricultural labour is increasing. This means that even as the female workforce participation is declining, the shift within agriculture is more towards casual agricultural labour than self-employed cultivators (Table 3).
Share of Female Cultivators and Agricultural Labourers in Total Female Workers in Rural Areas (%)
According to the National Industrial Classification 2008, just as the national figures suggest, the majority of rural women in most states are engaged in agriculture and allied activities (74.9 per cent) followed by secondary (16.89 per cent) and then tertiary activities (8.2 per cent). Within the secondary sector most women are engaged in manufacturing (9.79 per cent) followed by construction (6.39 per cent) activities. However, in states such as Goa, Manipur and Tripura, a high proportion of rural women are engaged in the secondary sector, mainly in manufacturing and construction. In Delhi, a high proportion of rural women are engaged in wholesale and retail trade (37.45 per cent). But still, the overall movement of women into better formal jobs like professional, scientific and technical activities is weak (see Appendix 1).
Role of Migration in Rural Occupational Structure
It is important to understand patterns of migration to explain occupational structure of male and female workers in rural areas. Overall, rural female migration in India has been much higher than males. According to the 64th Round (July 2007 to January 2008), 477 women per 1,000 persons migrated from rural areas as compared to 54 men per 1,000 persons. Recent NSSO data shows that in the latest round (64th Round) female rural to rural migration was 59.6 per cent while for males it was 27.5 per cent. On the other hand, rural to urban migration has been higher for males (33.9 per cent) as compared to females (18 per cent). One can also observe that rural to rural migration has slowed down for both genders while rural to urban migration has increased for both over the two time periods, although the change is not significant for females. Female migrants in the rural to urban stream largely work as domestic workers (Mahapatro, 2010) (Table 4).
As for reasons behind rural migration, 78.14 per cent of rural female migration is due to women getting married. Only 1.78 per cent of migration is due to employment and 2.78 per cent because of education. This is in stark contrast to the pattern of rural male migration, which is mainly due to employment (29.67 per cent) and education (23.12 per cent). However, migration for employment appears to be reducing slightly for both sexes. Migration for education is increasing though it is much higher for males as compared to females, but it is still a movement in the right direction. Thus, the occupational shift in male and female workers in rural areas shows that male workers are steadily moving out of agriculture (and also out of rural areas) while for women workers this movement is extremely slow. This is because men are entering into more diversified occupations in non-agricultural fields while women seem to remain in largely stagnant agricultural activities. As far as female ‘marriage’ migration is concerned, many rural women who migrate after marriage end up in various employment activities though often these are temporary and low-waged (Table 5).
Distribution of Migrants by Sex and Migration Streams (Duration <5 yr) (%)
Reasons for Rural Migration by Sex (Duration <5 years) (%)
Role of Social Groups in the Rural Occupational Structure
According to the 68th Round of the NSSO, the rural female WPR is highest for Scheduled Tribes (ST) (48 per cent) followed by Scheduled Castes (SC) (35.5 per cent) and Other Backward Castes (OBC) (32.4 per cent). It is lowest for the ‘general’ category of women (24.2 per cent). SCs and STs are the most marginalised and impoverished sections of society. Women from these groups have higher WPR because extreme poverty drives them to work and also they do not face the social taboos that prevent them or disapprove of them working. The converse is true for women from ‘general’ castes (Figure 2).
According to the NSSO 68th Round (July 2011–June 2012), the female worker population is highest in Himachal Pradesh (524), Sikkim (487), Andhra Pradesh (445) and Chhattisgarh (415) and lowest in Bihar (53), Assam (122), Delhi (146), Haryana (162) and Uttar Pradesh (177). One finds that female WPR is usually more evident in states with a higher SC and ST population.
Role of Religious Groups in Rural Occupational Structure
According to the 68th Round of the NSSO, when you consider religious backgrounds, Muslim women in rural areas have a significantly lower WPR as compared to women of other denominations and also when compared to the national average for women of all religions. Once again it is social norms that restrict women’s mobility and entry into the workforce that keeps more Muslim women tied to hearth and home (Table 6).
Worker Population Ratio (WPR) according to Usual Status (PS+SS) among Persons of Major Religious Groups
Women’s Land Rights
In India a majority women still do not have ownership or control over land resources. The Agricultural Census provides information on operational (agricultural) holdings worked on by men and women, irrespective of ownership status. According to the latest Agricultural Census 2010–2011, only 12.79 per cent of agricultural landholdings, covering 10.36 per cent of area, is worked on by women. This proportion has increased only marginally over the last Agricultural Census of 2001–2002. In 2001–2002, women operated only 11.6 per cent of cultivated agricultural landholdings, covering 9.1 per cent of area. Significantly, there is an inverse relationship between land size categories and land holding shares as well as area shares operated by women. In marginal holdings, the share of landholdings operated by women is 13.66 per cent whereas the area operated by them is 12.82 per cent. In large holdings, the corresponding percentage declines to 7 per cent and 6.34 per cent, respectively. These figures can be explained by the cultural and social biases that exist in India which are mainly responsible for diminished control over a critical resource like land by women, especially relatively better off women. It can also be noted that in the absence of land titles, women farmers have less access to institutional credit and institutional support as compared to men farmers (Srivastava & Srivastava, 2010). A study released by UN Women, India and Landesa, a US-headquartered non-profit organisation working to improve land rights for women and men, finds that despite time spent working in the field and changes in inheritance laws, women rarely inherit the land that sustains them (Sircar & Fletschner, 2014) (Table 7).
Share of Number and Area of Operational Holdings by Size Classes (%)
The regional pattern of women’s control over landholdings reveals that they are in a better position in the southern states. In Andhra Pradesh, for instance, women operate on 25.4 per cent of landholdings, covering 22 per cent of area. The corresponding figures for other states in the south are 19.62 per cent and 13.9 per cent, respectively, in Kerala; 19.11 per cent and 16.28 per cent, respectively, in Tamil Nadu and 14.99 per cent and 13.07 per cent, respectively, in Maharashtra. These states show a comparatively better land rights situation for women as compared to states for a number of reasons. Historically, they have had more areas under the ryotwari 2 system; amendments to the Hindu Succession Act of 1956 3 also came here earlier (between 1986 and 1994) than at the centre; similarly, Stamp Duty for the registration of property in the name of women was also reduced earlier and also there has been more male-outmigration in these regions (Choudhury, Behera, Sharma, & Haque, 2017) (Table 8).
State-wise Share of Women’s Operational Holdings (%)
Employment and Agricultural Income
According to the 68th Round of NSSO, 59.3 per cent females of the rural workforce are self-employed, 5.6 per cent have regular wage/salaried employment and 35.1 per cent females are employed as casual labour as compared with 54.5 per cent, 10 per cent and 35.5 per cent males in the same categories, respectively.
One notes that the number of self-employed women in rural areas is the highest followed by casual and regular workers. The trend of self-employed rural women is almost a mirror-image of women involved in casual labour. Further, the share of rural female workforce participation follows the same trend as that of self-employment. The trend of self-employed women is high in rural areas because whether it is in low paid work as casual labour or better paid work as regular workers, both take women out of the confines of their homes and therefore give women freedom of mobility. However, in rural India where most women do not have this freedom and are restricted by social norms to their homes, but still need to work, self-employment is an option. The NSS surveys till the 55th Round (1999–2000) show some increase in female casual labour and a decline in the share of self-employed women. But during the 55th to the 61st Rounds (1999/2000–2004/05), there is a change in the trend; the share of self-employed workers increases while that of casual workers declines. Perhaps an overall stagnation in agriculture and the rural economy has led to this shift. The growth rate in agriculture and allied activities has been declining since the 50th Round and is at its lowest in the 61st Round. This may have led to the less wage work compelling women workers to eke out a subsistence by resorting to self-employment (Srivastava & Srivastava, 2010). The share of self-employment once again starts to decline from the 61st Round to the 66th Round. A part of this shift can be ascribed to a revival in the rural economy after 2004–2005 which appears to have benefitted from MGNREGS (Thomas, 2012). However, in the 68th Round (2012–2013), women’s self-employment seems to be rising in spite of better growth rates in the farm sector. One reason for this change can be that women finding work conditions to be unsuitable feel safer when they are self-employed. Further, constraints imposed by social norms also force women to seek self-employment options instead of wage employment (Figure 3).
At this point, it will be interesting to understand the nature of self-employment that is typically followed by women. According to NSSO’s definition of self-employed persons, women who are self-employed in household work mainly on land, as their own account workers, employers or as helpers. 4 So we can derive from this discussion that if, over the years, a majority of rural women are engaged in agriculture (see Table 2), are self-employed, increasingly as agricultural labourers instead of cultivators (see Table 3), and also have lower proportion of land holdings operated by them (see Table 7), then it means that most of these women are engaged as ‘helpers’ in the workforce. It is to be noted that, according to the NSSO definition, these self-employed women are mostly family members who tend to help or assist related persons, typically the males of the household, in managing their farm enterprise. Such women helpers working full or part-time do not receive any regular salary or wages in return for their help.
Further, one can observe that the overall self-employment among rural women is more than men across states and that a higher incidence of self-employment is found in the Northeast and northern hill states (Figure 4).
Education and Workforce Participation Rate
The rural female literacy rate has increased from 30.62 per cent in the 1991 Census to 46.14 per cent in 2001 to 58.75 per cent in the 2011 Census. With the gender-gap in rural literacy declining over the years it means that the improvement in female literacy rates is more than males in rural areas (Table 9).
Literacy Rates in India (%)
The distribution of rural workers across various education levels over several NSS rounds shows that during 2011–2012 among ‘employed’ rural males, about 28 per cent are not literate while 26 per cent are educated, that is, with a secondary and above educational standard. 5 On the other hand, among ‘employed’ rural females, about 56 per cent are not literate while only about 11 per cent are educated. We see that the share of illiterate working women though the highest is also declining. It appears that rural women are dropping out of the workforce in large numbers rather than joining up as the levels of their education increase. In this respect, economists note a ‘U-shaped’ relationship between levels of education and women’s workforce participation. It begins with a relatively high level of participation in the case of those who are not literate and declines with those who are literate up to the primary level and further drops in the case of middle school, secondary and higher secondary education levels as well as at the diploma/certificate level. It once again rises with a higher education level, such as graduate and above, which creates a ‘U shape’.
The share of working women in all education levels is increasing over the years though the share of educated males is much greater than women. However, despite the share of working women in higher education levels (especially secondary and above) increasing, the overall rural workforce participation is declining. Further, most of the rural female workforce is either illiterate or educated up to primary and middle education. The share of vocational training (diploma/certificate) among women is also less as compared to men which means that there is a preponderance of low skilled women in the rural workforce and that is not a good development (Table 10).
With very low levels of education and income, women have no choice but to work to help support their family. But as men in the family start earning more, women tend to cut back on their work in the formal economy to concentrate more on household activities. It is the women in the middle—those who are literate with at least some schooling or those who have only completed high school—who are squeezed both by the pressure to stay at home and by the lack of jobs that match their intermediate level of skills and education. With higher levels of education and income, women are able to re-enter the workforce by getting well-paid jobs that match their education and skills. It can be pointed out that the demand for employment for high school and university graduates has not kept pace with the large supply of women looking for such work. Frustrated at being unable to find work commensurate with their qualifications, many women choose to drop out of the workforce altogether, which contributes to a low and stagnating workforce participation level (Subramanya, 2013).
Per 1000 Distribution of Persons Aged 15 Years and Above and Usually Employed (PS + SS) by Education Categories
Average Wage Earnings (₹) Per Day received by Regular Rural Female Wage Employees of Age 15–59 Years by Industry of Work and Broad Education Category
At the state level, a higher female literacy in certain states like Kerala (90.80 per cent) does not translate to a higher WPR of women. It is a meagre 20.24 per cent. Similarly, the lowest rural female workforce participation is recorded in Delhi (9.72 per cent) despite a high literacy rate of 73.10 per cent. States like Nagaland, Chhattisgarh, Andhra Pradesh and Himachal Pradesh show a high WPR along with high literacy rates. Hence, being literate may not positively influence a woman’s participation in work, but for women who are in the workforce, literacy and education is the most important determinant of better quality and better paid jobs, especially non-agricultural work. So women with higher education levels receive better pay, especially in non-agricultural work as compared to women with lower education levels (Figure 5) (Table 11).
Despite increasing literacy rates among rural women and their rising shares in various levels of education as compared to men, the rural female workforce participation is declining. A report by the Labour Bureau, 2011–2012 (GoI, 2012) states that the unemployment rate for rural women is 4.1 per cent which is nearly double that of men (2.4 per cent). This can mean that women find work conditions unsafe or unsuitable.
Female Wages and Workforce Participation Rate
Wage rates have been increasing in nominal terms over the years for both males and females; however, male wages are consistently higher than female wages for both regular and casual work. The difference in male wages over female wages is highest for regular employees (nearly 52.43 per cent). This is followed by casual labour in jobs, other than public works, where the differential is about 48.7 per cent. The wage differential is round 20 per cent in the case of casual labour in public works other than MGNREGS public works. Further, the wages of regular salaried workers (an average of males and females) is the highest (nearly ₹261.92) followed by casual workers in works others than MGNREGS (₹126.3). As regards MGNREGS work, it needs to be pointed out that it is not a job but certain days of supplementary work. The scheme just provides a ‘safety net’ to a very large number of rural families in times of distress (Dreze, 2013). MGNREGS wages are fixed in terms of units of day’s work. It is a piece rate. Hence the daily wage rate is only an average for the units of days worked. The average may turn out to be much less than the per unit minimum if there is crowding of workers, that is, if the number of workers engaged on a block of work is more than the estimated unit days of labour for the work. Therefore, wages for MGNREGS works cannot be compared with regular work or even casual labour work. The male–female difference in wages in MGNREGS public works is around 7.52 per cent (Table 12).
The average daily wage rates are much lower for females as compared to males when both agricultural and non-agricultural occupations are contrasted. One can assume that as the proportion of illiterate women in the rural workforce is very high as compared to men and the share of better educated men in the rural workforce is much higher than women (see Table 10), low female wages indicate that women in rural areas are subject to discrimination, including job-typing, which pushes them into low-paying jobs in both agricultural and non-agricultural sectors. At the all-India level, for all agricultural operations, the average male daily wages are higher than their female counterparts by 30.19 per cent. Across states, the highest wage differential is in Kerala (73.81 per cent) followed by Tamil Nadu (66.02 per cent) and Karnataka (54.29 per cent). The lowest wage differential can be seen in Haryana (5.15 per cent) followed by Manipur (9.02 per cent) and Madhya Pradesh (14.01 per cent). In the case of non-agricultural operations average, male daily wages are higher than their female counterparts by 71.96 per cent. Across states it can be seen that the highest wage differential is in Maharashtra (108.92 per cent) followed closely by Tamil Nadu (108.02 per cent) and Karnataka (95.21 per cent). The lowest wage differential is in Haryana (19.82 per cent) followed by Rajasthan (30.83 per cent) and West Bengal (38.39 per cent). Further, male non-agricultural wages are greater than their agricultural wages by 15.46 per cent. This is true of all states. However, female non-agricultural wages are less than agricultural wages by 12.58 per cent. The former is less than the latter in all states except Bihar, Haryana, Rajasthan and Tamil Nadu (Table 13).
Daily Wages Received by Casual Labour and Regular Wage/Salaried Employees Aged 15–59 Years in Rural Areas (in ₹)
Average Daily Wage Rate Differentials for Agricultural and Non-agricultural Occupations in Rural Areas during September, 2012 across States and Sex (in ₹)
Factors Influencing Rural Female Workforce Participation
The inter-state difference in rural female workforce participation is influenced by various reasons, some of which are cultural, historical and topographical in nature. A regression function was carried out to gauge the impact of a few factors on the rural female workforce across states. The explanatory variables taken were the rural female SC population, rural female ST population, women with college education and vocational training in rural areas as well as the per capita income 6 in rural areas. The variables were taken for ages 15 years and above. The function was estimated in absolute terms and expressed in logarithms to introduce linearity. The results show that the R-square value of the model is 0.99 which means that 99 per cent of the variations in the dependent variable are explained by independent variables. Education and vocational training shows a significant positive relationship at one per cent level of significance with female workforce participation meaning that education has a direct bearing on women’s employment (Figure 6) (Table 14).
As regards the contribution of social groups in affecting rural female workforce, it is observed that a one per cent increase in ST women across states leads to a 1.68 per cent increase in their workforce participation, and the relationship is statistically significant at one per cent levels of significance. In case of SC women, the relationship is also positive though not statistically significant. The SC/ST female workforce participation is high because they are the marginalised and impoverished sections of society who do not face social taboos that disapprove of work, when compared to women of general categories. Surprisingly, a higher rural per capita income does not seem to be attracting more women into the workforce. Per capita income shows a negative relationship, though not statistically significant, with rural female workforce participation, meaning that rising household incomes result in a withdrawal of women from the workforce, and the reason can be attributed to social stigma against women seeking work and also that women seek work only under distress conditions. This phenomenon can be corroborated from the graph which shows that states with higher rural per capita incomes usually have lower female workforce participation. 7
Regression Function of Factors Affecting Rural Female Workforce Participation
Conclusion
The main conclusions that emerge from this study are that despite improvements in the rural economy in recent years, women’s participation in the rural workforce is declining. The share of women workers in agriculture is higher as compared to men, though the share is declining and gradually moving towards non-farm activities. However, non-farm employment in rural areas is still heavily biased towards male workers. A low share of women in the secondary and tertiary sectors and the feminisation of agricultural workforce, with a preponderance of low-skilled women, is not a desirable scenario. Further, even within other sectors most rural women are engaged in manufacturing and construction activities and the movement of women into better formal jobs like professional, scientific and technical activities is weak.
Most female migration in India is within the rural to rural stream and is driven mainly by marriage though latest data shows that rural women are also migrating for educational purposes (though that proportion is considerable low). However, this is a welcome step.
Among social groups, SC/ST women have higher WPR because of their marginalised status and the absence of social norms discouraging them to work as compared to women belonging to ‘general’ categories. States with the higher SC/ST population usually report better female WPR.
In India, the majority of women still do not have ownership or control over land resources and the control is inversely related to land size, which means that women’s control over land decreases as the land holding size increases. This inverse relationship can be due to cultural and social factors that are responsible for less control of women, especially relatively better-off women, on land resources. The southern states fare better in terms of women’s land rights than other states.
Women are still largely self-employed and to some extent employed as casual labour in agriculture. According to NSSO classification, self-employed women in rural areas are mainly working as ‘helpers’ who do not receive proper remuneration. Female self-employment rises when there is an overall stagnation in the farm sector which means that rural women undertake self-employment when casual wage employment shrinks as a result of rural distress. However, in recent years, women’s self-employment is seen to be rising in spite of relatively better growth rates in the farm sector’s gross domestic product. The reason could be that women finding work conditions unsafe or unsuitable prefer it when they are self-employed. Further, constraints imposed by social norms also force women to seek self-employment options instead of wage employment.
Although rural female literacy rates and education levels have been rising over the years it does not seem to positively affect their workforce participation; educated women tend to work in better paid non-agricultural work. It appears that women with higher education and a specialised skills training have better chances of joining the workforce.
Rural wages have been increasing in nominal terms over the years, though female wages have been consistently lower than male wages both in the agriculture and non-agriculture sectors. Lower female wages compared to men indicate discrimination and employment in low paid jobs. Regular salaried wages have been the key driver of higher wages in rural areas.
The rural female WPR is declining possibly because rural women tend to work only during distress conditions, or perhaps they find work conditions unsafe or unsuitable, or social norms are restricting their entry into the job market. All three situations are a matter of grave concern. Women’s autonomy is measured in terms of their access to land and control over its operation. Thus in rural areas, besides employment, women’s access to land and productive resources is critical for improving their social and economic status and levels of empowerment. As regards their employment, the primary focus should be to create jobs that will enable women to join the workforce. Further, education and skills training of women has to be given top priority. Jobs should be created so that they provide a work-life balance, maternity protection, flexible working arrangements and a better access to credit. Ultimately, the goal is not merely to increase female workforce participation, but to provide opportunities for decent work that will, in turn, contribute to the economic empowerment of women.
DESCRIPTIONS OF THE SECTIONS OF NIC 2008
Section A: Agriculture, forestry and fishing
Section B: Mining and quarrying
Section C: Manufacturing
Section D: Electricity, gas, steam and air conditioning supply
Section E: Water supply; sewerage, waste management and remediation activities
Section F: Construction
Section G: Wholesale and retail trade; repair of motor vehicles and motorcycles
Section H: Transportation and storage
Section I: Accommodation and food service activities
Section J: Information and communication
Section K: Financial and insurance activities
Section L: Real estate activities
Section M: Professional, scientific and technical activities
Section N: Administrative and support service activities
Section O: Public administration and defence; compulsory social security
Section P: Education
Section Q: Human health and social work activities
Section R: Arts, entertainment and recreation
Section S: Other service activities
Section T: Activities of households as employers; undifferentiated goods and services producing activities of households for own use
Section U: Activities of extraterritorial organisations and bodies
Footnotes
Notes
Appendix
Share of Rural Female Workers according to Usual Status (PS+SS) by Industry Sections of NIC-2008 for each State/UT (%)
| States | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U |
|
|
76.66 |
|
8.81 | 0.01 | 0.00 | 5.20 | 3.45 | 0.04 | 1.09 | 0.14 | 0.01 | 0.00 | 0.00 | 0.01 | 0.23 | 1.62 | 0.49 | 0.00 | 1.46 | 0.12 | 0.00 |
|
|
90.37 |
|
0.04 | 0.00 | 0.00 | 1.38 | 1.46 | 0.26 | 0.17 | 0.06 | 0.00 | 0.00 | 0.23 | 0.17 | 1.54 | 1.28 | 1.10 | 0.00 | 1.02 | 0.91 | 0.00 |
|
|
79.04 |
|
3.40 | 0.00 | 0.00 | 3.13 | 3.01 | 0.06 | 0.79 | 0.29 | 0.00 | 0.00 | 0.51 | 0.04 | 0.17 | 5.04 | 1.13 | 0.00 | 0.51 | 2.62 | 0.00 |
|
|
76.84 |
|
8.23 | 0.00 | 0.00 | 2.87 | 3.92 | 0.04 | 0.17 | 0.00 | 0.05 | 0.00 | 0.00 | 0.00 | 0.12 | 6.75 | 0.20 | 0.00 | 0.79 | 0.03 | 0.00 |
|
|
90.19 |
|
2.48 | 0.00 | 0.00 | 3.02 | 1.28 | 0.08 | 0.05 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.06 | 0.68 | 1.30 | 0.25 | 0.09 | 0.19 | 0.00 |
|
|
0.00 |
|
0.03 | 0.00 | 0.00 | 0.00 | 37.45 | 0.00 | 0.00 | 22.63 | 0.00 | 0.00 | 0.00 | 0.00 | 8.93 | 28.37 | 1.57 | 0.00 | 0.00 | 1.02 | 0.00 |
|
|
7.07 |
|
27.06 | 0.00 | 0.00 | 6.04 | 14.50 | 0.91 | 0.11 | 0.64 | 10.69 | 0.00 | 6.05 | 0.00 | 1.14 | 4.48 | 0.52 | 0.00 | 14.98 | 5.41 | 0.00 |
|
|
85.55 |
|
5.08 | 0.00 | 0.00 | 2.84 | 1.59 | 0.00 | 0.09 | 0.00 | 0.05 | 0.00 | 0.00 | 0.00 | 0.18 | 2.02 | 0.50 | 0.00 | 0.75 | 0.56 | 0.00 |
|
|
86.02 |
|
3.98 | 0.00 | 0.04 | 4.40 | 0.16 | 0.37 | 0.09 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.14 | 3.26 | 0.69 | 0.00 | 0.86 | 0.00 | 0.00 |
|
|
86.98 |
|
0.94 | 0.28 | 0.01 | 5.36 | 0.82 | 0.20 | 0.06 | 0.01 | 0.14 | 0.00 | 0.03 | 0.00 | 0.60 | 3.95 | 0.24 | 0.00 | 0.38 | 0.02 | 0.00 |
|
|
85.05 |
|
5.79 | 0.00 | 0.00 | 3.51 | 0.23 | 0.00 | 0.08 | 0.01 | 0.02 | 0.00 | 0.00 | 0.00 | 0.20 | 3.06 | 1.03 | 0.00 | 0.60 | 0.41 | 0.00 |
|
|
84.44 |
|
7.00 | 0.00 | 0.00 | 2.55 | 2.41 | 0.01 | 0.29 | 0.00 | 0.08 | 0.00 | 0.00 | 0.00 | 0.16 | 1.29 | 0.31 | 0.00 | 0.38 | 0.10 | 0.00 |
|
|
79.37 |
|
10.00 | 0.04 | 0.00 | 1.14 | 3.45 | 0.15 | 1.07 | 0.03 | 0.34 | 0.00 | 0.02 | 0.00 | 0.98 | 2.40 | 0.41 | 0.00 | 0.20 | 0.19 | 0.00 |
|
|
38.69 |
|
18.01 | 0.00 | 0.11 | 13.04 | 4.75 | 0.62 | 1.31 | 0.31 | 2.28 | 0.01 | 0.24 | 1.55 | 1.19 | 7.96 | 5.92 | 0.04 | 2.17 | 1.69 | 0.00 |
|
|
80.02 |
|
5.10 | 0.00 | 0.00 | 10.36 | 1.99 | 0.01 | 0.05 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.16 | 1.50 | 0.36 | 0.03 | 0.12 | 0.27 | 0.00 |
|
|
89.12 |
|
3.10 | 0.00 | 0.00 | 2.26 | 2.28 | 0.07 | 0.16 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.12 | 2.01 | 0.30 | 0.00 | 0.23 | 0.33 | 0.00 |
|
|
24.12 |
|
17.36 | 0.00 | 0.69 | 40.52 | 9.67 | 0.04 | 1.55 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 1.21 | 3.26 | 0.49 | 0.00 | 0.63 | 0.00 | 0.00 |
|
|
73.62 |
|
1.81 | 0.05 | 0.00 | 3.49 | 7.90 | 0.09 | 3.02 | 0.00 | 0.00 | 0.11 | 0.00 | 0.00 | 2.34 | 4.83 | 1.30 | 0.00 | 0.37 | 0.10 | 0.00 |
|
|
74.69 |
|
0.20 | 0.00 | 0.10 | 13.24 | 6.29 | 0.00 | 0.73 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.85 | 2.27 | 0.56 | 0.00 | 0.44 | 0.00 | 0.00 |
|
|
90.17 |
|
1.24 | 0.02 | 0.00 | 2.57 | 3.19 | 0.00 | 0.25 | 0.15 | 0.00 | 0.00 | 0.00 | 0.00 | 0.75 | 0.88 | 0.79 | 0.00 | 0.00 | 0.00 | 0.00 |
|
|
69.31 |
|
14.50 | 0.00 | 0.00 | 7.77 | 2.07 | 0.57 | 0.26 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.12 | 2.49 | 0.40 | 0.00 | 1.76 | 0.05 | 0.00 |
|
|
75.40 |
|
10.70 | 0.00 | 0.18 | 0.88 | 1.67 | 0.03 | 0.04 | 0.00 | 0.09 | 0.00 | 0.00 | 0.00 | 0.06 | 4.47 | 0.67 | 0.00 | 5.37 | 0.43 | 0.00 |
|
|
77.39 |
|
2.29 | 0.00 | 0.10 | 14.98 | 1.43 | 0.22 | 0.03 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.60 | 1.52 | 0.71 | 0.04 | 0.26 | 0.40 | 0.00 |
|
|
85.64 |
|
1.44 | 0.20 | 0.00 | 3.44 | 3.53 | 0.12 | 0.19 | 0.01 | 0.06 | 0.00 | 0.00 | 0.04 | 0.73 | 3.00 | 0.94 | 0.00 | 0.62 | 0.04 | 0.00 |
|
|
50.59 |
|
16.77 | 0.03 | 0.30 | 22.01 | 3.90 | 0.01 | 1.14 | 0.03 | 0.23 | 0.00 | 0.05 | 0.00 | 0.17 | 2.73 | 0.47 | 0.03 | 0.83 | 0.36 | 0.00 |
|
|
19.12 |
|
10.16 | 0.00 | 0.00 | 60.29 | 1.21 | 0.04 | 0.24 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.19 | 5.68 | 0.51 | 0.00 | 0.00 | 2.54 | 0.00 |
|
|
90.25 |
|
4.77 | 0.03 | 0.00 | 1.03 | 1.27 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.10 | 0.00 | 1.61 | 0.32 | 0.00 | 0.57 | 0.06 | 0.00 |
|
|
82.61 |
|
8.48 | 0.00 | 0.13 | 2.17 | 1.52 | 0.00 | 0.41 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.08 | 2.65 | 0.21 | 0.00 | 1.20 | 0.14 | 0.00 |
|
|
41.69 |
|
42.24 | 0.01 | 0.00 | 2.89 | 2.27 | 0.15 | 0.55 | 0.00 | 0.04 | 0.02 | 0.15 | 0.00 | 0.21 | 4.78 | 1.04 | 0.30 | 0.32 | 3.32 | 0.00 |
|
|
41.61 |
|
0.41 | 1.45 | 0.00 | 10.21 | 9.10 | 2.45 | 2.05 | 0.00 | 3.32 | 0.00 | 0.00 | 0.53 | 3.04 | 16.06 | 5.39 | 0.00 | 0.00 | 4.39 | 0.00 |
|
|
12.19 |
|
14.29 | 0.00 | 0.00 | 0.00 | 5.55 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 5.55 | 0.00 | 7.08 | 15.19 | 0.00 | 0.00 | 40.14 | 0.00 |
|
|
54.14 |
|
29.49 | 0.00 | 0.00 | 5.40 | 0.47 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 9.67 | 0.00 | 0.84 | 0.00 | 0.00 | 0.00 |
|
|
10.34 |
|
29.15 | 0.00 | 0.00 | 0.00 | 0.34 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 60.17 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
|
|
39.73 |
|
11.90 | 0.00 | 0.00 | 10.96 | 0.00 | 0.00 | 0.00 | 0.00 | 14.85 | 0.00 | 0.00 | 0.00 | 0.00 | 20.98 | 1.59 | 0.00 | 0.00 | 0.00 | 0.00 |
|
|
44.94 |
|
16.19 | 0.00 | 0.00 | 13.59 | 9.12 | 0.00 | 7.54 | 0.10 | 3.23 | 0.00 | 0.07 | 0.00 | 0.00 | 4.97 | 0.00 | 0.00 | 0.26 | 0.00 | 0.00 |
|
|
74.94 |
|
9.79 | 0.01 | 0.06 | 6.59 | 2.45 | 0.11 | 0.50 | 0.05 | 0.13 | 0.00 | 0.03 | 0.05 | 0.29 | 2.64 | 0.67 | 0.04 | 0.85 | 0.51 | 0.00 |