Abstract
This study underlines that land is an important variable influencing the accessibility to different types of occupations and the possession of household assets. Inequality in the accessibility to salaried employment can be traced to several other factors such as distribution of land, non-availability of consumer durables and other teaching aids like computers. It also notes that the inequality among SCs and STs in relation to non-SCs and non-STs are systemic and that their initial low physical and human capital base places them perpetually at a low economic status.
Introduction
The people in Rajasthan are socially and economically much diversified. To an extent, geographical division of the largest state in India into eastern and western Rajasthan contributes to the social and cultural diversity of the people and to their history of social and economic developments. Of the total population of about 70 million people in Rajasthan, Scheduled Castes (SCs) and Scheduled Tribes (STs) had a share of 18% and 13%, respectively, in 2011 (Census of India, 2011). In the political and administrative spectrum of Rajasthan, non-SCs and non-STs together wield political power non-proportional to their relative weights in population. It has resulted in unequal accessibility to power centres, possession of assets and social spaces.
In the absence of visible deprivation, inequality would prevail at varying levels across social groups. Inequality refers to disparity in the distribution of income and wealth, which is manifested in relative standards of life of different social groups in the society. A distinction needs to be drawn between inequality and deprivation. Absolute deprivation represents a situation wherein basic necessities for a socially accepted life are denied to an individual or a group, while relative deprivation compares the status of deprivation across individuals and communities. SCs and STs are subjected to both absolute and relative deprivations (Sen, 1981). Inequality emerges mainly from inherited ownership, and it is an inevitable outcome of private property relations under capitalist production relations (Piketty, 2013). Entitlement failures drive to deprivations and eventually to poverty and starvation. Social restrictions in accessing means of production and sale of output in the market have worsened the economic conditions of SCs and STs, which in turn have a bearing on the opportunities for self-employment (Thorat & Sadana, 2009). Although state governments in India have implemented various schemes and programmes for employment and livelihood of SCs and STs, yet wide disparity in social living standards and economic status still exists. Thorat and Madeswaran (2018) attributed the lower economic status of SCs and STs in India to the failure of the state in effectively implementing the state’s programmes and schemes for poverty reduction. Further, state mediation is very vital to stop practices of isolating castes for their economic, civic and religious rights. Relatively low initial resource endowments available with SCs and STs entangle them in the vortex of a vicious circle of social and economic inequality. Deshpande observed that inequality is more prominent in spending on education, food, clothing and landholdings across caste groups in different states in India (Deshpande, 2000). Statutory provisions for shelter, health and education do reduce inequality, but basic amenities alone would not ensure relative social well-being of people (Roy et al., 2004). While privileged caste and class bank on their inherited initial large resource endowments, SCs and STs are deprived of such a capital base. The study underlines that social inequality breeds economic inequality and leaves SCs and STs perpetually in a socially and economically disadvantaged position. It resembles the biblical paraphrase of Mathew effect. 1
Economic inequality has always been a resonating issue and a yardstick to measure the standard of living for different social groups in a geographical entity. Click or tap here to enter text.The nature, pace of growth and geographical spread of inequality in India have aggravated since the onset of trade liberalization in 1991. The nature and sources of inequality are different for urban and rural India. Livestock, farmland and agricultural machinery constitute a miniscule part of asset portfolio of urban population, while those are important assets in rural area (Sarma et al., 2017). As prominence of agriculture and livestock rearing declined over the years, sources of inequality, its nature and content, have changed. A recent study on dairy farmers in Rajasthan has revealed that less than 5% of the rural population depends on dairying as their primary source of income, while more than 25% of female workforce reported dairying as their primary occupation (Mohanakumar & Sen, 2023). As cattle rearing has become less profitable, male workers have moved over to wage labouring and off-farm work. Emergence of Information and Communication Technology (ICT) and digitalization have widened the social and economic inequality in a polarized society. Sources of inequality in a digitalized economy are traced to asymmetric distribution of assets, which, in turn, influences individual characteristics such as skill set, level of education, proficiency in language and other related assets (Tewathia et al., 2020).
Inequality in income and asset holdings by social groups has been sufficiently explored in the Indian context. Analysis of inequality can be examined with respect to the probability of acquiring white collar jobs, which is a manifestation of the availability of economic and social capital. However, inequality in accessibility to opportunities by social groups is one of the areas demanding further exploration. The present study is an attempt to address the gap in the literature in the context of Rajasthan. Given the setting, the study has set out research questions such as: what is the extent of inequality in the distribution of land and other amenities of life, and what are important determinants of unequal access to livelihood options by social groups in rural Rajasthan? The discussion is organized in three sections. Following a brief discussion on data source and survey tools, the first section elaborates inequality in the distribution of assets by social groups. The second section analyses major determinants of inequality by social groups. The third section concludes the findings of the study.
Data Source and Method
The study is based on a primary survey of 4,544 rural households from 17 districts in Rajasthan. The districts where schemes and programmes on employment generation and income augmentation, particularly for women, were implemented by the government during the last 10 years have been selected for the study. For the study, 306 villages, 51 development blocks and 4,544 households have been covered. In the total sample households selected for the study, 14% were general, 19% were Scheduled Caste and 22% belonged to Scheduled Tribe. Rest of them were Other Backward Castes (OBCs) and State Other Backward Castes (SOBCs), which together constituted 45% of the total sample households. The distribution of sample population tallies with the population census by social groups in the state for 2011.
Sample districts together accounted for 41% of the SC population and 72% of the total rural tribal population of Rajasthan. About 18% of the total population and 19% of the total rural population were SCs and 17% of the rural population were STs in Rajasthan (Census of India, 2011). In agriculturally advanced districts such as Sri Ganganagar, the share of SCs in the total population was as high as 38%, whereas in tribal districts such as Dungarpur and Banswara, the relative share of SC population was less than the state average. Among 17 sample districts considered for the study, three districts, namely Bikaner, Churu and Karauli, had a substantial size of SCs (25%). Also, 8 out of 17 districts in the sample districts had a share of STs above 25% in district population (Census of India, 2011).
The primary survey tools captured different types of assets, including land and house; primary and secondary occupations; possession of agricultural equipment such as tractors, threshers and tillers; and consumer durables such as fridge, television and two and four-wheelers. The population proportion possessing assets and employment by social groups have been weighted with the respective share of population by social groups in the districts.
Distribution of Assets and Inequality
The cost of production of labour involves a physical and a cultural component of living (Marx, 1968). The physical cost of living comprises basic amenities required for a social life in a society. Often, such amenities, by their standards, are included in poverty estimation. However, cultural components of living standards or reproduction cost is important for social and economic equality. The reproduction cost of labour is defined as historically evolved and culturally determined social cost of living (Marx, 1968). Individual social status depends on relative living standards, and it is precisely for this reason that Marx argued that workers should be more concerned with the relative wage rather than the absolute wage. For a comparison of the relative living standard of different social groups within and across districts, seven items of consumer durables, namely (a) colour television; (b) fridge; (c) motor cycle; (d) four wheeler; (e) pumpset for agricultural purpose; (f) generator for electricity and (g) computer, are considered. Figure 1 shows the distribution of television, fridge and motor cycle among SCs and STs and non-SCs and non-STs (others). Twenty-eight per cent of rural households from non-SCs and non-STs reported to have possessed television sets. The corresponding proportions for SCs and STs were 6% and 9%, respectively. However, possessing a television set purchased on own income is different from availing it through government schemes. In the case of SCs and STs, certain consumer durables have been made available to them through schemes of the government, and therefore, possession of TV does not necessarily reflect the economic status of households. In the case of refrigerator, 1.5% SCs and 3% STs possessed, it while 12% of non-SCs and non-STs reported to have possessed it. More or less, the same disparity could be observed in the case of motor cycles as well. Figure 2 shows the distribution of pumpset, vehicle (three and four wheelers), computer and generator (used for irrigation purpose). Two per cent of ST households and less than 1% of SC households reported possession of pumpset, while 6% of non-SC and non-ST households possess it. In the case of computer and generator, a negligible percentage of SC and ST households own it, while the percentage of non-SC and non-ST households reporting the possession of computer and generator is higher. The same trend is observed in the case of three/four wheeler, with non-SC and non-ST households having higher share in possession of these assets.
Distribution of Assets by Social Groups.
Asset Holdings by Social Groups.
In the ST-dominant district of Banswara, not even a single ST household reported to have possessed a refrigerator. Less than 0.5% of ST households possessed refrigerator in 7 out of 17 sample districts. Barring Banswara and Dungarpur, the proportion of households possessing refrigerator was much higher among non-SCs and non-STs as compared to SCs and STs (Table 1). Non-availability of electricity is one of the reasons for not possessing refrigerator in ST-dominant districts. It is indicative of a systemic deprivation in SC- and ST-dominant districts. The same trend and pattern could be observed in progressive districts of states like Kerala (Mohanakumar, 2013). It points out to another form of state-mediated deprivation.
Distribution of Households Possessing Refrigerator and Television by Social Group and Sample Districts.
Table 2 shows the possession of two wheeler and four wheeler by sample households. At the outset, a word of caution is requested in the interpretation of the data. The public transport facility, particularly in rural areas in Rajasthan, is rather scarce and it is virtually non-existent in ST-dominant districts. Therefore, own transport is more or less a necessity, and possession of one does not reflect economic well-being of a household. It was found that 30.74% of ST households in ST-dominant districts such as Banswara possess a two wheeler and the same is the case with other ST-dominant districts such as Dungarpur and Udaipur. Labourers have to commute to the nearby township in search of daily wage employment, and own transport is inevitable for them. In ST- and SC-dominant districts, there is little employment opportunity in rural area even during peak agricultural seasons because farmers own a few bighas 2 of land, which is unirrigated and cultivable only once in a year. The terrain is undulated and less productive. For sowing and harvesting, labour is seldom hired in SC- and ST-dominant districts as family labour and neighbouring cultivator households help each other to carry out agricultural operations during peak seasons. Moreover, agricultural land seldom finds buyers even if the price that the land fetches is very low and the market for land is virtually non-existent. The contrasting scenario can be made clear from the possession of four wheelers by social groups in sample districts. The ST households in 7 and SC households in 8 out of 17 sample districts have reported that they did not own a four wheeler.
Distribution of Two Wheeler and Four Wheeler by Social Groups and Districts in Rajasthan (%).
Table 3 shows the distribution of generator and pumpset, which are primarily used for agricultural purposes as well as for drinking water. In several districts in Rajasthan, families in the lower income strata keep generator for electricity and for lifting water from tube wells for irrigation due to frequently disrupted electricity supply. Farmers with sizable agricultural land invariably possess generator and pumpset, and therefore, possession of such assets is essential for agricultural operations. It was found that non-SC and non-ST households keep generator in varying proportions across sample districts. However, in ST-dominant districts, namely Banswara, Dungarpur and Karauli, not even a single household reported to have a generator or a pumpset. The low asset base and the capital available with the SCs and STs are widening the inequality across social groups, and it is the source of income inequality. The observations are in conformity with the findings of other studies (Kijima, 2006; Sarma et al., 2017; Słomczyński & Janicka, 2008; Tewathia et al., 2020; Thorat & Madheswaran, 2018; Zacharias & Vakulabharanam, 2011).
Distribution of Generator and Pump Set by Social Groups and Districts in Rajasthan (%).
Extent of Inequality in Asset Distribution
The degree of inequality in the distribution of four important consumer durables, namely television, fridge, motorcycle and four wheeler, across social groups is estimated by employing standard measures of inequality. Though the Gini coefficient is a widely used measure of inequality, yet it suffers from a major limitation that it does not allow decomposition to trace sources of inequality (World Bank Group, 2005, pp. 95–107). Since SCs and STs encounter different forms of deprivation, inequality measures appear more relevant in this context. For decomposition, the best-known measure is Theil’s Index since it allows estimation of the source of inequality, which could be from within or across groups. Another is the Atkinson’s measure of inequality. Both belong to the family of generalized entropy inequality measures. It needs to be underlined in this context that the inequality measure is not estimated based on expenditure or income measures, but on asset holdings. There exist literature which state that any form of inequality slows down economic growth and general well-being (Sarma et al., 2017). It may be noted that the value of generalized entropy (GE) varies between zero and ∞, with zero representing an egalitarian distribution and a positive value represents the deviation from equal distribution. For Theil Index and Atkinson measure of inequality, the dispersion of inequality is estimated under two assumptions: (a) GE(0), which represents equal weights to all observations in the series, and (b) GE(1), wherein weight is proportionally assigned to observations. Similarly, Atkinson is estimated under Atkinson e = 1 and Atkinson e = 2 (World Bank Group, 2005). 3 Table 4 presents the estimates for inequality in four important items of consumer durables using different measures of inequality.
The following observations can be made from Table 4: (a) there is a positive association between the value of assets and the level of inequality; (b) the proportion of households possessing television set is significantly higher than the proportion of households possessing refrigerator. In other words, inequality is higher in the possession of refrigerator than television set. Inequality measured by GE(1) is 0.311 for four wheeler, which means that the inequality in the possession of four wheeler is higher than that for television sets for all measures of inequality. There is a difference between GE(0) and GE(1). GE(0) represents mean log deviation or equal weights are assigned to values above and below the average, while GE(1) attributes weights to observation above and below the average value, and therefore, the Theil Index of GE(0) and GE(1) gives different values of inequality (World Bank Group, 2005). Inequality measures did not directly indicate the extent of deviation of distribution of assets (consumer durables) between SCs and STs and non-SCs and non-STs, but from the preceding analysis, it can be assessed that higher inequality has been largely contributed by inequality in the possession of consumer durables across social groups.
Inequality in Asset Distribution by Type of Assets.
Determinants of Inequality
In this section, unequal access to different types of employment and its determinants are analysed. Social capital and material conditions of reproduction are systemically determined and are different for different social groups. Possession of productive land is an indicator of material conditions, which is, to a great extent, directly proportional to the caste hierarchy. Possession of productive land with proper documentation and in the prime area of developed land market is relatively low for SCs and STs as compared to non-SCs and non-STs. The community network among non-SCs and non-STs is much stronger and yields more than SCs and STs. The social capital is an aggregate of different types of resources (actual and potential) sourced from a durable network of institutionalized relationships across members of a community. The community network, therefore, provides certain values to its members by which the members access social resources embedded within the network (Bourdieu, 1986). The same is reflected through household consumer expenditure survey. There exist differences in monthly per capita expenditure (MPCE) for different social categories. While the MPCE of ST (rural) in Rajasthan was ₹1,211 against ₹2,119 for others (rural), for SC (rural) it stood at ₹1,389. As per the latest survey conducted in 2022–2023, though there has been an increase in the MPCE for all social categories, the inequality still persists, with SC (rural) reporting MPCE of ₹3,794, ST (rural) ₹3,206, others (rural) ₹5,428 and overall rural MPCE for Rajasthan standing at ₹4,263 (MoSPI, 2024). The theoretical framework of the social capital theory is specified in the study using the logit model in terms of countable economic and social variables such as agricultural land, caste group, type of livelihood (employment), possession of assets and livestock. To represent different dimensions of accessibility to different types of employment, which is a manifestation of various social and economic endowments embedded in Marxian class analysis and social capital theory, logit models with different specifications have been estimated.
Three sets of models were specified to capture major determinants of accessibility to employment and possession of different assets. It may appear as circular reasoning. As the social network of SCs and STs is weaker than that of non-SCs and non-STs, both social and economic conditions work in favour of the latter. The outcome variable in the logit regression represents the effect of the interaction of land and other assets. Primary data on the principal status of employment was collected for three broad types of occupations, namely (a) self-employed in own account enterprises including cultivators; (b) regular and salaried employment; and (c) casual wage labouring. Employment type is specified as a dependent variable in the model and independent variables are: (a) area under cultivation (land in bigha) and (b) social groups (SCs, STs and non-SCs and non-STs). Non-SCs and non-STs include OBCs, SOBCs and general castes. To capture the combined effect of SCs and STs as well as individual effects of SCs and STs on the type of employment, three models were specified; that is, for each type of employment, there are three specifications.
Specification 1: SCs and STs = 1 and otherwise = 0 (combined effect of SC and ST)
Specification 2: SCs = 1 and Otherwise (ST excluded) = 0 (individual effect of SC only)
Specification 3: ST = 1 and Otherwise (SC excluded) = 0 (individual effect of ST only)
In the second set of models, major determinants of consumer durables, namely four wheeler, agricultural equipment (tractor) and possession of livestock, are specified.
For every dependent variable, a similar set of specifications is estimated, namely (a) for SCs and STs combined; (b) for SCs only and (c) for STs only.
The logit model (general specification) takes the following form:
Table 5 gives nine specifications, three specifications for each occupational category. Models serially numbered 1, 2 and 3 present probabilities of SC and ST engagement as a farmer, regular salaried employee and casual labour, respectively. Model 1 shows that there is a positive association between possession of agricultural land and the probability of becoming a farmer. Two important observations emerge from Model 3: (a) There is an inverse association between possession of agricultural land and principal occupation as wage labouring; (b) SCs and STs have a high probability of becoming casual wage labour as compared to non-SCs and non-STs (odds ratio: 2.196). The area under cultivation or size of landholdings is one of the major determinants of self-employment in agriculture or the determinant of own account enterprises. As SCs and STs possess relatively smaller areas for cultivation as compared to non-SCs and non-STs, the probability of SCs and STs earning a livelihood from farming is relatively low and they are left with the option of being employed as wage labours. There exists a negative association between land area under possession/cultivation and salaried employment. It implies that households with a larger area under cultivation still prefer to be self-employed in agriculture rather than being employed on a regular basis in the non-farm sector elsewhere. Models 4, 5 and 6 show the probability of SC households (STs excluded in the model) having the principal occupation as farmer, salaried employment and casual wage labour, respectively. The probability of an SC household becoming casual labour as its principal occupation is double (odds ratio: 2.60) than that of a non-SC household (Model 6). It is rather justifiable because SC households possess relatively less agricultural land and, therefore, are left with fewer other options of livelihood. Model 5 supplements that a household from an SC social group has less probability to become a regular salaried employee and 40% less probability to take up farming as a principal occupation as compared to non-SCs. The probability of working as a daily wage casual labour is negatively associated with agricultural land under possession and the observation appears to be consistent with other studies. The finding justifies that the presence of SCs and STs in wage labouring is more than proportional to their population share in the total. Models 7, 8 and 9 show the probabilities of ST households’ engagement in different categories of employment. The probability of an ST household to become a regular salaried employee is 30% less than that of a non-ST household. An ST household is more likely to become a farmer (odds ratio: 1.28) than a non-ST household. It could be because STs in Rajasthan cultivate small patches of land (more often than not forest land without documents) in remote and undulated locations far away from townships. They are rather forced to grow crops for sustenance and they reproduce in the periphery of the market relations.
Logit Regression Model: Determinants of Type of Employment.
Models 1–5 in Table 6 show the probability of SCs and STs owning different types of consumer durables, capital equipment for agricultural operations and livestock. Model 1 shows the probability of an SC or ST household owning a four wheeler. A non-SC or non-ST household in Rajasthan has more 40% less probability to own a four wheeler than an SC or ST household. In the case of tractor, an SC or ST household is less likely to own a tractor than non-SC or non-ST (odds ratio: 0.78). In the context of agrarian crisis, the number of days of employment available to casual labours had declined substantially while marginal and small farmers encountered crisis of reproduction. Other studies have indicated that farmers do depend more on dairying during the crisis in the crop production sector. However, the logit regression with probability of owning a cow or buffalo or both for SCs and STs is found to be much less as compared to non-SCs and non-STs (Model 3). Since their place of residence is away from town and offers little to no livelihood opportunities, ST households rear animals to supplement their income from small patches of land cultivated.
Logit Regression on Determinants of Consumer Durables, Capital Equipment for Agriculture and Livestock.
Conclusion
Inherited land is one of the important sources of wealth and determines different dimensions of inequality in rural India. The SCs and STs stand at a disadvantageous position as they inherit little from their predecessors and have little to be passed over to the next generation. This underlines a historical social process by which social and economic disadvantages breed into the future generations depriving them of physical and human capital.
Possession of land and other assets is determined by a vicious combination of upper caste and class-dominated economic and social institutions, which very often jointly put up stiff resistance against structural changes in the distribution of assets and production of wealth. Deprivations, social and economic inequality and its myriad forms that SCs and STs encounter in their everyday life are historically rooted. Given the structure of the prevailing social order, an SC or ST household is more likely to become a casual labour than a farmer or regular salaried employee as compared to non-SC and non-ST households. It provides answers to the empirical observation that the proportion of agricultural labours in the total workforce is much higher than their relative share in population.
An important determinant of the choice of occupation is the land under possession. It is explained that there exists inequality in asset distribution and that the inequality in land distribution is one of the major determinants of accessibility to different types of occupations. It is a case of inequality breeding inequality. As accessibility to different types of assets including computers is unequally distributed, it leaves a self-perpetuating biblical Matthew effect on the vulnerable sections.
The observed inequality in the possession of consumer durables, automobiles and land are inextricably linked. The government programmes and schemes, specially designed for the upliftment of the living standard of the rural poor, may be designed and implemented effectively to overcome the disadvantages emerging from the digital world to a great extent. However, land question remains the base of the inequality.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This article is an outcome of a research project funded by the Government of Rajasthan to the Institute of Development Studies, Jaipur (IDSJ), Rajasthan. The work was carried out in IDSJ. The research data for the same can be shared on request.