The BJP’s Welfare Schemes: Did They Make a Difference in the 2019 Elections?

Abstract

In this article, we use data from the 2019 NES post-poll survey to assess the impact of BJP’s welfare schemes on voting behaviour. We demonstrate that compared to earlier elections, voters are more likely to give credit to the central government as opposed to state governments or local politicians for welfare schemes. This centralization is especially the case for some of the BJP’s new welfare programmes such as Ujjwala and the Jan Dhan Yojana. However, even earlier Congress-era schemes such as the Mahatma Gandhi National Rural Employment Guarantee Scheme and the Awas Yojana are now more associated with the central government. Schemes such as the Public Distribution System (PDS) and Old Age Pensions are still more likely to be associated with state governments. At the all-India level, we find some evidence that voters who received benefits under Ujjwala, Jan Dhan Yojana or Awas Yojana schemes were more likely to vote for the BJP, whereas recipients of pensions or MGNREGA were less likely to support the BJP.

Keywords

Welfare schemes BJP vote NES 2019 centralization of credit programmatic politics

The scale of the BJP’s victory in the 2019 Lok Sabha elections at a time of faltering economic growth, rising agrarian distress, and increasing unemployment has led most observers to assume that voters supported the BJP despite their material interests. The dominance of national security and strong leadership as campaign themes, the more overt deployment of appeals to the majority Hindu community compared to the 2014 campaign, the BJP’s ability to saturate the public sphere with sympathetic media reporting and a massive imbalance in campaign finance have all loomed larger in ex-post analyses than material factors in explaining the vote. However, this was also an election in which welfare schemes—both claims of credit for and promises of—loomed large.

The first term of the Modi administration (2014–2019) saw the launch of several flagship schemes (such as Ujjwala Yojana; Beti Bachao, Beti Padhao; Swachh Bharat; Jan DhanYojana; and Ayushman Bharat) and rebranding of others (Pardikar, ‘Art of Political Branding’). These and existing schemes were also integrated with Aadhaar. PM Narendra Modi and his government relentlessly claimed credit for these initiatives throughout their first term of office. In the run-up to the 2019 elections, the central government also launched a new cash transfer directed at farmers—PM-Kisan—in response to the rising agrarian distress that was perceived to have contributed to the BJP’s defeat in the state elections in late 2018.¹ In return, the pledge to introduce a new basic income scheme, Nyuntam Aay Yojana (NYAY) was the centrepiece of the Congress manifesto. In many states, regional parties also focussed on welfare schemes in their election campaigns.

We know very little about how such existing—and promised—welfare schemes affect voting decisions. It is incontestable that the Indian state continues to function in a discretionary rather than rule-bound fashion when it interacts with citizens. Local intermediaries or brokers play a crucial role for many citizens in enabling citizens to access services or programmes which, in theory, they should be able to access as a right (Auerbach & Thachil, 2018; Bussell, 2019). The substantial role of discretion helps to sustain the notion that India is a ‘patronage democracy’ in which voters make decisions in the expectation of securing future access to state resources (Chandra, 2004). However, a growing literature contests the thesis of a quid pro quo exchange of benefits for votes. If quid pro quo exchanges are happening, brokers need to be able to monitor how voters behave. Yet research shows that brokers struggle to do so (Chhibber & Verma, 2018, p. 120; Schneider, 2016). Urbanization and population growth make it harder for party workers and brokers to discern voters’ actions and make it more efficient for political parties to rely less on party machines and more on programmatic forms of political communication or unmediated appeals to voters by political leaders (Stokes, Dunning, Nazareno, & Brusco, 2013, p. 21).

Furthermore, even if the discretionary disbursement of benefits to party supporters continues, patronage itself is not sufficient to win elections. For this reason, political leaders have become more inclined to adopt what Manor (2010) describes as ‘post-clientelist’ schemes, which are implemented more effectively and are not directed along partisan lines. Studies in several states have pointed to the growing importance of such ‘post-clientelist’ or more ‘programmatic’ policies in explaining election outcomes (Elliott, 2011; Sinha, 2016; Wyatt, 2013).

Contrary to the earlier readings of Indian democracy as a patronage democracy, the NES tradition of empirical studies have not found much evidence of clientelism as a determining factor in how Indians vote. Instead, NES surveys have reported the increasing relevance of governance and performance of the governments as explanatory factors in Indian elections (Verma, 2012; Yadav & Palshikar, 2014). Other studies have also pointed to the emerging significance of issue-based voting, or economic voting in recent elections (Suri, 2009; Vaishnav & Swanson, 2015).Yadav and Palshikar (2014) discussed a gradual shift from identity politics to that of politics of governance since 2004, which coincided with the UPA’s agenda of programmatic politics. At one level, the shift occurred in the context of the waning of social cleavages based on religion and caste in the decade of the 2000s. In the period since then, political parties have been unable to activate these cleavages further and to keep them at the centre stage of politics. Even at the state level, political parties had very little success in building cleavage politics on an enduring basis. Yadav and Palshikar argued that the receding politics of social cleavages forced political parties to adopt ‘catch-all’ policies. There is also a recognition by scholars that Indian elections take place around multiple issue-axes and Indian voters should not be seen as single-issue voters (Sinha, 2016).

Rather than indicating the resilience of clientelism or contingent exchanges of benefits for votes (and vice versa), the prominence of welfare schemes in Indian elections since the 2000s raises the question as to whether voters retrospectively reward governments or political parties for policies that have provided them with a material benefit or whether they weight the potential benefits they could receive from a different party when making voting decisions. Policy-related retrospective voting is unlikely to be the determining factor driving election outcomes. However, it could make a difference in informing voter assessments about the overall performance of governments, especially among certain groups of voters. There is evidence from Latin America, for instance, that the new generation of social policies introduced in countries such as Brazil and Mexico since the early 2000s have had an electoral impact, even if they have not caused long-lasting political realignment (De La O, 2013; Hunter & Power, 2007; Zucco, 2013).

Making this kind of argument is complex in a multi-level polity such as India’s where chains of electoral accountability are opaque. Voters may struggle to identify, which level of government is responsible for which policy. If a voter cannot correctly identify chains of accountability, we might ask whether they can reward/punish the correct party or tier of government. The constitutional set-up further intensifies this problem, where responsibility for some areas of social policy is shared between the centre and the states. Furthermore, even where the central government initiates programmes, or predominantly funds them, state governments—or panchayats in the case of a policy like MGNREGA—may be the primary administrative tier responsible for service delivery. In the past, this has allowed state governments to steal the credit for policies initiated and primarily funded by the central government (Tillin & Pereira, 2017).

In this article, we look at evidence from the NES post-poll survey on welfare and voting in the 2019 Lok Sabha elections. The post-poll survey was conducted in 26 states after polling (12 April to 21 May 2019). A total of 24,236 voters were surveyed in 211 parliamentary seats.² The survey included a series of questions on welfare schemes, some of which have been asked in previous national and state election surveys providing comparative historical data. Using this data, we ask three principal questions: (a) How many people benefit from government welfare programmes? (b) Who do beneficiaries credit for welfare schemes: central government, state government or local officials? (c) Is there any evidence of retrospective voting?

We find first that the welfare schemes introduced by the BJP since 2014 have achieved relatively high levels of coverage—34 per cent of respondents had received gas cylinders under the Ujjwala³ scheme, for instance. Furthermore, some schemes introduced by previous governments have also achieved extensive coverage. The PDS is most notable—nationally an average of 44 per cent of respondents accessed the PDS, but, at the state level, the proportion reached between 80 and 90 per cent of respondents in Andhra Pradesh, Telangana and Odisha—all states ruled by regional parties.

Second, we uncover a pronounced centralization in the attribution of credit for welfare schemes by beneficiaries in 2019 compared to 2014. Compared to earlier elections, there has been a substantial centralization in the likelihood that voters give credit to the central government (as opposed to state governments or local politicians) for welfare schemes. However, there is variation across schemes, with voters more likely to credit state governments with responsibility for agricultural loan waivers, pensions and PDS—all schemes at which state governments have been at the forefront of funding and implementation. The central government receives the lion’s share of credit for other programmes, reflecting the aggressive centralization of credit claiming for welfare programmes by the Narendra Modi government since coming to office in 2014. Interestingly, the central government also received a larger proportion of the credit for the MGNREGA—a UPA-era scheme—than in previous elections. This may suggest that voters are becoming more aware of the chains of electoral accountability for different schemes.

Third, we look at the most difficult question: whether social policy has an impact on the way people vote. Specifically, we look for evidence of whether voters rewarded the BJP for their receipt of welfare schemes. We find evidence in NES 2019 to support the claim that the BJP received some benefit for its new welfare schemes. Beneficiaries of schemes that were more associated with state governments were somewhat less likely to vote for the BJP. However, these findings should be interpreted carefully. Given the number of schemes in operation regionally and nationally, more research is necessary to understand how voters interpret the very complex web of accountability for different government activities. Furthermore, receipt of welfare benefits was unlikely to have been a determining factor in people’s voting decisions. The evidence we discuss here, however, suggests that it may not have been an immaterial part of the connection between voters and the BJP.

The BJP and Welfare

The BJP’s position on welfare is unlike any other political party in the country and on the face of it appears to be founded on a set of contradictory ideas. On the one hand, the party is highly critical of the type of welfare model adopted and practised in India. On the other hand, the party has also not abandoned the idea that governments should provide some form of welfare to the people. Its campaign and mobilization rhetoric beginning with the 2014 elections continuing through the term of the NDA-II and the 2019 campaign itself has revolved around these two precepts.

For the BJP, it is not politically prudent to do away with state-provisioning of welfare, and it has had to find some space in an already crowded market. From two rounds of the State of Democracy in South Asia (SDSA) (De Souza, Palshikar, & Yadav, 2008; Shastri et al., 2017), we know that most people not only in India but across South Asia associate welfare and justice as integral dimensions of democracy. Nearly everyone regardless of education and class linked democracy with some ‘substantial outcome in terms of equality and welfare’. Furthermore, when people were asked about the most essential element of democracy, people underlined welfare, unlike in say the industrialized West, where the procedural dimensions of democracy were prioritized.

Given the large numbers of poor people, and this particular understanding of democracy, welfare and the poor are a strong component on the agenda of almost all political parties. Moving away from the poor and welfare would not only cede space to political opponents, but it would be the ‘equivalent of political suicide’ (Chhibber & Verma, 2018). By 2014, the BJP had learnt from its experience. The Congress, the BJP’s primary challenger, has almost always campaigned on a pro-poor and development agenda. In 2004, when the BJP pitched its tent on the ‘India Shining’ platform, the Congress batted for the underdog. Without debunking the economic reforms, the Congress brought the ‘aam aadmi’ (common man) to the foreground and pushed for a more humane agenda revolving around the idea of inclusiveness (Arora & Kailash, 2014). Consequently, the BJP has put great effort to both signal that it is in the welfare game but more importantly, that it has a slightly different approach compared to the others.⁴

With its broader goal of a Congress-mukt Bharat, the BJP has challenged the Congress on multiple fronts including the welfare dimension. The BJP framed its pro-welfare campaign around the idea that the developmental strategy of the Congress was weak, not pro-poor and that it dulled the aspirations of the people, especially the young. The campaign compared the past (Congress rule) with the current government to create an image that development in real terms is only taking place now. By speaking of welfare like never before, the BJP was going into the Congress terrain. It was a vote-maximizing strategy aimed to squeeze the votes of its opponents.

Redistribution and equalizing opportunities that would allow for a greater social mobility have not been the forte of the BJP. Traditionally, for the party, welfare meant economic investment geared for economic growth and fiscal prudence. The party has tweaked this position slightly to adapt to the competitive environment. To position itself as a welfare agent, the BJP has argued that welfare programmes were being systematically abused and there is a need to direct them to the most needy. Here, the party was implying that the previous distribution mechanisms were faulty and the current government has set it right.

The two points that invariably appeared in the 2019 campaign of the BJP included, first that welfare distribution under the Congress regime was expensive and undeserving sections of society had appropriated the benefits. Second, the Congress favoured particular sections of society and did not treat all citizens equitably. The party consequently argued that the welfare conception and distribution has to be reworked to something that approaches near-universality so that ‘everybody’ benefits from the development. It is around this idea that the party campaign slogan of sab ka sath, sab ka vikas revolves.

It has gone to great lengths to underline the point that the use of technology and direct benefit transfers has helped weed out fake beneficiaries who were receiving various subsidies. This line is very similar to the European right, who too aim to ‘reclaim’ those services from the ‘bureaucrats’ and ‘welfare scroungers’ that ‘abuse them’ at the cost of their ‘rightful owners’: the common man who is falling on hard times (de Koster, Achterberg, & Van der Waal, 2013). The government claimed that when non-existent beneficiaries were removed, public money was being saved and it also showed the corruption free nature of this government.

Under Modi, the use of Aadhaar (biometric identification) to identify beneficiaries, which began under the UPA, has intensified. Aadhaar was intended to promote access to government welfare schemes by providing a unique identification number to every Indian, as well as weeding out ‘fake’ beneficiaries via ‘de-duplication’ of beneficiaries. There is evidence (including from the 2019 NES post-poll survey) that Aadhaar has had the unintended consequences of generating new exclusions as a result of technical errors and over-zealous implementation (see, for instance, Khera, 2015). However, since 2014, Aadhaar has been presented as part of a package of technology-enabled reforms to governance that is helping to eradicate corruption and improve the delivery of government programmes to the poor. The Modi government has also focussed fastidiously on top-down management of programme implementation of its flagship new schemes in priority districts (Aiyar & Tillin, 2019).

During his campaign rallies in 2019, the prime minister made the point that his government was committed to strong and equitable development and is ‘dedicated to poor and all schemes are being formulated to give maximum benefits to this lot’.⁵ In the election campaign of 2019, the BJP thus attempted a re-positioning of the PM as a leader of the poor rather than mere VikasPurush of the 2014 version. The election outcomes suggest that these strategies paid off for the BJP when it consolidated its electoral support in these elections. In this article, we try to understand with the help of our empirical explorations of the NES data, whether and to what extent its new welfarist agenda contributed to the victory of the BJP.

Trends from the NES So Far

The National Election Studies has routinely conducted detailed enquiries on the extent and perceptions of social welfare schemes since 2009. These enquiries have given us three-pointers about the nuanced connection between welfare and vote. First, levels of voter awareness of social welfare schemes have been increasing. In the 2009 Lok Sabha elections, around 40 per cent voters were aware of the Mid Day Meal Scheme of the UPA and 30 per cent voters from the poor, and very poor sections had heard of the National Rural Employment Guarantee Scheme. Three among every four of parents of school-going children were aware of the Mid Day Meal Scheme. At that time, the proportion of beneficiaries of these schemes was much smaller, though not insubstantial (Yadav & Palshikar, 2014, pp. 90–92). As we report below, the extent and awareness of welfare schemes continued to grow over the years and underlined the importance of the distributive dimension of Indian democracy.

Second, there was some evidence of a weak connection between welfare benefits and vote for the ruling party. In 2009 elections, the Congress party had a net advantage of over 15 per cent votes over the BJP among those voters who had heard of the UPA flagship welfare schemes and had benefitted from them. Even among those who had heard of the schemes but did not benefit the Congress party enjoyed around 5 per cent net advantage over the BJP (Yadav & Palshikar, 2014, p. 93). Beneficiaries of NREGA voted more for the Congress party than those who did not benefit. The same was the case with schemes like Mid Day Meal and Old Age Pension. On the basis of his analysis of the 2009 NES data and that of state assembly election studies during the years 2011–2012, Kumar (2013) made two observations. First, the ruling party or alliance generally tended to gain electoral support from welfare scheme beneficiaries. Second, it was state-level ruling parties rather than the central, which were better able to appropriate this support. Thus, the earlier advantage to the Congress among welfare beneficiaries gradually disappeared in the 2014 Lok Sabha elections as regional parties claimed credit for social service delivery. The Congress could still retain a slightly more than its average support among the National Rural Health Mission Scheme (NRHM) and Pension scheme beneficiaries. However, the NREGA beneficiaries preferred the regional parties over the Congress and the BJP in 2014 (data provided by the CSDS [Centre for the Study of Developing Societies] data unit).

The pattern of voters crediting state governments for welfare benefits was also evident in state assembly elections after 2014⁶ (Kumar, Deshpande, & Kailash, forthcoming). Surveys across the cycle of state elections underscored that states continue to matter in understanding the relationship between welfare and vote. However, in terms of electoral advantage to the ruling party, welfare politics had only a moderate impact in these elections. The impact of welfare programmes on election outcomes was mediated by the nature of party competition in which BJP’s entry into the region as a new political player also mattered. Third, the impact of welfare on election outcomes was also affected by the record of implementation. There was a definite advantage to ruling parties among welfare beneficiaries in states where strong welfare regimes existed and where the presence of the BJP was marginal. On the other hand, in states like Uttar Pradesh, rolling out social welfare schemes did not help the incumbent ruling part(ies) win the state elections. Our analysis of the survey data from these studies suggested that the citizens’ level of satisfaction with the state government and more importantly their assessment of the overall performance of the state governments seem to have mattered most in deciding the nature of vote of welfare beneficiaries.

The National Election Studies of 2019 confirmed and strengthened some of these earlier observations. However, they also marked a shift in terms of attribution of credit for social welfare policies. So far, in all our earlier studies, respondents mainly credited the state governments for the overall implementation of the welfare policies. In 2019, on the other hand, as we show below, voters were more likely than in the past to hold the central government responsible for many welfare schemes. Moreover, voters were also able to distinguish more accurately between schemes and have attributed credit to respective state and central agencies accordingly.

Analysis of the 2019 NES Data

We have already noted how the scope of welfare schemes has expanded over the years to cover a large number of beneficiaries. Among the new schemes introduced by the NDA government, Ujjwala and Jan Dhan Yojana had a reasonably decent coverage whereas the schemes for farmers had a moderate reach. As reported in Table 1, the schemes like Awas Yojana or Pension scheme, which were introduced by earlier Congress governments underwent considerable expansion during the past 5 years. Besides, large sections of people availed the benefits of the PDS, one of the oldest social welfare schemes implemented in the country.

Table 1.

Extent of Benefits Under Different Welfare Schemes

Scheme	Percentage of Beneficiaries
Scheme	2019	2014	2009
Housing scheme (Awas Yojana)	21	15	15
MGNREGA	21	20	26
Pension scheme (old age, widows, disabled, etc.)	25	17	21
Public Distribution System	44	–	–
Ujjawala Yojana	34	–	–
Ayushman Bharat/National Rural Health Scheme (2009, 2014)	17	21	14
Jan Dhan Yojana	22	–	–
Agricultural loan Waiver	13	–	18
Income support scheme for farmers	13	–	–

Source: Compiled by the Lokniti, CSDS data unit based on the NES 2009, 2014, and 2019.

An exception to this trend is that of the employment guarantee scheme under MGNREGA. There is a 5 percentage point decrease in the number of beneficiaries under this scheme during the last decade despite the rural employment crisis looming large. In total, 33 per cent of the rural respondents of the NES 2019 feel that, compared to earlier days, fewer jobs are available under the employment guarantee scheme now. It connects with the initial reluctance of the NDA government to take ahead the MGNREGA. Moreover, the scheme has a sizeable coverage of more than 20 per cent of the population. The percentage of beneficiaries of MGNREGA increases only marginally among the poor sections (22%). Table 2 sets out the social profile of beneficiaries. This data suggest relatively wide access to welfare schemes, including a significant level of access among richer groups to welfare schemes. We see considerable variation in the state-wise patterns of implementation of this scheme. In states such as Chhattisgarh, Uttarakhand, Meghalaya, Telangana and West Bengal, more than 40 per cent of the population benefitted from the employment guarantee scheme (Table 3). On the other hand, its coverage remained very limited in BJP-ruled states such as Maharashtra, Gujarat and Uttar Pradesh.

Table 2.

Social Profile of Beneficiaries

	Ujjwala	MGNREGA	Pension	Jan Dhan
Overall	34	21	25	22
Class
Poor	32	33	28	27
Lower	35	34	35	34
Middle	22	22	24	24
Rich	12	11	14	14
Caste
Upper castes	19	17	20	21
Upper OBC	21	20	23	22
Lower OBC	14	12	13	12
Dalits	16	18	14	16
Adivasis	11	12	09	09
Muslims	12	11	12	11
Gender
Male	53	52	52	54
Female	47	48	48	46
Locality
Rural	80	90	74	78
Urban	20	10	26	22

Source: NES, 2019 data made available by CSDS Data Unit.

Table 3.

State-wise Variation in the Implementation of Welfare Schemes (state-wise percentage of beneficiaries)

State Name	Ujjwala	Awas	MGNREGA	Pension	PDS	Jan Dhan	Ayushman Bharat
Andhra	20	13	38	59	88	22	08
Assam	24	12	24	11	09	06	23
Bihar	33	20	09	19	39	20	13
Gujarat	33	16	04	10	31	25	19
Haryana	23	07	08	31	34	15	12
Himachal Pradesh	14	10	35	22	45	12	20
Jammu and Kashmir	27	10	19	14	30	19	04
Karnataka	34	28	07	45	34	25	13
Kerala	45	15	26	43	73	04	16
Madhya Pradesh	62	38	28	34	50	36	22
Maharashtra	20	11	06	03	08	08	04
Meghalaya	04	18	42	08	10	00	15
Odisha	59	20	13	28	91	25	07
Punjab	10	05	12	18	18	06	11
Rajasthan	54	34	36	52	37	50	26
Tamil Nadu	29	44	33	34	46	24	37
Uttar Pradesh	36	16	13	16	46	24	15
West Bengal	26	20	40	11	52	17	19
Jharkhand	61	47	34	32	45	45	43
Chhattisgarh	45	18	49	14	66	19	36
Uttarakhand	32	06	45	38	57	31	22
Telangana	26	14	43	48	81	29	10
All India average	34	21	21	25	44	22	17

Source: NES, 2019 data made available by CSDS Data Unit.

The state-wise variations in the overall implementation of welfare schemes indicate the critical role that state governments continue to play as mediating agencies. As we have argued in our earlier work, the nature of regional welfare regimes is decided by a plethora of political, economic and social factors that shape the local constellations of power (Tillin, Deshpande, & Kailash, 2015). These constellations seem to influence the ways in which different welfare schemes are prioritized by state governments.

In the post-2014 phase, patterns of party competition and the consequent relationship between centre and state(s) appear to be important factors in the selection of schemes at the state level. Thus, the coverage under the popular central scheme Ujjwala is very low in states such as Andhra Pradesh, Punjab, Telangana or West Bengal that are ruled by non-BJP parties. However, these states seem to have taken a more active role in implementing schemes such as MGNREGS, PDS and pension schemes where they retain agency to themselves. The BJP, it seems, was keen to push the central schemes in states under its rule but more than that in states where it wanted to consolidate its dominance. Thus, we see substantial coverage under Ujjwala and Jan Dhan in states like Rajasthan and Madhya Pradesh. The historically strong welfare regimes such as Tamil Nadu, Kerala and Odisha, which had a record of active engagement with welfare politics, have also implemented select central and state-level schemes in a substantive manner. By contrast, BJP governed states such as Maharashtra, Gujarat or Haryana retain their weak to moderate character as regional welfare regimes. In other words, despite the centralization of welfare politics, we see a significant variation in the implementation of welfare programmes at the state level in the past 5 years. This variation is likely to be an important factor in understanding the relationship between welfare and vote.

Despite the state-wise variation in the implementation of different welfare schemes, the NES 2019 depicts a clear trend in terms of attribution of credit to different government agencies. As shown in Table 3, schemes such as Ujjwala, Jan Dhan, Awas Yojana and Ayushman Bharat are identified as central schemes by the voters, whereas PDS and pensions are perceived as state-level schemes. Strikingly, there has also been a centralization of credit attribution for MGNREGA compared to 2014. As shown in Table 4, the number of MGNREGA beneficiaries who credit the central government for the implementation of the scheme has almost doubled between 2014 and 2019. The pension and Awas schemes are equally striking cases. In 2014, less than 20 per cent of the beneficiaries of pension scheme attributed its credit to the central government. There is a more than 10 percentage point rise in it in 2019. There is a marked shift from states to the centre over the last 5 years in case of Awas. If nearly half of its beneficiaries attributed credit to state governments in 2014, the same percentage gives credit to the central government in 2019. These reversals symbolize centralization of not only the credit claiming mechanisms but also that of the overall welfare discourse. At one level, these trends run parallel with the overall changes in the nature of the party system and subsequent changes in the patterns of political competition. Therefore, they have wider implications for the dynamics of welfare politics and the working of Indian federalism. We discuss some of these implications in the concluding section of this article.

Table 4.

Who Gets the Credit for the Implementation of Welfare Schemes? (opinions of beneficiaries of respective schemes)

Scheme	2019		2014
Scheme	Centre	State	Centre	State
Ujjwala	72	14	–	–
MGNREGA	50	32	27	42
Pension	31	52	19	54
PDS	28	57	–	–
Jan Dhan	72	13	–	–
Awas	51	32	22	50
Ayushman Bharat/NRHM (in 2014)	54	30	20	56

Source: NES, 2019 data made available by CSDS Data Unit.

In the remaining section of the paper, we probe further to understand the possible impact of welfare schemes on vote choices. Given the limits of the survey research, this is a somewhat ambitious enquiry. The survey data can provide us with associational patterns but not with causal explanations. Besides, as we have noted earlier, elections in India are woven around multiple issue-axes. Sections of voter citizens develop their perceptions around a grid of issues. In this context, it would be difficult to assign a decisive role to any one factor that influences people’s political choices. Therefore, welfare benefits cannot be seen as the only decisive factor in deciphering voter choices even among the beneficiaries of one or more welfare schemes.

However, as Table 5 suggests, there appear to be some interesting patterns among beneficiaries of different welfare schemes in the 2019 elections. The BJP and allies enjoy a more pronounced support among Ujjwala, Awas Yojana and Jan Dhan beneficiaries. These are all schemes for which voters attribute credit to the central government. However, among the MGNREGA beneficiaries, the BJP gets less than its average support. These beneficiaries do not vote for the Congress though, suggesting that welfare schemes may not create long-lasting associations with the party that introduced them (as studies in other countries have also found—see, for example, Zucco (2013). MGNREGA does not appear to have played a significant role in stemming the attrition of the Congress vote. Instead, the vote of MGNREGA beneficiaries is dispersed among regional parties across states. Despite centralization of the credit attribution in these elections, more than one-third of welfare beneficiaries do not vote for the national parties thus underlining the continued relevance of regional dynamics in welfare politics. Among PDS and pension beneficiaries, regional parties see a slightly higher share of votes. Of course, a proportion of voters receive multiple benefits, and this is not reflected in the table.

Table 5.

How Beneficiaries Voted?

Scheme	Congress	Congress Allies	BJP	BJP Allies	Others
Overall vote share	20	07	37	07	29
Ujjwala	20	06	43	06	25
MGNREGA	20	06	32	05	37
Pension	23	06	34	06	31
PDS	19	06	36	05	34
Jan Dhan	18	06	44	06	26
Awas	21	09	38	08	24
Ayushman Bharat	19	10	40	07	24

Source: NES, 2019 data made available by CSDS Data Unit.

In the wake of the deepening agrarian crisis, farmers’ issues remained at the centre stage of public debate during the last 5 years—especially since 2018, when the farmers rallied to the parliament with their demands. In response, the central government introduced an income support scheme (PM-Kisan) and several state governments introduced agricultural loan waiver schemes. Looking at the farmers’ vote in the 2019 elections, it seems that these schemes may have helped to neutralize farmer discontent. As depicted in Table 6, the BJP enjoys marginally more than its average support among farmers who received PM-Kisan, while the Congress and regional parties saw more support among loan waiver beneficiaries. However, it is impossible to tell from survey data what the direct impact of welfare schemes was on farmers’ perceptions. As Lokniti’s report in the Hindu notes,⁷ for many farmer voters, the overall agenda of development mattered more in these elections rather than the specific issues of their welfare. Despite their massive protests before the elections, nearly 70 per cent farmer voters expressed their satisfaction with the performance of the NDA government at the centre.

Table 6.

How Farmers and Farmer Beneficiaries Voted?

	All Farmers	Farmer Beneficiaries of the Income Support Scheme for Farmers	Farmer Beneficiaries of Agricultural Loan Waiver Scheme for Farmers
Congress	20	16	22
Congress Allies	06	04	03
BJP	39	42	39
BJP Allies	08	08	07
Others	27	30	29

Source: NES, 2019 data made available by CSDS Data Unit.

Within the limitations of the survey data, we finally try to understand the relative (statistical) significance of the welfare-related concerns in deciding the nature of vote in 2019 elections with the help of the regression analysis presented below. Although policy-related retrospective voting is still unlikely to play a determining role in election outcomes, the increased coverage of welfare programs and their centrality in the election campaign make it a relevant exercise.

The dependent variable we use here is the NDA vote. The pattern remains more or less the same if vote for the BJP is used instead. The regression analysis suggests that both the BJP and its allies clearly gain support among the beneficiaries of welfare schemes even when other social and political variables are statistically controlled. There is thus a significant yet nuanced pattern of support for the BJP among welfare beneficiaries. Beneficiaries of centrally sponsored schemes like Ujjwala, Jan Dhan and Ayushman Bharat are more likely to vote for the BJP. However, those of MGNREGA and pension schemes are less likely to vote of the BJP and even its allies. News reports analyzing the election outcomes argued that women in general and women beneficiaries of Ujjwala scheme, in particular, have voted for the BJP.⁸ Our analysis of the NES data complicates this claim. As shown in Table 7, more men than women are likely to support the BJP even when other variables influencing their voting decisions are statistically controlled. At the same time, it is a statistically significant possibility that beneficiaries of Ujjwala are likely to vote for the BJP/NDA despite their gender identities.

Table 7.

Whether Welfare Mattered?

	Dependent Variable NDA Vote
	B	S.E.	Wald	df	Sig.	Exp (B)
Gender	−0.069	0.035	4.001	1	0.045	0.933
Locality (rural–urban)	−0.090	0.041	4.762	1	0.029	0.914
Caste			933.932	5	0.000
Upper castes	0.854	0.097	77.496	1	0.000	2.350
OBCs	0.816	0.095	74.146	1	0.000	2.262
Dalits	0.271	0.101	7.203	1	0.007	1.311
Adivasis	0.451	0.108	17.496	1	0.000	1.570
Muslims	−1.264	0.115	121.282	1	0.000	0.282
Media exposure ( high to low)	0.041	0.016	6.271	1	0.012	1.042
Education	0.027	0.018	2.222	1	0.136	1.027
Ujjwala benefit	0.128	0.039	10.796	1	0.001	1.137
Awas benefit	0.252	0.045	31.012	1	0.000	1.287
MGNREGA benefit	−0.522	0.045	133.613	1	0.000	0.593
Pension benefit	−0.348	0.041	71.465	1	0.000	0.706
Jan Dhan benefit	−0.203	0.044	21.166	1	0.000	1.225
Class	−0.046	0.018	6.539	1	0.011	1.048
Ayushman Bharat	0.236	0.046	26.196	1	0.000	1.267
Satisfaction with central govt.	1.187	0.021	3.127E3	1	0.000	0.305
Constant	1.579	0.167	89.449	1	0.000	4.850

Source: Authors’ own based on data made available by the CSDS data unit.

Note: B: Regression coefficient; SE: standard error; Wald: Wald statistic; df: degrees of freedom; Sig: statistical significance; Exp (B): odds ratio.

The more important takeaways from this table are twofold. The first is about a distinctive connection between welfare and vote in the 2019 elections. The second is about the ability of voters to distinguish between central-and the state-level schemes, which may also have influenced their voting decisions. Thus, if beneficiaries of Ujjwala rewarded the BJP, the beneficiaries of MGNREGA and pension chose not only regional parties but non-BJP regional parties. As a result, both the BJP and its NDA partners enjoy less support among these two groups of beneficiaries.

Conclusion

Using a first-cut analysis of the NES 2019 post-poll survey data, we argue in this article that welfare politics did matter in the 2019 elections. However, it cannot be seen as the only factor or as the only decisive factor that shaped the voting decisions of welfare beneficiaries. At the same time, the data indicates voters were aware of questions of service delivery in the elections this time, held certain expectations from parties and governments, were able to attribute credit to different government agencies for different schemes and, therefore, may have opted for retrospective voting to certain parties.

We argue that, rather than a case of quid pro quo exchange, the welfare connect in the 2019 elections marks a further step towards the expansion of programmatic politics in Indian elections. Given the complex nature of Indian elections, it is a still indiscernible shift that would require careful observation in further research. Similarly, there is every likelihood that the expansion of programmatic politics may get arrested as a result of centralization of the polity, consequent weakening of federalism and possible erosion of the democratic space in Indian politics. While the distribution of material welfare benefits is likely to continue to play an important role in electoral politics, wider conceptions of welfare as a component of social citizenship may come under pressure. Notwithstanding this, the symbolic signi-ficance of the connection between welfare and vote cannot be undermined.

Despite the presence of large majorities of poor, the welfare agenda has remained under-articulated in Indian elections for a long time. This has led to characterization of Indian democracy as a patronage democracy in which welfare claims mainly took the form of clientelist exchanges. In their empirical theorizations on Indian elections and democracy, three generations of scholars associated with the NES have often been argued against these readings. The NES findings, along with many other recent studies of Indian democracy, have suggested a gradual shift in Indian democracy towards programmatic politics leading to expansion of democracy albeit in an untidy manner. Our preliminary exploration of the 2019 NES data contributes to these arguments in two ways. One, we demonstrate that compared to earlier elections, there has been a significant centralization of credit attribution for welfare programmes. Two, we suggest that the BJP and its allies may have benefited (marginally) from new programmes that were clearly attributed to the Centre.

Further research is necessary to better understand how schemes such as Ujjwala benefitted the BJP. Since the scheme remains at an early stage of implementation and many beneficiaries have not yet received more than their initial cooking gas connection, the impact of the scheme may lie more in the realm of offering the promise or potential of future benefits rather than approval of benefits already received. Such programmes may help make BJP promises of future delivery more credible than rival pledges (such as Congress’ basic income manifesto commitment).⁹ In this sense, schemes such as Ujjwala become less about retrospective ‘vote buying’ and more about signalling a particular reputation for future service delivery.

The implications of some of the dynamics sketched in this article for the performance of social welfare programmes will be important to watch. As research on other regions has shown, the centralization of credit claiming for welfare initiatives can alter the incentives of subnational governments when it comes to programme implementation (Niedzwiecki, 2018). Opposition-ruled state governments, such as West Bengal or Delhi, have already sought to make political capital out of impeding central government initiatives or implementing competing schemes, for instance, in the field of health insurance. The future of welfare politics and Centre-state tensions in this field will have important implications for the quality and universalism of public goods provision across India.¹⁰

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 received no financial support for the research, authorship and/or publication of this article.

Notes

References

Acosta

A. M.

, & Tillin

(2019). Negotiating universalism in India and Latin America: Fiscal decentralization, subnational politics and social outcomes. Regional & Federal Studies, 29(2), 115–134.

Aiyar

, & Tillin

(2019, May). The problem: The union and the states. Seminar, 717, 10–13.

Arora

, & Kailash

K. K.

(2014). Strengthening legislative capabilities of the Indian parliament: The national advisory council. In Pai

& Kumar

(Eds.), The Indian parliament: A critical appraisal (pp. 189–230). Hyderabad: Orient BlackSwan.

Auerbach

A. M.

, & Thachil

(2018). How clients select brokers: Competition and choice in India’s slums. American Political Science Review, 112(4), 775–791.

Bussell

(2019). Clients and constituents: Political responsiveness in patronage democracies. Modern South Asia, Oxford, UK and New York, NY: Oxford University Press.

Chandra

(2004). Why ethnic parties succeed: Patronage and ethnic head counts in India. New York, NY: Cambridge University Press.

Chhibber

P. K.

, & Verma

(2018). Ideology and identity: The changing party systems of India. New York, NY: Oxford University Press.

De Koster

, Achterberg

, & Van der Waal

(2013). The new right and the welfare state: The electoral relevance of welfare chauvinism and welfare populism in the Netherlands. International Political Science Review, 34(1), 3–20.

De La O

A. L.

(2013). Do conditional cash transfers affect electoral behavior? Evidence from a randomized experiment in Mexico. American Journal of Political Science, 57(1), 1–14.

10.

de Souza

P. R.

, Palshikar

, & Yadav

(2008). State of democracy in South Asia: A report. New Delhi: Oxford University Press.

11.

Elliott

(2011). Moving from clientelist politics toward a welfare regime: Evidence from the 2009 assembly election in Andhra Pradesh. Commonwealth & Comparative Politics, 49(1), 48–79.

12.

Hindustan Times (2018, December 12). BJP pays price for agrarian distress, employment crisis. Hindustan Times. Retrieved from https://www.hindustantimes.com/assembly-elections/bjp-pays-price-for-agrarian-distress-employment-crisis/story-rZ4JpVPr91M1UEOPR9LBQM.html

13.

Hunter

, & Power

T. J.

(2007). Rewarding Lula: Executive power, social policy, and the Brazilian elections of 2006. Latin American Politics and Society, 49(1), 1–30.

14.

Khera

(2015). UID: From inclusion to exclusion. Seminar, 672, 78–81.

15.

Kumar

(2013, September). Welfare policies of the government and election: Does party in power gain electorally from populist policies? Paper presented at the Comparative State Politics and Public Policy in India workshop, King’s India Institute, King’s College London.

16.

Kumar

, Deshpande

, & Kailash

K.K.

(Unpublished). Inequalities, welfare and democracy: Studies of politics policy interface in Indian states. Report submitted to the ICSSR.

17.

Manor

(2010). What do they know of India who only India know? The uses of comparative politics. Commonwealth & Comparative Politics, 48(4), 505–516.

18.

Niedzwiecki

(2018). Uneven social policies: The politics of subnational variation in Latin America. New York, NY: Cambridge University Press.

19.

Pardikar

(2019). Art of political branding: Why 18 NDA schemes carry ‘Pradhan Mantri’ label. Retrieved from https://www.news18.com/news/india/art-of-political-branding-why-18-nda-schemes-carry-pradhan-mantri-label-2033221.html

20.

Schneider

(2016). Do brokers know their voters? A test of guessability in India (SSRN Scholarly Paper ID 3007407). Rochester, NY: Social Science Research Network. Retrieved from https://papers.ssrn.com/abstract=3007407

21.

Shastri

, Palshikar

, Kumar

, Hachhethu

, Tawfique

M. S.

, Mehboob

A. B.

, & Peiris

(2017). State of democracy in South Asia. Report II. Bengaluru: Lokniti-CSDS, Delhi and Jain University Press.

22.

Sinha

(2016). Why has development become a political issues in Indian politics. Brown Journal of World Affairs, 23, 189–203.

23.

Stokes

S. C.

, Dunning

, Nazareno

, & Brusco

(2013). Brokers, voters, and clientelism: The puzzle of distributive politics. New York, NY: Cambridge University Press.

24.

Suri

K. C.

(2009). The economy and voting in the 15th Lok Sabha elections. Economic and Political Weekly, 44(39), 64–70.

25.

Thachil

(2014). Elite parties, poor voters: How social services win votes in India. Cambridge: Cambridge University Press.

26.

Tillin

, & Pereira

A. W.

(2017). Federalism, multi-level elections and social policy in Brazil and India. Commonwealth & Comparative Politics, 55(3), 328–352.

27.

Tillin

, Deshpande

, & Kailash

K. K.

(2015). Politics of welfare: Comparisons across Indian states. New Delhi: Oxford University Press.

28.

Vaishnav

, & Swanson

(2015). Does good economics make for good politics? Evidence from Indian States. India Review, 14(3), 279–311.

29.

Verma

(2012). What determines electoral outcomes in India? Caste, class, or voters’ satisfaction with government performance? Asian Survey, 52(2), 270–297.

30.

Wyatt

(2013). Combining clientelist and programmatic politics in Tamil Nadu, South India. Commonwealth & Comparative Politics, 51(1), 27–55.

31.

Yadav

, & Palshikar

(2014). Between fortuna and virtu: Explaining congress’ ambiguous victory in 2009. In Palshikar

, Suri

K. C.

, & Yadav

(Eds.), Party competition in Indian states: Electoral politics in post-congress polity (pp. 42–99). New Delhi: Oxford University Press.

32.

Zucco Jr.

(2013). When payouts payoff: Conditional cash transfers and voting behavior in Brazil 2002–2010. American Journal of Political Science, 57(4), 810–822.