metadata: authors: 0: author: Bussolo,Maurizio
1: author: Dixit,Akshay Govind
count: India,South Asia
docna: 0: docna: (Perceptions of) Inequality, Demand for
            Redistribution, and Group-Specific Public Goods : A Survey
            Experiment in India
docty: Policy Research Working Paper
theme: Social Safety Nets,Gender,Human Development and Gender,Data Development and Capacity Building,Social Protection,Social Development and Protection,Public Sector Management,Social Insurance and Pensions,Data production, accessibility and use,Social protection delivery systems
abstracts: cdata!: This paper uses data from a survey of
            116,061 households in India to study people&#x2019;s
            beliefs about inequality and demand for redistribution. The
            findings show that a household&#x2019;s beliefs about
            inequality, implied by the perception of their position on
            the income distribution, is negatively correlated with
            support for reducing inequality. This is relevant since
            there are significant differences between where individuals
            believe their household stands and their actual position,
            with the gap between perceived and actual position exceeding
            two deciles on average. Despite these large differences,
            informing individuals of their household&#x2019;s
            position on the income distribution has no discernible
            effect on support for reducing inequality. The paper posits
            that demand for redistribution may be unresponsive to this
            information because it is based on exclusively on
            household&#x2019;s income and does not account for the
            sharing of resources within communities. In communities
            where group-specific public goods, such as religious and
            social goods, are present, class antagonism and
            redistribution are mitigated by community solidarity.
            Households benefit from these goods, and such benefits alter
            the individuals&#x2019; beliefs of inequality.
            Consistent with this prediction, the average individual
            perceives their household as richer in districts with a
            greater supply of religious or social goods. The sharing of
            resources within religious or ethnic groups can shape
            perceptions of the income distribution and reduce support
            for redistribution within these groups, and thus requires
            serious consideration in studies of inequality.
display_title: (Perceptions of) Inequality, Demand
            for Redistribution, and Group-Specific Public Goods : A
            Survey Experiment in India
listing_relative_url: /research/2023/06/34103057/perceptions-inequality-demand-redistribution-group-specific-public-goods-survey-experiment-india
topicv3: Poverty Measurement and Analysis m1326941 707,Social Development m1327660 134,Behavioral Initiatives for Poverty
            Reduction and Equity m1503826 3746,Markets and Institutions for Poverty
            Reduction and Shared Prosperity m1503847 3781,Income Inequality m1503891 2668
publishtoextweb_dt: 2023-06-27T00:00:00Z
dois: 10.1596/1813-9450-10505
author_keys: 0: author_key: 669228
1: author_key: 1944355
model_extractions: Policy Research Working Paper 10505 (Perceptions of) Inequality, Demand for Redistribution, and Group-Specific Public Goods A Survey Experiment in India _Maurizio Bussolo Akshay Dixit_ South Asia Region Office of the Chief Economist June 2023
Policy Research Working Paper 10505

# **Abstract**

This paper uses data from a survey of 116,061 households in India to study people’s beliefs about inequality and demand for redistribution. The findings show that a household’s beliefs about inequality, implied by the perception of their position on the income distribution, is negatively correlated with support for reducing inequality. This is relevant since there are significant differences between where individuals believe their household stands and their actual position, with the gap between perceived and actual position exceeding two deciles on average. Despite these large differences, informing individuals of their household’s position on the income distribution has no discernible effect on support for reducing inequality. The paper posits that demand for redistribution may be unresponsive to this information because it is based on exclusively on household’s income and does not account for the sharing of resources within communities. In communities where group-specific public goods, such as religious and social goods, are present, class antagonism and redistribution are mitigated by community solidarity. Households benefit from these goods, and such benefits alter the individuals’ beliefs of inequality. Consistent with this prediction, the average individual perceives their household as richer in districts with a greater supply of religious or social goods. The sharing of resources within religious or ethnic groups can shape perceptions of the income distribution and reduce support for redistribution within these groups, and thus requires serious consideration in studies of inequality.

This paper is a product of the Office of the Chief Economist, South Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mbussolo@worldbank.org and at akshay_dixit@g.harvard.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **(Perceptions of) Inequality, Demand for Redistribution, and Group-Specific Public**

**Goods: A Survey Experiment in India**

Maurizio Bussolo<sup>1</sup> Akshay Dixit<sup>2</sup> JEL Classification: D31, D63, H24, H41, I30, Z13 Keywords: Community; Public goods; Inequality; Distribution; Biased Perceptions.

**Acknowledgments:** We thank Ravi Kanbur for encouraging us to write this paper, participants at the Comparative Politics workshop at Harvard University for helpful comments, and Nayantara Sarma for her active contributions to the research. We are grateful to Mahesh Vyas and Kaushik Krishnan for fielding questions on inequality and redistribution as a part of the Consumer Pyramids Household Survey (CPHS) in July-August 2021, and to the India Country Management Unit for their useful comments.

> 1 The World Bank, mbussolo@worldbak.org

> 2 Harvard University, <u>akshay_dixit@g.harvard.edu</u>
# **1. Introduction**

How does an individual’s perception of their position on the income distribution influence their beliefs about inequality and their demand for redistribution? What shapes this perception of one’s relative position in the first place? A growing literature examines these questions (Alesina, Glaeser, and Sacerdote 2001; Alesina, Stantcheva, and Teso 2018; Benabou and Ok 2001; Benabou and Tirole 2006; Bussolo, Ferrer-i-Carbonell, Giolbas and Torre 2021; Iversen and Soskice 2020; Mo and Conn 2018). However, existing research has studied them mainly in high income countries. India remains surprisingly understudied, considering that it is a populous democracy that harbors a deeply unequal society.

We present results from the first nationwide study of perceptions of the income distribution in India. Our data comes from a survey of 116,061 households, spanning all major states of India. We examine people’s beliefs about which decile their household occupies on the income distribution, and compare this to the household’s actual position based on income data collected on a monthly basis over nearly two years. We find that the difference between perceived and income-based decile in India is large, exceeding two deciles on average. Moreover, over 70% of the sample perceive themselves as poorer than they are based on income. While the presence of misperceptions has been widely documented across contexts (Cansunar 2021; Cruces, Perez-Truglia, and Tetaz 2013; Gimpelson and Treisman 2018; Hoy and Mager 2020), the magnitude we observe is striking, as is the widespread underestimation of one’s position.

We find that household nominal income (the _objective_ position of the household in the income distribution) does not predict support for reducing inequality in India. Rather, where people believe their household stands on the income distribution (the _subjective_ perception of the position) is a significant predictor of the belief that the government should narrow the gap between the rich and the poor. Given this finding and the highlighted large differences between 2
perceptions and actual positions in the income distribution among Indians, we tested whether demands for redistribution change when people are informed of their actual household’s position on the nominal income distribution. In an experiment embedded in the survey, a randomly selected set of households were informed about their position, and how this differed from their perception. In contrast to standard models of redistribution, such as those derived from Meltzer and Richard’s (1981) model, we find that informing individuals that they were poorer than they thought had no average effect on support for reducing inequality.<sup>3</sup> Following Dasgupta and Kanbur (2007), we explore a novel reason for why the average household did not respond as expected to information about their position on the distribution of incomes—such information is related to the monetary (or nominal) income of the household, as measured by the survey, but it ignores the non-monetary benefits of group affiliation.<sup>4</sup> Dasgupta and Kanbur (2007) argue that “belonging to a [religious, ethnic, linguistic or regional] group often seems to connote the existence of something beneficial and common (i.e. equally available) to all members, but from the benefits of which non-members are excluded.” [p.1817] They posit that the cohesion within the group is reinforced by sharing some unique extra-economic characteristic and by accessing goods that are non-rival for members of the group, but not available to non-members. Such goods with these simultaneous sharing and exclusion attributes are described by economists as group or community-specific public goods.

In this paper, we consider religious and social goods – such as the conduct of religious ceremonies and celebrations, community kitchens, the maintenance of places of worship

> 3 In the basic Meltzer and Richard (1981) framework, a simple redistribution scheme is funded by taxes on incomes above a certain threshold and, if people _are_ above that threshold, they will not support this scheme as they will not benefit from it. When perceptions are incorporated in such a model what matters is whether people _believe_ or not that they are above the threshold, not their actual position. This is the reason why correcting with a treatment information the overestimation of people’s position in the distribution should lead to more support for redistribution. Note, however, that individuals may have other motives, in addition to self-interest, to support redistribution (see Alesina and Giuliano, 2009 for a review). With additional motives, the relationship between misperception and its correction and support for redistribution may be more complex.

> 4 See also, for a similar argument Akerlof, G. A., & Kranton, R. E. (2000).

3
specific to many communities in India – a prime example of group-specific public goods. These goods are often provided through voluntary contributions from community members for the benefit of their particular religious, linguistic, or ethnic group. We argue that in the perceptions of their economic standing, individuals assess the benefits they derive from these groupspecific public goods. Hence, household nominal income alone is an inaccurate barometer for an individual when forming their beliefs about economic inequality and their demands for redistribution.

As the local (within community) supply of religious and social goods increases, do households feel richer on average? Using data on expenditures on social and religious obligations as a proxy for the district-level supply of social and religious goods, we find that as district-level spending on social and religious obligations increases, the perceived household decile rises significantly on average. This result remains valid even after controlling for household income and household spending on religious and social obligations, along with other covariates. The magnitude of the relationship is substantial. Moving from a district below the median in terms of spending on religious and social goods to a district above the median is comparable to the change in perceived decile that would result if the household’s income-based position rose by one decile.

In sum, the benefits from these group-specific public goods are included in the perceptions of relative economic standing, and therefore these perceptions – rather than the position in the distribution of nominal incomes – are what matters for demands for redistribution. In a community with widespread community-specific public goods, inequality gauged solely on the distribution of nominal incomes is not expected to motivate demands for redistribution and providing information about the correct position in the distribution of _nominal_ incomes does not necessarily change the subjective perceptions of economic standing. Thus, such informational intervention is not expected to change demands for redistribution.

4
The effects of information about the income distribution on redistributive preferences continue to be debated. In a study in Buenos Aires, Cruces, Perez-Truglia and Tetaz (2013) found that households who were informed that they were poorer than they thought responded by increasing their support for redistribution, much like standard economic reasoning suggests. However, in another study, people who were informed of their relative poverty responded by _reducing_ their support for redistribution (Hoy and Mager 2020). Findings from other studies appear to be similarly mixed (Fehr, Mollerstrom, and Perez-Truglia 2022; Karadja, Mollerstrom, and Seim 2016; Kuziemko et al. 2015; Nair 2018). To this debate, we contribute evidence from the first large-scale survey of beliefs about inequality from India.

In contributing descriptive evidence of beliefs about the income distribution and inequality from a sample spanning all major states, religions and caste groups, we add to the research on distributional concerns and the political salience of income inequalities in India (Gaikwad, Hanson, and Tóth 2019; Jaffrelot 2015, 2016; Kohli 2012; Suryanarayan 2019; Thachil 2014; Thachil and Herring 2008). Further, our findings join a nascent literature in questioning how standard political economy models have been applied to the study of redistributive preferences in developing countries (Holland 2018; Kasara and Suryanarayan 2020; Thachil 2014). We emphasize the need for scholars to take the role of group-specific public goods, and the implicit sharing of resources within communities, seriously when examining beliefs about inequality.

# **2. Research Design and Data**

Our analysis is based on data from the Consumer Pyramids Household Survey (CPHS), conducted every four months with a panel of 175,000 households by the Centre for Monitoring the Indian Economy. The CPHS collects monthly data on household income, expenses, and assets, among other economic indicators. We computed the mean income reported by 5
households in CPHS over 23 months from January 2019 to November 2020. These mean incomes were then used to divide the income distribution into ten “objective” income deciles, and each household was categorized in one of these deciles. The mean and standard deviation of monthly income corresponding to each decile, and the number of households interviewed by decile, is given in supplementary Table S7 and Figure S9.

In the June-August 2021 wave of the CPHS, an additional module on inequality was administered to the panel. In this round of the CPHS, interviews were successfully completed with 116,061 households, which comprise the sample for our analysis.<sup>5</sup> Half of these households were randomly assigned to the treatment group, and the other half to a control group. This randomization was stratified by state and whether the household was in a rural area. We compare the treatment and control groups on a set of observable characteristics and find no discernible difference between the groups (see supplementary table S4).

The module on inequality began by eliciting respondents’ beliefs about their position on the income distribution, _“Suppose we divide the households of India into 10 equal parts, where the poorest households are in the first part and the richest households are in the last part. See this bar_ [respondents were shown a long rectangle composed of 10 equally sized blocks] _. The first box contains the poorest households. The second box contains the next poorest households. The last box contains the richest households. Which box do you think your household would fall into?”._ Following this question, respondents in the treatment group were informed if their estimates coincided with those of the research team. Respondents were told, _“Based on your answers, you belong to Group_ [X] _. In reality, you belong to Group_ [Y] _. Hence, you are poorer than what you thought / richer than what you thought / correct.”_ The bias in their perceptions was thus explicitly pointed out to respondents in the treatment group. This

> 5 Since interviews were not completed with a significant fraction of the CPHS sample, this sample on which our analysis is based is not nationally representative. More generally, the representativeness of the CPHS sample has been debated by scholars and analysts—a limitation that we acknowledge.

6
results in three treatment subgroups—those who overestimated their household’s position on the income distribution, those who underestimated their household’s position, and those for whom their prior was confirmed. Note that households that responded to the inequality module had previously been interviewed for the CPHS several times. Hence, they were familiar with the scope and credibility of the survey.

After the treatment, the module collected information on beliefs about inequality. Respondents were asked, _“There can be a big gap between the rich and the poor in the country. Do you think this gap is a problem for society?_ ”, with responses coded yes or no. They were also asked, _“Do you think the government should do something to reduce this gap between the rich and the poor?”,_ with responses coded yes or no.<sup>6</sup> These questions mirror the survey-based measures of beliefs about inequality that have been extensively used by scholars (Alesina, Stantcheva, and Teso 2018; Cruces, Perez-Truglia, and Tetaz 2013; Hoy and Mager 2020; Kuziemko et al. 2015).

We use Equation (1) to estimate the average effect of the treatments on responses to these two questions. We estimate this average effect separately for the three treatment subgroups mentioned above. As a robustness check, we also estimate a version of Equation (1) that excludes all controls.

that excludes all controls. (1) i 0 1T T i 2 i 3 T i i ii ii ii ii<sup>+ XX</sup> ii<sup>γγ+ εε</sup> ii YY = ββ + ββ TT + ββ TTRRT RR + ββ SST Here, i is the outcome for respondent _i_ in district _j_ in state _k_ ; T ii ii<sup>is a vector of binary</sup> variables indicating the respondent’s state; YY i is a binary variable that equals one if the SST ii household was in a rural area; i includes controls for religion, caste and household size; and TTRRT RR ii T T i denotes treatment assignment, with XX 1 being the quantity of interest. ii TT ββ

> 6 The full set of questions is in the supplementary materials.

7
# **3. Descriptive and Experimental Findings**

We divide this section into three parts. First, we document differences between perceived decile (where individuals believe their household stands on the income distribution), and objective decile (the household’s position on the income distribution based on income data from 2019-20). Next, we explore descriptive trends in support for reducing inequality in India, and explore the extent to which perceived and objective income deciles are correlated with support for reducing inequality. Finally, we test if information on the household’s objective decile has any causal effect on support for reducing inequality.

# **3.1. Perceptions of household position in the income distribution**

In Table 1, we list the average difference between perceived decile and objective decile in Column (4), the proportion of households whose perceived decile exceeded their objective decile in Column (5), and the proportion whose perceived decile was lower their objective decile in Column (7). In other words, Column (5) refers to people who perceived their households as richer than they were based on income, whereas Column (7) refers to people who perceived their households as poorer.

Strikingly, over 70% of the sample perceived themselves to be poorer than their incomes would suggest. This is much higher compared to what other studies have found. For instance, Hoy and Mager (2020) found that less than 10% of their online sample from India underestimated their position. A household survey in Buenos Aires found that 55% of the sample underestimated their position (Cruces, Perez-Truglia, and Tetaz 2013). Surveys from highincome countries have found that most people think they are around the middle of the national income distribution, with households below the median typically overestimating their position (Gimpelson and Treisman 2018).

8
|**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|**(6)**|**(7)**|**(8)**|
|---|---|---|---|---|---|---|---|
|**Quintiles**<br>**of**<br>**income**|**Average**<br>**objective**<br>**decile**|**Average**<br>**perceived**<br>**decile**|**Mean**<br>**bias**|**Proportion**<br>**with positive**<br>**bias**|**Average**<br>**positive**<br>**bias**|**Proportion**<br>**with**<br>**negative bias**|**Average**<br>**negative**<br>**bias**|
|Lowest|1.502|2.717|1.215|0.658|1.948|0.067|-1.000|
|Second|3.529|3.273|-0.256|0.287|1.752|0.474|-1.600|
|Third|5.503|3.752|-1.751|0.108|1.559|0.770|-2.494|
|Fourth|7.525|4.165|-3.361|0.030|1.332|0.919|-3.702|
|Highest|9.545|5.219|-4.327|0.005|1.000|0.964|-4.495|
|**Overall**<br>**(N=116,061)**|**6.147**|**4.020**|**-2.136**|**0.172**|**1.813**|**0.705**|**-3.472**|

Notes: “Bias” refers to the difference between perceived and objective decile. Positive bias means perceived decile exceeded objective decile, i.e., the respondent overestimated their position because they perceived their household as higher up on the income distribution than it was based on income data. Negative bias means perceived decile was lower than objective decile, i.e., the respondent perceived their household as lower down on the income distribution than it was.

_Table 1. Objective income decile, perceived decile, and bias by quintile of objective income_ In the supplementary materials (Tables S1-S3), we present the bias in perceived income decile by caste category and religion, respectively. Across religious and caste groups, most households underestimate their position. The implication is that a relatively small fraction of our sample could be told, when undergoing the information treatment of our experiment, that they were poorer than they thought, and only this fraction could thus feel compelled to demand greater equality.

# **3.2. Support for redistribution**

In Figure 1, we display the fraction of respondents who agree with the statement “The government should narrow the gap between the rich and the poor”. The upper panel of Figure 1 aggregates responses by objective income decile, with 1 being the lowest and 10 the highest. Overall, support for reducing inequality is prevalent and strikingly uniform across income deciles. Supplementary figures S1 and S2 display the uniformly high support for reducing inequality across caste categories and religious groups. We find greater variation by state, as shown in Figure S3, though most respondents support redistribution in all states.

9
# Govt should reduce gap between rich and poor

<!-- Start of picture text --> Objective decile<br><!-- End of picture text --> <!-- Start of picture text --> 1<br>2<br>3<br>4<br>5<br>6<br>7<br>8<br>9<br>10<br>0 2 4 6 8 1<br>Perceived decile<br>1<br>2<br>3<br>4<br>5<br>6<br>7<br>8<br>9<br>10<br>0 2 4 6 8 1<br>Note: Control group observations, N=58,112<br><!-- End of picture text -->
<!-- Start of picture text --> Gap b/w rich and poor is a problem<br><!-- End of picture text --> <!-- Start of picture text --> Perceived > Objective decile ——<br>Perceived = Objective decile ae<br>Perceived < Objective decile —4—<br>—-—— Sp pt oi<br>-.08 -.06 -.04 -.02 0 .02 04 .06 .08<br>Effect Size (Percentage points)<br><!-- End of picture text --> Notes: Displaying 95% confidence intervals Positive bias: Perceived decile > Objective decile Negative bias: Perceived decile < Objective decile
<!-- Start of picture text --> Govt should reduce gap b/w rich and poor<br>Perceived > Objective decile ——<br>Perceived = Objective decile —++_<br>Perceived < Objective decile —<br>_<br>-.08 -.06 -.04 -.02 0 .02 .04 .06 .08<br>Effect Size (Percentage points)<br>Notes: Displaying 95% confidence intervals<br>Positive bias: Perceived decile > Objective decile<br>Negative bias: Perceived decile < Objective decile<br><!-- End of picture text -->
Existing work has explored a number of reasons why beliefs about inequality may not accord with the predictions of standard models of redistribution, including beliefs about the role of government (Alesina, Stantcheva, and Teso 2018), the scope for upward mobility (Benabou and Ok 2001; Benabou and Tirole 2006), and skepticism about state capacity (Holland 2018). In the next section, we explore a novel possibility, building on Dasgupta and Kanbur (2007).

# **4. Religious and Social Goods, and Perceived Income Decile**

Studies on perceptions of the income distribution often assume that relative household income is the sole parameter of interest for assessing a household’s class interests. Dasgupta and Kanbur (2007) argue this assumption is non-trivial in contexts with widespread provision of religious or social goods within communities. Examples of social and religious goods include religious ceremonies and festivals, community kitchens, and cultural or literary production within specific ethnic traditions. These goods are community-specific, in that they are meant to benefit members of a specific ethnic or religious group and voluntarily supplied by members of the same group. Such goods may carry an intrinsic valuable to group members, fostering what Dasgupta and Kanbur (2007) term “non-monetary dependencies” among group members. To the extent that the provision of community-specific goods affects perceptions of relative income, standard income-based measures of a household’s position are likely to be misleading. Households may be less likely to respond to information on the income distribution based solely on household income, simply because such information ignores the sharing of resources that may be occurring locally within communities in the form of religious and social goods, and the value that individuals place on these goods.

We test this argument by examining the correlation between perceived household decile and the supply of religious and social goods. Specifically, we explore a prediction that follows 13
from Dasgupta and Kanbur (2007): Conditional on household income, as the supply of religious and social goods increases, perceived household decile increases. A precise test is made difficult by the lack of fine-grained geographic data on the supply of group-specific public goods. We utilize data on household expenditures on social and religious obligations. In the CPHS, spending on “religious obligations” includes the expenditure by a household during a month towards religious ceremonies, donations to places of worship, payments to religious leaders, and contributions towards religious events. Spending on “social obligations” refers to expenditures on religious ceremonies, gifts, weddings, funerals, social causes and events, and contributions to creation of local public conveniences. We sum all household expenditures on social and religious obligations in a district and use this as a proxy for the supply of social and religious goods in the district. Approximately half the sample across economic strata reports expenditures on social and religious obligations, and the amount of spending increases with household income (see Section F of the supplementary materials).

Using Equation (2), we explore whether district-level spending on these goods is correlated with perceived household income decile. Here, i ii<sup>refers to the perceived</sup> income decile of household _i_ in district _j_ in state _k_ . i refers to the district-level mean PPT household expenditure on social and religious obligations in district TT _j_ in state _k,_ with 1 being the quantity of interest. Our estimate of 1 is conditional on i , household _i_ ’s own spending ππ ii on religious and social goods, as well asππO i , the household’s decile based on income data. HH ii Standard errors i are clustered at the district level. To ensure that all districts are weighed OO ii equally in our analysis, each observation (i.e., household) is weighted by the inverse of the ηη district sample size in the CPHS. This guards against the possibility that our estimates are driven by districts with a larger sample. Note that expenditure data is missing for 16,268 households in the June-August 2021 round of the CPHS. These missing values are spread evenly across income deciles as shown in Table S6, distributed across all states, religions and 14
In Table 2, we present the correlation between district-level spending on social and religious obligations and perceived household decile. The estimates in Column (2) show that as mean spending on religious and social obligation in the district rises, household perceived decile also rises, conditional on the household’s objective decile. Since the estimate is conditional on the household’s own spending on religious and social obligations, it reflects the relationship between perceived decile and a greater supply of religious and social goods from other households in the district. Overall, the evidence is consistent with the interpretation that households perceive themselves as richer in districts with a greater supply of religious and social goods. As a robustness check, shown in Table S6, we estimate Equation (2) dropping all districts that have a sample size of less than 10 in the CPHS and find virtually identical results.

||(1)||(2)|
|---|---|---|---|
||Perceived<br>decile|HH|Perceived<br>HH<br>decile|
|District: Mean HH spendingon religious/social obligations|||0.000819**|
||||(0.000396)|
|Objective HH decile|0.239***||0.238***|
||(0.0119)||(0.0118)|
|Proportion of HH spendingon religious/social obligations|2.455*||-0.118|
||(1.417)||(0.862)|
|Observations|97,439||97,439|

Notes: All specifications include controls for state, religion, caste, and household size. The unit of analysis is the household, and all observations were weighted by the inverse of the district sample size in the CPHS. Robust standard errors clustered at the district level in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

_Table 2. Supply of social/religious goods and perceived household decile_ 15
<!-- Start of picture text --> 6<br>25<br>£<br>a<br>o<br>§<br>=4<br>8<br>£<br>3<br>2>3 socialHigh supply goods of +[> > —*——*— DistrictDistrict withwith abovebelow medianmedian supplysupply<br>é -<br>co) 2 Moving up one<br>= income decile<br>=<br>o<br>Qa<br>©<br>a .1<br>0<br>rrssrs rs rs es a |<br>1 2 3 4 5 6 7 8 9 10<br>Objective household decile<br><!-- End of picture text -->
This vertical distance, between the blue and the orange lines in Figure 4, is the magnitude of the correlation we are focusing on. And this distance is (almost) equivalent to moving from decile 5 to decile 4 on the blue line. In other words, the loss of income experienced by moving down one decile is how much is ‘worth’, in monetary terms, the loss of non-monetary benefits incurred by moving from a high to a low spending district. They are worth the same because, in this context, both have the same impact on the change in the perception of being poor.<sup>7</sup> Some caveats are in order. A district-level measure is far from granular given the size of the average district in India. Since the CPHS lumps all social or religious expenditures, the proxy measure does not allow us to describe the specific community-level goods to which households may have contributed, nor does it allow us to distinguish contributions to community-level goods from spending on individual-specific goods. Consequently, our analysis is more exploratory than confirmatory, and the estimate in Column (2) of Table 2 is best regarded as a lower-bound of the relationship between the supply of community-level goods and perceptions of relative income.

# **5. Discussion**

We have documented findings from the first large-scale survey of beliefs about inequality in India, noting the importance of perceptions of relative income in shaping support for reducing inequality. Despite sizeable differences between where people believe their household stands on the income distribution versus its actual position, the average respondent’s support for reducing inequality remained unresponsive to information on their household’s position. Building on Dasgupta and Kanbur (2007), we argue that households may be less likely to respond to information on the income distribution based solely on household income, simply

> 7 In fact, as shown in the figure, the two vertical distances, the one linked to moving down one decile and the other of switching districts, are not exactly the same, but for the sake of the argument the main text dismisses this difference.

17
because such information ignores the sharing of resources that may be occurring locally within communities in the form of religious and social goods. Indeed, we find that the district-level supply of religious and social goods is positively correlated with individual beliefs about their household’s position on the income distribution.

Does the supply of these goods represent a transfer from the rich to the poor? This is a question for future work, ideally with finer data on who derives benefits from community-level goods. We do note that richer households spend more on religious and social obligations, whereas poorer households spend a larger _fraction_ of their income on these obligations, as shown in Section F of the supplementary materials. Thus, the distributional effects of community-level public goods are not straightforward and merit further study.

To our knowledge, our findings are the first to suggest an empirical link between community-specific public goods and beliefs about the income distribution. Future research should focus on overcoming the spatial limitations of our data by focusing on the village or neighborhood rather than the district. The challenge of establishing a causal relationship also remains. Examining the precise mechanisms at play is another avenue for further work.

Group-specific mechanisms of resource sharing are prevalent across the developing world (De Weerdt and Fafchamps 2011; Di Falco et al. 2018; Di Tella and MacCulloch 2002; Fafchamps 2011; Mobarak and Rosenzweig 2013; Olken and Singhal 2011). Hence, our findings have wider implications for the study of redistributive preferences in developing countries. We advance one potential reason why beliefs about inequality may respond in counterintuitive ways to information about the income distribution, in the process calling into question the assumption that income alone is an adequate barometer for a household’s material interests. There is a need for more empirical work on perceptions of inequality that engages with the role of community resource sharing arrangements in shaping citizens’ beliefs.

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