The Burden of Caste on Social Identity in India

Abstract

This paper investigates the determinants of perceived social status in India. Results show

that caste is still the largest determinant, yet not the only one, as income, education and

occupation are all relevant factors as well. However, only unlikely improvements in those

economic attributes could offset the burden of being from a low caste or tribe on perceived

social rank. This study is part of the literature that shows how the internalization of prejudice

and long lasting discrimination may have impaired individuals' self-esteem. The results stress

the need to account for self-depreciation when assessing the efficiency of affirmative action

policies.

Keywords: Social Identity, Caste, India, Discrimination

JEL : J15, Z13, O15, O53

1

1.INTRODUCTION

Since the seminal work by Becker (1957) and Arrow (1971), discrimination has been

extensively studied by economists. However, until very recently discrimination, either by

taste or statistical, has been viewed as a one way act imposed by a discriminator on the one

who is discriminated against. However, a couple of recent behavioural experiments have

shown that individuals, who have long suffered from discrimination, may also suffer from a

diminished self-image. Because their social identity has been largely influenced by negative

stereotypes, they have internalized those stereotypes and tend to conform to them. Hoff

and Pandey (2006) have led an experiment where children from Northern India were asked

to solve mazes. When the children's castes were not revealed, performance by low caste

children was not very different from that of higher castes. Yet, when castes were publicly

announced, performance by lower castes children significantly dropped. Although the

authors cannot rule out a couple of competing hypothesis, it seems that a loss of self-

confidence was at play in the performance decline. This experience was replicated and

adapted to the Chinese context by Afridi et al. (2012) and led to similar conclusions.

Similarly, Shih et al. (1999) conducted an experiment during which Asian American females

were grouped in three and given a math test. In one group, the Asian identity was

emphasized. In a second the gender was stressed and in the control group no identity was

particularly made salient. Results show that the first group outperformed and the second

group under-performed compared to the control group. Thus, women performance was

altered by the stressed stereotype. There are many other experiments of this sort1 and most

evidence that individuals act in conformity with what others expect of them, either because

context activates their diminished self-image or because individuals expect an unfair

2

treatment. However, another strand of the literature considers that long standing

discrimination has shaped self-perception independently of the context and thereby reduced

the most vulnerable group's set of expectations. Hoff and Stiglitz (2010) show that belief

systems, such as the internalization of one’s inferiority, shape perceptions and reduce self-

confidence and end in an equilibrium that confirms such an inferiority even though entirely

baseless.

In the light of these recent experiments, some economists (Akerlof and Kranton, 2005,

2010) have pleaded for the integration of the concept of social identity in order to explain

changes in behaviours and preferences. For instance, individuals may self-discriminate or be

less prone to collective action if their social identity leads to a diminished self-image. Hoff et

al. (2011) conducted an experiment where higher castes appeared more willing to punish

norm violators. One of the explanations put forward is the greater capacity of higher castes

to play the role of enforcers as a result of their internalized higher status, and thus a

probably greater capacity to build collective action. Not only do these experiments and

research in social identity shed a new light on the process of discrimination by underlying

the fact that it may also work through depreciated self-esteem, but it also calls for a

reassessment of the efficiency of anti-discrimination policies and more precisely of

affirmative action, which is a much discussed subject. Some works show that these policies

are effective at eroding negative stereotypes (Beaman et al. 2009) or raising aspirations

(Beaman et al. 2012), while others argue that they only benefited the better off fringe of the

targeted populations (Bag and Sikdar 2013) or are often disregarded because of social stigma

(Gille 2013). Indeed, affirmative action appears as a two edge sword as it can empower

despised groups while underlining negative stereotype and thereby reinforcing diminished

self-image. If potential beneficiaries have internalized a negative self-image, as shown in this

3

article, and therefore do believe they lack worth and self-discriminate, which can be a self-

reinforcing equilibrium or are reminded of their inferiority one could question their

willingness to apply to reserved positions and thereby the efficiency of such policies.

This article examines the legacy of caste based discrimination in India on low caste self-

image. Indian society has long been fragmented into a myriad of hereditary endogamous

groups that can be socially ranked, and usually known as castes. One is born into a caste and

cannot change it over his lifetime. A social status is associated with each group and although

a unique hierarchy among the thousands of castes found on the subcontinent cannot be

established, it is nevertheless clear that some groups, often referred to as untouchables or

Dalits, as by their preferred names, lie at the very bottom of the theoretical social hierarchy

and have long suffered from social stigma. Because Dalits are theoretically ritually impure,

they also have traditionally been ostracized. In order to make up for this long standing

deprivation, the Constitution of India enshrined the duty for the State "to promote with

special care the educational and economic interest of the weaker section of the people and,

in particular, of the Scheduled Castes and Scheduled Tribes, and shall protect them from

social injustice and all forms of exploitation”2. The groups referred to as Scheduled Castes

("SC") or Scheduled Tribes ("ST"), as per their administrative labels, actually encompass both

the former untouchables and tribes who although not equivalent to untouchables have also

suffered from a similar kind of stigma and ostracism. Later texts reserved vacancies in the

public sector and educational institutes for SCs and STs, and there has been some debate in

India about extending reservation policies to other sectors and other groups, mentioned as

Other Backward Classes ("OBCs").

4

This article investigates the impact of caste on the way individuals perceive their social

ranks. More precisely it examines the determinants of the answers given to the following

question "to which of these five social classes do you think you belong to?". It should be

emphasized that this question was privately asked and answers are very likely to translate

the way the individual perceives himself, his internalized social status, which is part of his

social identity. This article examines the effect of caste belonging on perceived social rank,

asks whether other attributes besides castes, such as income, education and occupation are

relevant in shaping perceived social rank and whether improvements in such economic

attributes may compensate for the burden of belonging to Scheduled Castes or Tribes. First,

results show that caste belonging is still a major determinant of perceived social rank.

Members of low castes and tribes seem to have internalized the fact that they should lie at

the bottom of the social ladder, no matter what their other attributes are. Second, other

characteristics also play a role in the sense that better education, higher income and more

enviable job positions all lead to improvements in perceived social rank. Yet, the

improvements in those characteristics necessary to compensate for the burden of belonging

to a Scheduled Caste or Tribe are so large that they appear unlikely. Thus, affirmative action

policies that have taken the form of reservation in India may improve those characteristics,

which is a valuable goal in itself, yet they may come up against the legacy of past

discrimination on self-image.

The structure of the paper is as follows. Section (2) presents the data and the variables

relevant to the analysis. Section (3) sets out the empirical strategy, while section (4) displays

and comments the results and estimates. Section (5) discusses potential empirical issues and

presents robustness checks while section (6) concludes.

5

2.DATA

2.1. Presentation of the data

The data are extracted from the Indian section of the World Values Survey ("WVS")

conducted in 20013. It covers 1,951 households for which "ethnic group" is reported, the

latter encompassing both castes and religious denominations. In order to avoid addressing

the issue of castes within religions other than Hinduism, which would be extremely thorny,

the sample has been restricted to the 1,657 Hindu households. Households are identified as

per the official labels of Scheduled Castes (15% of the sample), Scheduled Tribes (6% of the

sample4). 38% of the households are identified as "backward", a term that is often used to

refer to low but not untouchable castes. However, it is not sure that the backward castes

listed here do actually correspond to the more formal Other Backward Classes ("OBCs")

category as recognized by some governmental institutions.

This article focuses on one of the questions asked during face to face interviews: "to

which of these five social classes do you think you belong5?". Figure 1 below presents the

distribution of the answers across caste groups. As expected, SCs and STs tend to rank

themselves much lower than nonscheduled groups.

6

Figure 1: Distribution of perceived social class by caste

However, low ranking by SCs and STs may be due to worse economic attributes such as

income, occupation or education6. The 2008 average income in India, as estimated by the

Central Statistics Organization of the Government of India, was 3,000 rupees per month.

While 80% of SCs and 75% of STs have an income below this average, only 53% of the

nonscheduled groups do. The World Bank sets the poverty line in 2005 at 648 and 429

rupees a month for urban and rural areas respectively. About 6% of the sampled scheduled

groups have an income below 500 rupees a month, while only 1% of the nonscheduled

groups do. Generally speaking, the income distribution for the scheduled groups is more

skewed towards the lower end than for nonscheduled groups. Inequalities in educational

outcomes are also quite stark as 65% of SCs and 56% of STs did not complete primary school,

7

while this number for nonscheduled group is 33%7. As far as occupations are concerned, SCs

and STs tend to hold positions that require less human or physical capital. 23% are either

employed as agricultural worker or unskilled manual worker, while this number is 6% for

nonscheduled groups. More generally, the great overlap between castes and economic

attributes is well documented in Deshpande (2011).

Thus given the great overlap between socio-economic indicators of social status and

caste, it is difficult to predict a priori whether the greater tendency for scheduled groups to

rank low on a social scale is directly linked to membership to either a Scheduled Caste or

Tribe or unfavorable attributes. Untangling the two is one of the objectives of the empirical

strategy and estimations.

2.2. Variables used

We wish to examine whether caste is the sole determinant of a perceived social

ranking or whether other attributes may also affect the outcome and in a manner that could

eventually offset the burden of caste belonging. Therefore, the analysis will focus on 5 main

variables that are perceived social class, caste, income, education and occupation.

Perceived social status takes on values 1 for lower class through 5 for upper class.

Castes are represented by three dummy variables for Scheduled Castes, Scheduled Tribes

and nonscheduled groups. It should be noted that the latter category is very broad as it

encompasses OBCs, whose status is relatively low as well as higher castes who rank at the

top of the theoretical caste hierarchy. Backward castes are identified within the sample,

although given there is some doubt that this category actually corresponds to the OBCs as

recognized by governmental institutions, the analysis will focus on scheduled groups such as

8

SCs and STs versus nonscheduled groups, although some comparison between SCs, STs,

backward castes and others will occasionally be performed, keeping in mind that the

nonscheduled group is rather heterogeneous.

Household's income was not recorded as a continuous variable but rather as a

categorical one that takes on 9 values. Tests on the homogeneity of the distribution of

income, educational and occupational ranges across classes have been performed and as a

result some categories were aggregated8.

2.3. Benchmark scenario

Given that most of the variables are discrete, a benchmark scenario needs to be defined.

It will serve as a reference case and will depict a situation, apart from caste, that would most

likely result in a low social ranking, i.e. an agricultural worker9 earning less than 1,000 rupees

a month, who is illiterate. However, the reference case will be a nonscheduled individual.

Such a base case scenario will allow to directly compare the effect of belonging to either a

Scheduled Caste or Tribe to the impact of improving various attributes. Therefore, we will be

able to draw conclusions on improvements necessary to cancel the potential poor self-image

associated with belonging to a low caste or tribe.

3.EMPIRICAL STRATEGY

Given that the dependent variable is ordinal, the analysis resorts to an ordered probit

model. Let Yi* be the latent continuous measure of perceived social class by individual i

defined by the following relationship:

Yi*= αk Xik + εi (1)

9

Where Xik is the set of independent variables that encompasses the group to which individual

i belongs, either SC or ST or nonscheduled group, the individual’s occupation type, education

level and income range as well as a vector of control variables usual to the literature on

social capital such as gender and age of the respondent as well as its quadratic form

together with a dummy equal to one if the individual lives in a urban area10. εi is a random

error term assumed to follow a standard normal distribution.

Yi is the observed ordinal variable so that for the jth outcome Yi=j for j=1…5 and is determined

from the model as follows:

1 if - ∞ ≤ Yi*

≤ μ1

Yi = j if μj-1 < Yi*

≤ μj

5 if μ4 < Yi*

≤ + ∞

Where μi are thresholds to be estimated together with the coefficients.

The probabilities for each ordinal outcome are therefore:

P [Yi = 1] = Φ (μ1- αk Xik)

….

P [Yi = j] = Φ (μj – αk Xik) - Φ (μj-1 - αk Xik)

….

P [Yi = 5] = 1- Φ (μj-1 - αk Xik)

For Φ the standard normal cdf.

Although coefficients in ordered probit models give the general direction of an effect, they

do not provide any information about its magnitude. In order to know how the probabilities

of ranking in the different classes would change in response to a move from the residual

10

category of an independent variable to the category in question, the values of the other

variables remaining unchanged, marginal effects are computed as follows:

(P [Yi = 1]) / ( Xik) = - Φ (μ1- αk Xik) αk

(P [Yi = j]) / ( Xik) = - αk [Φ (μj – αk Xik) - Φ (μj-1 - αk Xik)]

(P [Yi = 5]) / ( Xik) = αk Φ (μj-1 - αk Xik)

Because the cutoff points μj have to be estimated together with the coefficients, marginal

effects provide different slopes for the 5 social classes. For instance, the marginal effect of

being from a Scheduled Caste may have a different effect on the likelihood to rank in lower

class from the likelihood to rank in middle class. Marginal effects will therefore be

presented.

4.RESULTS

4.1. Base Model

A first set of estimation is run on the model presented in section 311. However, in order

to make the results clearer, the significance of the difference in coefficients for each range is

assessed. Whenever coefficients between two ranges did not significantly differ, these

ranges were aggregated. For instance, the effect of having primary education is not different

from that of being illiterate. Thus, both variables were regrouped into a single category 12. It

is interesting to see that the educational levels that matter as far as perceived social class is

concerned are below middle / high school and post graduate. Similarly, occupation

categories are regrouped as follows:

11

- Occupation 1 Cultivating own farm / Manager / Professional / Supervisory office worker

- Occupation 2 Non manual office worker / Skilled manual worker

- Occupation 3 Semi-skilled manual worker

- Occupation 4 Unemployed / Student / Retired / Housewife

- Occupation 5 Agricultural worker / Unskilled manual worker

These categories can be intuitively ranked. While the first category encompasses mainly

supervisory positions, the second one regroups more subordinate yet clerical positions,

while categories 3 and 5 are manual occupations and lack human capital9.

Based on these new aggregates, results were estimated anew and are presented in Table 1.

Specification (1) in Table 1 compares scheduled groups versus the rest of the population,

while specification (2) decomposes the scheduled groups into SCs and STs and specification

(3) compares SCs, STs and backward castes to the rest of the population, mainly higher

castes.

12

Table 1: Base specification

Sched. Groups SCs and STs SCs,STs, Backward Castes

vs non Sched. Groups vs non Sched. Groups vs Higher Castes

(1) (2) (3)

Coeff. Rob. Stand. Coeff. Rob. Stand. Coeff. Rob. Stand.

Errors Errors Errors

Castes Scheduled -0.778*** (0.0786)

SC -0.718*** (0.0897) -0.914*** (0.0979)

ST -0.916*** (0.137) -1.111*** (0.143)

backward -0.358*** (0.0648)

Income 3,001 - 5,000 Rps/month 0.216*** (0.0757) 0.222*** (0.0760) 0.204*** (0.0768)

5,001-10,000 Rps/month 0.495*** (0.0810) 0.495*** (0.0810) 0.419*** (0.0831)

>10,000 Rps/month 1.025*** (0.126) 1.025*** (0.126) 0.955*** (0.127)

Occupation* Occupation 1 0.420*** (0.122) 0.438*** (0.124) 0.460*** (0.124)

Occupation 2 0.0574 (0.164) 0.0667 (0.165) 0.0781 (0.164)

Occupation 3 -0.229 (0.150) -0.222 (0.150) -0.172 (0.152)

13

Occupation 4 0.386*** (0.125) 0.402*** (0.127) 0.447*** (0.127)

Education Mid. School - college 0.450*** (0.0735) 0.449*** (0.0735) 0.417*** (0.0738)

Postgrad. / Prof. Degree 0.737*** (0.129) 0.734*** (0.129) 0.698*** (0.131)

Controls Urban 0.198*** (0.0638) 0.191*** (0.0642) 0.221*** (0.0644)

Female -0.0326 (0.0769) -0.0354 (0.0771) -0.0602 (0.0776)

Age -0.00393 (0.0107) -0.00491 (0.0108) -0.00320 (0.0109)

Age² 8.58e-05 (0.000117) 9.46e-05 (0.000118) 6.95e-05 (0.000119)

Observations 1,482 1,482 1,482

Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1Omitted categories: income: less than 3,000 rupees / month; Occupation: Agricultural worker / unskilled manual worker; Education: illiterate or completed primary school.* Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

14

As expected, being from a scheduled group significantly decreases the likelihood to rank in

higher classes all other attributes held constant. Table 2 presents the marginal effects based on

specification (2) of Table 1. It shows the change in the likelihood to rank in each of the class that is

induced by a move from the baseline scenario to the category, all other variables held constant.

For instance, the probability for the baseline person to rank in lower class is increased by 19% if

he is SC, while the likelihood to rank in upper class is increased by 7.4% if he is in the highest

income category, all other variables remaining unchanged.

Table 2: Marginal effects based on specification (2) of Table 1

Lower ClassWorking

ClassLower

Middle ClassUpper

Middle Class Upper classCaste SC 0.190*** 0.0890*** -0.155*** -0.112*** -0.0113***

(0.0291) (0.00903) (0.0249) (0.0116) (0.00279)ST 0.270*** 0.0827*** -0.221*** -0.121*** -0.0107***

(0.0501) (0.00836) (0.0406) (0.0113) (0.00263)Income 3,001 - 5,000 Rps/month -0.0415*** -0.0385*** 0.0255*** 0.0477*** 0.00693**

(0.0132) (0.0137) (0.00743) (0.0174) (0.00287)5,001-10,000 Rps/month -0.0831*** -0.0869*** 0.0376*** 0.113*** 0.0194***

(0.0116) (0.0151) (0.00672) (0.0210) (0.00511)>10,000 Rps/month -0.123*** -0.169*** -0.0354 0.253*** 0.0743***

(0.0101) (0.0182) (0.0270) (0.0347) (0.0183)Occupation* Occupation 1 -0.0870*** -0.0734*** 0.0576*** 0.0902*** 0.0126***

(0.0241) (0.0212) (0.0162) (0.0259) (0.00472)Occupation 2 -0.0132 -0.0114 0.00887 0.0138 0.00187

(0.0314) (0.0285) (0.0201) (0.0350) (0.00495)Occupation 3 0.0506 0.0345 -0.0398 -0.0408 -0.00461*

(0.0377) (0.0213) (0.0315) (0.0250) (0.00263)Occupation 4 -0.0764*** -0.0689*** 0.0472*** 0.0855*** 0.0125**

(0.0225) (0.0222) (0.0129) (0.0280) (0.00536)Education Mid. School - college -0.0900*** -0.0748*** 0.0604*** 0.0918*** 0.0127***

(0.0152) (0.0127) (0.0115) (0.0153) (0.00336)Postgrad. / Prof. Degree -0.0990*** -0.127*** 0.00287 0.181*** 0.0422***

(0.0118) (0.0209) (0.0189) (0.0355) (0.0140)Controls Urban -0.0393*** -0.0320*** 0.0278*** 0.0385*** 0.00499**

(0.0134) (0.0108) (0.00977) (0.0130) (0.00195)Observations 1,482 1,482 1,482 1,482 1,482Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1. Specifications also include controls such as gender of respondent and age and age².Omitted categories: Income: less than 3,000 rupees / month; Occupation: Agricultural worker / Unskilled manual worker; Education: illiterate or completed primary school;* Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

15

The probability for SCs to rank either as low or working class is increased by 27.9%

compared to nonscheduled groups, while it is increased by 35.3% for STs. The fact that STs rank

significantly lower than nonscheduled groups is understandable as they have endured long

standing discrimination in the same manner as Scheduled Castes, and in many cases have

suffered from very similar untouchability practices and stigma. Yet, STs also rank significantly

lower than SCs. This may be attributable to the fact that, while Scheduled Castes have managed

to assert themselves as a political force (Jaffrelot 2002) under the impulsion of charismatic

leaders such as Dr Ambedkar, STs somewhat lagged behind. Moreover, STs are often relegated to

remote areas so that, as Kumar (2003) writes “such a profile of tribal India makes it obvious that

the tribals are the worst sufferers of resourcelessness and choicelessness as well as the most

disenchanted section of the Indian population in post-colonial India”. Both factors probably

contribute to STs diminished self-image, even when compared to SCs, although as later results

will show the second one is probably the most important.

For comparison purposes, switching from the lowest income range (i.e. less than 3,000

rupees per month) to the highest one (more than 10,000 rupees a month) decreases the

likelihood to rank either as low or working class by 29.2% and it does barely compensate for the

effect of belonging to a Scheduled Caste (27.9%) but not to a Scheduled Tribe (35.3%), all other

attributes held constant. As already noted, 3,000 rupees per month was the average income in

200813 while Banerjee and Piketty (2005) assessed, based on tax returns data in 1999-2000, that

the top percentile earned approximately 7,300 rupees and more per month14. The top 0.5%, earn

more than 12,000 rupees a month. So the necessary jump in income to cancel the SC or ST effect

is quite equivalent to moving from an average income to the top 0.5%. Similarly, moving out of

the least enviable occupational category, i.e. agricultural manual worker (omitted) to supervisory

or clerical position (occupation 1), all other things equal, would reduce the likelihood to rank in

16

the two lowest classes by 16% which is little in comparison to the impact of being from a

scheduled group. Finally, having a postgraduate degree compared to being either illiterate or

having achieved primary school reduces the likelihood to rank in the two last groups by 22.6%.

Thus, it is fair to say that the effect on perceived social status of belonging to an SC or an ST

cannot be compensated by any improvement in each one of the other attributes, even the most

unlikely ones such as increasing income 3.5 times.

The impact of belonging to a Scheduled Caste or Tribe is even larger when the omitted

reference group is purged from the "backward" group. Table 3 below presents marginal

probabilities, based on specification (3) of Table 1. Indeed, the nonscheduled group is rather

heterogeneous as it includes both high and backward castes. When SCs and STs are compared

directly to higher castes (specification (3)), the impact of being either an SC or an ST on the

likelihood to rank either as low or working class is increased to 35.2% and 41.9% respectively and

improvements in characteristics could only very partially reverse this effect. Not only are SCs and

STs unlikely to rise in perceived social rank, it is also very unlikely that high caste individuals will

decline in status. Table 3 shows that any improvement in the attributes of a baseline person who

is a high caste illiterate agricultural worker earning less than 3,000 rupees per month, in other

words that has the worst attributes besides caste, leads to a better ranking, while any of these

improvements cannot offset the effect of belonging to a SC or a ST.

17

Table 3: Marginal effects based on specification (3) of Table 1

Lower Class Working Class

Lower Middle Class

Upper Middle Class

Upper class

Caste SC 0.252*** 0.100*** -0.209*** -0.131*** -0.0120***

(0.0336) (0.00904) (0.0281) (0.0114) (0.00298)

ST 0.340*** 0.0787*** -0.277*** -0.131*** -0.0105***

(0.0538) (0.0120) (0.0408) (0.0103) (0.00263)

Backward 0.0756*** 0.0587*** -0.0574*** -0.0689*** -0.00801***

(0.0146) (0.0108) (0.0121) (0.0123) (0.00230)

Income 3,001 - 5,000 -0.0378*** -0.0359*** 0.0243*** 0.0436** 0.00586**

Rps / month (0.0132) (0.0139) (0.00784) (0.0173) (0.00262)

5,001-10,000 -0.0712*** -0.0745*** 0.0371*** 0.0941*** 0.0144***

(0.0122) (0.0155) (0.00645) (0.0209) (0.00426)

>10,000 -0.116*** -0.161*** -0.0213 0.237*** 0.0612***

(0.0103) (0.0189) (0.0250) (0.0358) (0.0160)

Occupation* Occupation 1 -0.0898*** -0.0783*** 0.0611*** 0.0945*** 0.0124***

(0.0235) (0.0214) (0.0163) (0.0257) (0.00453)

Occupation 2 -0.0151 -0.0136 0.0104 0.0162 0.00206

(0.0304) (0.0290) (0.0197) (0.0350) (0.00471)

Occupation 3 0.0378 0.0279 -0.0300 -0.0322 -0.00349

(0.0360) (0.0230) (0.0303) (0.0263) (0.00264)

Occupation 4 -0.0828*** -0.0776*** 0.0519*** 0.0953*** 0.0133**

(0.0218) (0.0225) (0.0126) (0.0282) (0.00537)

Education Mid. School – college

-0.0824*** -0.0708*** 0.0573*** 0.0849*** 0.0109***

(0.0150) (0.0129) (0.0115) (0.0153) (0.00300)

Postgrad. / Prof. Degree

-0.0940*** -0.122*** 0.00843 0.172*** 0.0363***

(0.0121) (0.0216) (0.0176) (0.0363) (0.0127)

18

Controls Urban -0.0446*** -0.0375*** 0.0325*** 0.0442*** 0.00535***

(0.0132) (0.0110) (0.0100) (0.0130) (0.00193)

Observations 1,482 1,482 1,482 1,482 1,482

Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1. Specifications also include controls such as gender of respondent and age; age².Omitted categories: Income: less than 3,000 rupees / month; Occupation: Agricultural worker / Unskilled manual worker; Education: illiterate or completed primary school*Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

To be fair, we have so far only compared improvements in each of the economic attributes

to the effect of castes. However, positive shifts in one attribute, say education for instance, is

likely to prompt improvements in other attributes as well. For instance, we may say from Table 2,

that having at least middle school education decreases the likelihood to rank in the two lowest

classes by 16.5%. Having college education may also prompt an increase in income15 from the

below 3,000 rupees range to the next one which in turns leads to a decrease in the likelihood to

rank in the two lowest classes by 8.0%. Similarly, given that more than 50% of the individuals who

achieved at least middle school are employed in a type 1 occupation (Cultivating own farm /

Manager / Professional / Supervisory office worker)16, and that the latter decreases the

probability to rank in the two lowest classes by 16%, an initial improvement in education may set

a virtuous circle into motion that may cancel out the effect of belonging to a Scheduled Caste or

Tribe as the total effect would be a 40% decrease in the likelihood to rank in the two lowest

classes compared to a 28% and 35% increase due to membership to SCs and STs respectively.

However, such a statement implicitly assumes as certain the shift in income prompted by

education, for instance, which may not happen. Thus, we still may conclude that canceling out the

SC or ST effect may require a bit of a stretch, especially when the reference group is purged from

the OBCs.

19

Figures 2 and 3 below sets out the likelihood to rank in lower middle class17 as attributes

such as income, occupation and education move from the omitted category to beyond average

levels that is earning more than 3,000 rupees a month, having more than primary education and

being employed in a type 1 occupation. Figure 2 compares SCs, STs and nonscheduled groups and

corresponds to specification (2) of Table 1 while Figure 3 compares SCs, STs, Backward Caste and

the rest of the population and reflects specification (3) of Table 1.

As can be seen from the Figures, cumulative improvements in all these attributes do not

manage to ensure SCs or STs a positive probability to enter the lower middle class category,

especially when the reference group if purged from the OBC category, while any improvement in

the attributes of the high caste baseline individual leads to a better status. Not only is caste

membership a burden on perceived social rank for members of scheduled groups but it is also

very favorable to higher castes sense of status. Indeed, if any improvement in the worst attributes

of a higher caste individual result in a better ranking, it is quite unlikely that higher castes

individuals will decline in status.

Figure 2: Likelihood to rank in Lower Middle Class based on specification (2) of Table 1

20

This figure sets out the likelihood to rank in Lower Middle Class as attributes cumulatively improve from the benchmark scenario ( Income: less than 3,000 rupees / month; Occupation: Agricultural worker / Unskilled manual worker; Education: illiterate or completed primary school) to beyond average levels (Income: more than 3,000 rupees / month; Occupation: Cultivating own farm / Manager / Professional / Supervisory office worker; Education: more than primary school education).“Caste” shows the likelihood that a SC/ST with benchmark attributes rank in lower middle class compared to a member of a nonscheduled group with similar attributes. “Caste + income” shows the likelihood that an individual belonging to a SC/ST/nonscheduled group rank in Lower Middle Class when his income rises from below to more than 3,000 rupees a month, other attributes held constant at benchmark values. “Caste + income + education” describes the same situation as “caste + income” except that the educational level has risen to above primary school. “Caste + income + education + occupation” show the likelihood to rank in Lower Middle Class for an individual with average attributes and belonging to an SC/ST/ nonscheduled group.

21

Figure 3: Likelihood to rank in Lower Middle Class based on specification (3) of Table 1

This figure sets out the likelihood to rank in lower middle class as attributes cumulatively improve from the benchmark scenario (Income: less than 3,000 rupees / month; Occupation: Agricultural worker / Unskilled manual worker; Education: illiterate or completed primary school) to beyond average levels (Income: more than 3,000 rupees / month; Occupation: Cultivating own farm / Manager / Professional / Supervisory office worker; Education: more than primary school education).“Caste” shows the likelihood that an individual belonging to a SC/ST/backward caste and having benchmark attributes rank in lower middle class compared to a member of a higher caste with similar attributes. “Caste + income” shows the likelihood that an individual belonging to a SC/ST/Backward/nonscheduled group rank in Lower Middle Class when his income rise from below to more than 3,000 rupees a month, other attributes held constant at benchmark values. “Caste + income + education” describes the same situation as “caste + income” except that the educational level has risen to above primary school. “Caste + income + education + occupation” show the likelihood to rank in Lower Middle Class for an individual with average attributes and belonging to an SC/ST/ Backward Class/nonscheduled group.

Living in an urban area, all other attributes held constant decreases the likelihood to rank

in the two lowest classes by 7%. However, this impact may vary depending on groups. So far, the

effect of groups, either Scheduled Caste or Tribe, has been compared to that of other variables,

implicitly assuming that other determinants of perceived social class have a similar effect across

castes. However, there is a common belief that in urban settings being from a low caste is not as

much of a burden as when living in rural areas. This common belief originates from the fact that

caste cannot be guessed from physical attributes, caste belongings being only known from

common knowledge, which requires, for information to travel, a limited number of connections.

22

To test this hypothesis, the urban variable has been interacted with the SC and ST dummies.

Results are presented in the online appendix (Table A2).

Living in a urban area increases the probability to rank in higher classes, whatever the

group and there is no specific effect for SCs, thereby disproving the common belief that caste is

less of a burden in a urban setting, at least as far as SCs are concerned. On the other hand,

moving to urban areas has an additional effect on STs self-perception of 0.65 compared to 0.15

for either SCs or nonscheduled group. This confirms the previous hypothesis that STs rank lower

than SCs because they mostly live in remote villages as the impact of being a urban SC is now

close to that of being a urban ST.

So far, it has been broadly assumed that the effect of attributes other than caste is

homogeneous across groups. Should this not be the case, caste would not only have an impact of

itself but also through the alterations of the effects of other variables. For instance, if the impacts

of those attributes are significantly larger for Scheduled Castes and Tribes than for other groups,

then the improvements in income necessary to overcome the burden of being from a scheduled

group may not be as large and, in a way, members of scheduled groups could earn their way out

of caste.

4.2. Conditional Effects

A likelihood ratio test obtained by fitting the model for scheduled and nonscheduled groups18 and

then comparing the results with those of the base model estimated over the whole sample

concluded that the parameters vectors do significantly differ across groups at the 5% level of

significance (likelihood ratio χ2 26.55). Determinants of perceived social class may therefore not

23

have the same effect for each group. The main determinants of perceived social class that are

education, occupation, and income are interacted with the scheduled group dummy and results

are presented in Table 5 (specification (1) of this Table reproduces the results from the base

specification presented in Table 1 column (2) for convenience).

24

Table 5: Inclusion of the interaction terms

(1) (2) (3) (4)Caste SC -0.718*** -0.733*** -0.564*** -0.724***

(0.0897) (0.0995) (0.211) (0.106)ST -0.916*** -0.941*** -0.772*** -0.913***

(0.137) (0.159) (0.262) (0.154)Income 3,001 - 5,000 Rps/month 0.222*** 0.211** 0.214*** 0.222***

(0.0760) (0.0825) (0.0763) (0.0760)5,001-10,000 Rps/month 0.495*** 0.469*** 0.491*** 0.489***

(0.0810) (0.0850) (0.0814) (0.0812)>10,000 Rps/month 1.025*** 1.071*** 1.024*** 1.030***

(0.126) (0.130) (0.126) (0.126)Income x 3,001 - 5,000 Rps/month 0.0746Scheduled (0.194)

5,001-10,000 Rps/month 0.304(0.234)

>10,000 Rps/month -0.474(0.419)

Occupation* Occupation 1 0.438*** 0.432*** 0.497*** 0.437***(0.124) (0.125) (0.150) (0.124)

Occupation 2 0.0667 0.0539 0.265 0.0572(0.165) (0.166) (0.195) (0.165)

Occupation 3 -0.222 -0.232 -0.257 -0.224(0.150) (0.151) (0.179) (0.150)

Occupation 4 0.402*** 0.404*** 0.501*** 0.400***(0.127) (0.127) (0.152) (0.127)

Occupation* x Occupation 1 -0.0386Scheduled (0.252)

Occupation 2 -0.794**(0.371)

Occupation 3 0.335(0.299)

Occupation 4 -0.270(0.247)

Education Mid. School – college 0.449*** 0.446*** 0.461*** 0.450***(0.0735) (0.0734) (0.0740) (0.0799)

Postgrad. / Prof. Degree 0.734*** 0.716*** 0.760*** 0.707***(0.129) (0.129) (0.130) (0.132)

Education Mid. School – college -0.0160x Scheduled (0.155)

Postgrad. / Prof. Degree 0.902**(0.441)

Observations 1,482 1,482 1,482 1,482Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1. All specifications include age, age², gender and urbanOmitted categories: Income < 3,000 rupees / month; Occupation: Agricultural worker/ Unskilled manual worker; Education: illiterate or completed primary school;* Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

25

First, the effect of income does not vary across groups (specification 2). Second, for the

whole population, the effect of being employed as either a non manual office worker or a skilled

manual worker (occupation 2) is not different from being an agricultural or unskilled manual

worker. Yet, for scheduled groups, this situation actually leads to a lower social ranking

(specification 3), although coefficients associated with the caste variables are somewhat reduced,

meaning that the direct effect of belonging to a scheduled group, when purged from the varying

effect of occupation is smaller. An interpretation of this result could be that the internalized

diminished self-image is strongly linked to discrimination in the workplace, especially in non-

supervisory position. Finally, having a professional or a postgraduate degree has an additional

effect for members of scheduled groups that is quite equivalent to that of belonging to SC or ST

(0.9 vs 0.7 and 0.9 respectively). Acquiring a top level education therefore puts members of

scheduled and nonscheduled groups on an equal footing.

Only the effect of a top educational level has a specific effect for scheduled groups that

allows them to rank similarly to nonscheduled groups. Yet, this good piece of news should

nevertheless be moderated by the fact that less than 1% of SCs and STs do have either a

postgraduate or a professional degree. On the other hand, the impacts of other characteristics

either do not vary across groups or are detrimental. Thus, the comments made above about

improving attributes to compensate for the caste still hold: improvements in those attributes

could potentially compensate for the burden of belonging to a Scheduled Caste or Tribe, yet, the

study of the magnitude of the coefficients show that such improvements need to be so large that

they are unlikely. Nevertheless, the specific effect of SCs and STs higher education pleads in favor

of university quotas.

5.POTENTIAL ISSUES

26

5.1. Subjectivity

It could be objected to the analysis that perceived social class is subjective and that

subjective measures induce, as mentioned by Clark and Oswald (2008) three difficulties:

ordinality, scaling and omitted dispositions. The issue of scaling relates to the fact that different

individuals may have different mental scales that prevent from treating their answers as cardinal

values. For instance, an individual may assess the distance between middle lower class and

working class differently from another. The issue of ordinality arises when ranking of the answers

is heterogeneous and ambiguous. Given that this study is only concerned with ordinality and not

cardinality of the dependent variable and resorts to an ordered probit model whose outcomes

are easy to rank, the first two difficulties of ordinality and scaling are overcome. The omitted

disposition problem is somewhat trickier. If the perceived outcome is assumed to be correlated

with individuals' unobservable characteristics such as optimism, self-confidence or obedience to

traditions, that may in turn be correlated with explanatory variables, such as caste, the analysis is

left with an omitted variable problem. As Clark and Oswald (2002) put it "cross section equations

will be unreliable whenever unobservable characteristics (like a person's natural cheerfulness) are

correlated with observable characteristics (like education)". In the case at hand we may think that

the influence of caste on perceived social status depends on how binding the individual think

caste is. For instance, an individual may be very dissatisfied with his life, and therefore rank lower,

while such a feeling may be correlated with being from a lower caste. Or, because he perceives

himself as very obedient to traditions he would rank in a specific manner, while such obedience is

correlated with caste status. To control for both cases, we resort to answers provided by the WVS

from questions about the individual's general sense of happiness, satisfaction with his life and

sense of free choice and control over his life and whether this individual pictures himself as a very

27

religious person19. These variables are included into the base specification and results are

presented in Table 6.

Table 6: Inclusion of subjective variables

(1) (2) (3) (4) (5) (6)Caste SC -0.718*** -0.760*** -0.729*** -0.720*** -0.727*** -0.713***

(0.0897) (0.0902) (0.0889) (0.0959) (0.0927) (0.0963)ST -0.916*** -0.955*** -0.939*** -1.009*** -0.953*** -1.011***

(0.137) (0.143) (0.143) (0.150) (0.142) (0.155)Income 3,001 - 5,000 0.222*** 0.181** 0.181** 0.157* 0.212*** 0.125Rps / month (0.0760) (0.0780) (0.0775) (0.0825) (0.0778) (0.0843)

5,001 - 10,000 0.495*** 0.467*** 0.458*** 0.490*** 0.495*** 0.463***(0.0810) (0.0804) (0.0812) (0.0854) (0.0822) (0.0867)

> 10,000 1.025*** 0.988*** 0.942*** 1.007*** 0.981*** 0.922***(0.126) (0.126) (0.124) (0.133) (0.128) (0.132)

Occupation* Occupation 1 0.438*** 0.405*** 0.434*** 0.407*** 0.426*** 0.385***(0.124) (0.126) (0.125) (0.136) (0.129) (0.140)

Occupation 2 0.0667 0.0139 0.0907 -0.00889 0.0138 0.00606(0.165) (0.168) (0.168) (0.176) (0.171) (0.183)

Occupation 3 -0.222 -0.248 -0.198 -0.292* -0.261* -0.274*(0.150) (0.151) (0.152) (0.164) (0.152) (0.165)

Occupation 4 0.402*** 0.364*** 0.427*** 0.400*** 0.414*** 0.427***(0.127) (0.127) (0.127) (0.137) (0.132) (0.143)

Education Mid. School - college 0.449*** 0.433*** 0.456*** 0.412*** 0.426*** 0.439***(0.0735) (0.0747) (0.0740) (0.0802) (0.0751) (0.0814)

Postgrad. / Prof 0.734*** 0.701*** 0.669*** 0.661*** 0.785*** 0.715***Degree (0.129) (0.127) (0.124) (0.135) (0.128) (0.129)

Rob. Checks Happiness -0.137*** -0.000627(0.0389) (0.0464)

Satisfaction 0.0806*** 0.0597***(0.0138) (0.0166)

Freedom of Choice 0.0284** 0.0127(0.0114) (0.0121)

Religious 0.161** 0.0930(0.0692) (0.0719)

Observations 1,482 1,460 1,469 1,310 1,403 1,258Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1. All specifications include age, age², gender and urbanOmitted categories: Income < 3,000 rupees / month; Occupation: Agricultural worker/ Unskilled manual worker; Education: illiterate or completed primary school;* Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

Coefficients associated with castes are little changed by these additions, given that the

distributions of all the additional variables such as sense of happiness, freedom of choice and so

on are not significantly different across groups and thus are not significantly correlated with caste

28

or tribe belonging. Thus, we can be confident that personal characteristics do not prompt an

endogeneity issue. Moreover, to further emphasize that this is not a sizable issue, we may refer

to Clark and Oswald (2002) conclusions that "in happiness research, the biases in cross section

patterns may be less dramatic than has sometimes been supposed".

It could also be objected that the declared social class may not correspond to reality. Three

arguments could be made to tackle this issue. First, I want to insist that there cannot be any sort

of objectivity in the definition of social class. Even when researchers in sociology or statisticians

try to match populations with social classes, they have to make a judgment call about the class

segmentation, which necessarily brings in subjectivity. It is true that some elements allow for an

assessment of the sociological distance between individuals, such as income, lifestyles or

education and according to such distances, clusters may be identified. Yet, the sociological

distance is a continuum and where one class should start and the other end is a subjective

decision. Therefore, I would argue that there are no "real" or objective classes. Second, given that

the question about classes was translated into 13 local languages20, it is very likely that

respondents felt they were asked to rank themselves on a scale and did not attach too much

importance to the strict definition of the word "class". Third, it should be stressed that this

analysis focuses on perceived social class and the question as to whether this perception is in

conformity with some sort of reality is irrelevant; although it does assume that individuals share a

common sense of the social ladder. Nevertheless the process investigated here is that of self-

ranking and is entirely subjective.

5.2. Environment

One of the dimensions that is missing from the analysis is the respondent's environment and

most notably the local composition of the villages. Indeed it could be argued that in villages that

29

are extremely homogenous in terms of castes, say for instance dalits villages, social identity rests

much more on other economic variables while caste may be less salient. Moreover, the effect of

caste on social identity may matter differently in the South and in the North of India.

Unfortunately, the only information about the respondent's location available is the state. As a

robustness check, a dummy for the Northern states21 was introduced (specification (1) of Table 7)

as well as state fixed effects (specification (2) of Table 7). The percentage of SCs and STs in the

state's population22 was included in the base equation as a control variable (specification (3)) as

well as their quadratic terms to capture potential nonlinear effects (specification (4)).

30

Table 7: Robustness checks with state characteristics

(1) (2) (3) (4)Caste SC -0.718*** -0.769*** -0.672*** -0.709***

(0.0898) (0.100) (0.0930) (0.0953)ST -0.919*** -0.941*** -0.964*** -0.940***

(0.137) (0.150) (0.138) (0.139)Income 3,001 - 5,000 0.219*** 0.330*** 0.233*** 0.256***Rps / month (0.0762) (0.0807) (0.0766) (0.0775)

5,001 - 10,000 0.492*** 0.668*** 0.523*** 0.555***(0.0815) (0.0914) (0.0837) (0.0850)

> 10,000 1.022*** 1.097*** 1.057*** 1.086***(0.126) (0.144) (0.129) (0.131)

Occupation* Occupation 1 0.437*** 0.455*** 0.446*** 0.453***(0.125) (0.128) (0.126) (0.126)

Occupation 2 0.0699 0.0521 0.0632 0.0526(0.165) (0.167) (0.165) (0.165)

Occupation 3 -0.232 -0.225 -0.228 -0.279*(0.150) (0.176) (0.152) (0.158)

Occupation 4 0.400*** 0.494*** 0.431*** 0.434***(0.127) (0.132) (0.129) (0.130)

Education Mid. School - college 0.451*** 0.505*** 0.468*** 0.453***(0.0737) (0.0761) (0.0739) (0.0740)

Postgrad. / Prof degree 0.734*** 0.806*** 0.763*** 0.730***(0.129) (0.133) (0.129) (0.131)

Rob checks North 0.0418(0.0710)

% SC -0.825 -7.233**(0.622) (2.859)

% ST 0.684 -2.662**(0.454) (1.259)

% SC² 17.78**(8.344)

% ST² 12.83***(4.451)

Fixed Effects No State No NoObservations 1,482 1,482 1,482 1,482Robust standard errors in parentheses; *** p<0.01, ** p<0.05,*p<0.1. All specifications include age, age², gender and urbanOmitted categories: Income < 3,000 rupees / month; Occupation: Agricultural worker/ Unskilled manual worker; Education: illiterate or completed primary school* Occupation 1 : Cultivating own farm / Manager / Professional / Supervisory office worker; Occupation 2 : Non manual office worker / Skilled manual worker; Occupation 3: Semi-skilled manual worker; Occupation 4: Unemployed / Student / Retired / Housewife

Coefficients associated with the SC and ST variables remain highly significant and their

sizes are little changed by these modifications. There is no specific effect of living in the North.

When state fixed effects are entered, SC and ST coefficients somewhat decrease. Among state

characteristics that may influence ranking into social classes and be correlated with the effect of

belonging to a scheduled group, we can think of the nature of caste relationships. It is well known

31

that in some states caste relationships are much more strained or obedience to traditions and to

the caste code is stronger. In such situations belonging to a scheduled group would be an even

greater burden than somewhere else. The percentages of SCs and STs in the state has a significant

U-shaped effect on perceived social class. Yet, the inclusion of these variables did alter neither the

significance nor the size of the coefficients associated with the SC and ST variables. However, it

should be kept in mind that this measure of social composition is at the state's level and thus is

quite coarse. Information about local composition would be more appropriate. Nevertheless, the

negative effect of being from a Scheduled Caste or Tribe is robust to all these inclusions.

6.CONCLUSIONS

This article has shown that caste is still a major determinant of perceived social rank in India.

Members of Scheduled Castes and Tribes seem to have internalized their low social positions,

other characteristics held constant. This does not mean that economic attributes such as

education, occupation or income are not relevant, as improvements in the latter may increase

perceived social rank. However, only very unlikely shifts in those attributes could make up for the

burden of belonging to either a Scheduled Caste or Tribe. These results are important from three

points of view.

First, they underline the fact that part of deprivation and discrimination is caused not only by

being looked down upon but also by an internalized diminished self-image. This article has mainly

dealt with perceived social rank, i.e. an internalized sense of social status. However, had the

answers to the question "to which of these social classes do you think you belong to?" been

declared publicly, intuition tells us that the effect of caste would have been much stronger. It

would definitely be of great interest to assess potential discrepancies between the perceived

social status and the one publicly declared. Akerlof and Kranton (2000) showed that social

32

identity is highly dependent on the actions undertaken by others. Thus we may think that such a

discrepancy between the self-perceived social identity and the declared one, probably exists and

as noted by previous authors (Tajfel et al. 1971; Tajfel and John 1979) are a source of anxiety,

known as "cognitive dissonance". Thus, we may hypothesize that the whole process of

discrimination includes three layers: a negative attitude towards the person who is discriminated

against, the expectation by the latter of this negative attitude and an internalized diminished self-

image. Disentangling the three aspects would be of great interest to better understand

discrimination. This is left for future research.

Second these results show that caste still strongly shapes social identity in nowadays India,

and does so more than any other attributes. Third, as mentioned in introduction, the

internalization by low caste of the stigma they suffered from partly questions the efficiency of

affirmative action policies. Indeed, these policies are most efficient when the beneficiaries feel

truly entitled to seize the opportunities they offer, which may not be the case if they suffer from

low self-esteem. Moreover, affirmative action policies aim at improving economic attributes of

the most deprived, which is a valuable goal in itself, but (a) these improvements can hardly

eradicate the legacy of social stigma and (b) may actually have the perverse effect of reinforcing

low self-esteem by insisting on negative identity. However, an exception should be made with

respect to quotas in higher education. It has been shown that having a postgraduate or

professional degree has a positive impact specific to SCs and STs that reverses the adverse effect

of belonging to a scheduled group, putting them and nonscheduled groups on an equal footing.

This vigorously speaks in favor of the quotas imposed on universities for SCs and STs admission.

33

NOTES

34

1 See for instance Croizet and Claire (1998), Spencer et al. (1999), Dee (2009) Benjamin et al. (2010a, 2010b). For a more extensive review of these experiments please refer to Steele (1997), Chen and Li (2009) or Akerlof and Kranton (2010).2 Constitution of India; Directive Principles of State Policy; Article 46.3 Other rounds of the survey are not workable since information about caste is either unavailable or the sample is largely unbalanced.4 According to the 2001 Census of India, SC represent 16% of the population and ST 8%.5 It is important to stress that this question was translated into 13 local languages and that the connotation associated with the classes' labels may be quite different from what is commonly understood in English. It is very likely that the classes are perceived by the interviewees as some sort of ranking on a scale from 1 to 5 and the labels devoid of the usual sociological meaning, as well as the word "class". Unfortunately, further information on this particular topic is lacking. If the assumption according to which individuals felt they were asked to rank themselves, irrespective of the actual meaning of the classes is correct, then this leaves room for subjectivity. This issue is further addressed in section 5.1. In the paper, I stress the fact that what is dealt with is perceived social class, this latter word being most probably understood as a rank rather than a class in a Marxist sense.6 Table A1 in the online appendix presents the distribution of the assumed main determinants, besides castes, of social classes across castes.7 Educational outcomes in the survey sample and in the 2001 Census of India have been compared and generally speaking, they are quite similar.8 Results from these tests are available upon request. 9 Table A3 in the online appendix presents the distribution of income across occupations and clarifies occupational ranking. Being employed as an agricultural worker is the lowest earning category.10 The household is defined as urban if it is located in a town with more than 5,000 inhabitants. This is the criteria retained by the Census of India.11 Estimates are available upon request.12 χ2 test of difference in parameters are available upon request.13 Source: Central Statistic Organization, Government of India.14 The exact number is 87,633 rupees a year. Four millions individuals fall into the top percentile.15 For instance, 80% of the individuals who did not achieve middle school earn less than 3,000 rupees per month, while only 35% of those who achieved middle school do.16 Table A4 in the online appendix sets out the occupational distribution across education levels17 Marginal probabilities show that lower middle class is the threshold as likelihoods to rank in this class and higher turn negative for SCs and STs.18 Unfortunately, observations for STs are too scarce (94) to perform an analysis that goes beyond the scheduled nonscheduled partition.19 The happiness variable is ordinal and is maximized when the interviewee declared plain unhappiness, which explains the coefficient's negative sign.20Results were estimated including a set of dummies for the language used. Results are little changed in this specification compared to the basic one. They are available upon request. Moreover, given that states were defined in India according to linguistic criteria, such a specification is very close to one that would include state fixed effects, which is presented in section 5.2.21 The North dummy is equal to one if the most widely spoken language belong to the Indo-eruropean family. Languages of the southern states belong to the Dravidian family.22 Source: 2001 Census of India.

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