Ethnic Politics and Economic Policy:

Theory and Evidence from India∗

Nikhar Gaikwad†

Abstract

How do ethnic politics recalibrate the dynamics of political conflict over economic policy?I present a formal model of political competition in ethnically divided societies to explicatethe link between identity politics and politics over economic policymaking. I show that bothbrands of politics are symptomatic of the same strategic choice faced by politicians. My keyinsight is that incentives to engage in ethnic politics dampen motivations to win support usingeconomic policy. By triggering identity in the electoral arena, politicians can boost their pop-ularity among voters who value ethnicity. But the identity card polarizes political preferences,such that groups mobilized on identity become relatively less responsive to policy. Politiciansthus fashion economic platforms toward other groups. My focus on identity mobilization gen-erates insights that upturn many expectations about who gets what from the state in divideddemocracies. Contrary to conventional wisdom, I show that ethnically homogenous industriesreceive fewer preferential policies, because politicians are more likely to court voters in theseindustries based on identity appeals while courting workers in heterogenous industries usingeconomic appeals. I test my theoretical predictions by using survey experiments and originaldata on industry-level trade policies and indicators of religion and caste ethnicity in India.

∗I thank Cameron Ballard-Rosa, Allison Carnegie, Darin Christensen, Alexandre Debs, Thad Dunning, JustinFox, Francisco Garfias, Carolina Garriga, Saumitra Jha, In Song Kim, Matto Mildenberger, Helen Milner, GarethNellis, Margaret Peters, Henry Pascoe, Shawn Ramirez, Kenneth Scheve, Pavi Suryanarayan, Guadalupe Tuñón, JasonWeinreb, Steven Wilkinson, and workshop participants at Yale University, Stanford University, the University ofCalifornia, Berkeley, Columbia-Princeton-Yale Historical Working Group, the 43rd Annual South Asia Conference,the Midwest Political Science Association, and the American Political Science Association Conference for helpfulfeedback. Draft: Please do not cite or circulate.

†Fellow, Niehaus Center for Globalization and Governance, Princeton University; nikhar.gaikwad@yale.edu.

1

1 Introduction

To explain how economic policies are formulated in the political arena, a vast literature delin-

eates how voters form coalitions to advance their material interests. In these accounts, patterns

of interest translate into patterns of mobilization, from which redistributive pressures on the state

emanate.1 Linkages between individual economic preferences and preferential economic policy

outcomes are well documented across myriad issue areas—from trade, to investment, to indus-

trial regulation—and undergird broader theories of representation. These frameworks have strong

explanatory power when the primary axis of political competition in a society is economic. But

in many electoral settings, political contests also cleave along non-economic, ethno-cultural lines.

Political entrepreneurs time and again mobilize voters using identity-related appeals in addition to

economic policy platforms.2

Following India’s Hindu-Muslim riots of 2002, for example, Gujarat’s Chief Minister Narendra

Modi sought and won re-election by waging a campaign steeped in religious communalism. Yet,

when seeking the Prime Ministerial office in 2014, Modi embraced a secular tone and replaced reli-

gion with an economic reform campaign.3 During the 1911 federal election in Canada, which was

fought over trade liberalization, the Liberal Party centered its re-election campaign on lower tar-

iffs, while the Conservatives ran on a platform of protectionism. Yet in Quebec, the Conservatives

forged an alliance with French-Canadian nationalists and contested the Liberals on ethno-linguistic

terms; by winning key constituencies, they cost the Liberals the national election and, in turn, ar-

rested trade policy reform.4 In Czechoslovakia following the Great Depression, when pro-Czech

German parties attempted to offer industrial and economic policy benefits to the country’s German

regions, a newly formed anti-Czech party waged a campaign of ethnic nationalism, and splintered

and delivered German regions to the Nazis.5 During the early twentieth century, while northern

1See, e.g.: Alt et al. 1996; Hiscox 2002b; Mayer 1984; Milner 1988; McGillivray 2004; Rogowski 1989.2Chandra 2004; Jaffrelot 1996; Varshney 2002; Wilkinson 2004.3See, for example: “Hopes and Fears in India Stirred by Hindu Nationalist,” The New York Times, 12/14/02;

“Bloodshed in ’02 Shadows Indian Politician in Race That Tests Nationalist Party,” The New York Times, 12/11/07;“Modi promises a ’shining India’ in victory speech,” The Washington Post, 5/16/14.

4Dutil and MacKenzie 2011.5Wiskemann 1967.

2

U.S. Republicans courted workers and industry groups with protectionist manufacturing tariffs,

southern Democrats fought elections by playing the “race card” and exploiting racial divisions.6

Politicians across many settings commonly rely on both cultural mobilization and economic pro-

tectionism to garner votes, yet analytical connections between the two brands of politics remain

strikingly undeveloped.

How do ethnic politics affect political conflict over economic policy? A focus on the political

aspects of identity conflict throws two key assumptions in societal coalition theories of economic

representation into sharp relief. First, although this scholarship treats voters as economic actors,

people are also motivated by non-material factors.7 Individuals quite often adhere to identity-

related imperatives when forging political allegiances. Second, this scholarship posits that politi-

cians champion the economic interests of the coalitions they represent, helping aggregate group

preferences into distributive policies.8 But political entrepreneurs time and again strategically mo-

bilize voters using identity rather than policy.9 If voters value both material and identity-related

factors, and if politicians exploit both economic and ethnic predilections in the electorate, then the-

ories of representation should take seriously how economic mobilization and identity mobilization

jointly influence political competition. A failure to do so overlooks the role of identity in shaping

economic policy outcomes. We might concurrently miss how economic policy imperatives inform

patterns of identity strife in ethnically divided societies.

This paper develops a theory that incorporates the role of identity politics into the study of

economic policymaking. In doing so, it helps explain why shifting campaign strategies emerge,

and how different forms of mobilization interact to influence representation in ethnically hetero-

dox societies. I start by assuming that the world resembles settings described by the literature on

trade and economic policymaking.10 Here, political cleavages are shaped by distributional con-

6Cohen 2008. For other cases, such as in Belgium, Ireland, and the U.S. North, see: Girvin 1989; Hechter 1976;Hume 2003; Heisler 1977.

7Akerlof and Kranton 2000; Dickson and Scheve 2006; Shayo 2009.8See, e.g.: Hiscox 2002a.9Chandra 2004; Jaffrelot 1996; Varshney 2002; Wilkinson 2004.

10Mayda and Rodrik 2005; Mayer 1984; Milner and Kubota 2005; McGillivray 2004; Rogowski 1989; Scheve andSlaughter 2001. To be sure, other compelling theoretical alternatives also seek to explain the determinants of tradepolicymaking. For instance, the institutional approach points to the role of domestic institutions (Bailey, Goldstein

3

flicts, and contests are determined by the size, resources, and mobilization capabilities of different

coalitions. Because economic policy recalibrates the material wellbeing of different societal and

industry coalitions, political elites enact policies in ways that advance the economic preferences

of politically pivotal groups in the electorate. I next introduce the possibility that voters also have

preferences related to their identities, and that politicians instrumentally manipulate the salience of

these non-economic interests in order to win elections. This approach resonates with the literature

on ethnic politics, which demonstrates that political entrepreneurs commonly trigger identity for

self-serving purposes. By wielding the “identity card,” they effectively divide the electorate along

ethno-cultural lines, prompting voters to heed ethnicity when choosing candidates.11

My core argument is that both identity politics and politics over economic policy are symp-

tomatic of the same strategic decision faced by politicians. The choice to deploy identity versus

economic appeals is intertwined because mobilizing voters on identity can render economic pol-

icy a less effective technology to win votes. In turn, because identity mobilization recalibrates

incentives to win votes using economic policy, the decision to emphasize ethnicity influences the

economic policies that politicians offer different groups in equilibrium.

I propose a theoretical framework to explicate these tradeoffs. In my framework, voters are

workers who have both material and non-material interests. Their material interests are the indus-

trial wages that they earn, while their identity-related interests pertain to the political representation

of their ethnic group. What happens when workers’ material interests come into conflict with the

interests of their co-ethnics? These conflicts abound in ethnically divided societies, leaving voters

with a stark choice between voting as an identity bloc or crossing ethnic lines and voting for their

trading interests. My solution to this problem focuses on the strategic behavior of politicians, who

and Weingast 1997; Mansfield, Milner and Rosendorff 2000; Hiscox 1999) and international institutions (Bagwell andStaiger 1999; Tomz, Goldstein and Rivers 2007; Rose 2004) in influencing trade policies, and the ideational approachpoints to the role beliefs and ideas in spurring trade policy variations (Irwin 1996; Chwieroth 2007; Schonhardt-Bailey2006). See also: Helpman, Melitz and Yeaple 2004; Melitz 2003. In reality, electoral, interest group, and institutionalapproaches all explain different aspects of trade policymaking; indeed, scholars agree that “virtually no serious studentof trade policy believes any particular approach monopolizes the truth on these issues,” (Alt et al. 1996, 691).

11Indeed, looking at the case of India, some have argued that people are inclined to “vote their caste, not cast theirvote.” Corbridge and Harriss 2000; Chandra 2004; Jaffrelot 1996; Varshney 2002; Wilkinson 2004. For theories ofcross-cutting cleavages, see Dunning and Harrison 2010.

4

seek to win elections by offering economic policies that alter voters’ relative wages or by playing

the identity card to divide the electorate along ethnic lines. When politicians play the identity card,

they might be able to boost their popularity among voters who disproportionately value identity.

Yet, identity politics also polarizes the electorate because it alienates progressive voters and ener-

gizes fundamentalist voters. I show that once polarized along the identity front, voters belonging to

an ethnic group become less likely to switch their electoral preferences in exchange for marginal

changes in economic policy. Politicians thus face fewer incentives to use policy change to win

support from voters that they target using ethnic appeals.12

The intuition behind my argument is that because groups of voters vary in how responsive

they are to changes in economic policy, politicians adapt their policies to the most favored groups.

They direct their economic policy platforms to groups that have the largest number of swing vot-

ers—those voters who are willing to switch their support from one candidate to the other for small

changes in policy. Groups in which the voters are polarized along the dimension of identity have

fewer swing voters than groups in which voters are concentrated along the dimension of identity.

Politicians thus fashion their policy platforms to favor voters in the latter group at the expense of

voters in the former group. These strategic tradeoffs help elucidate the dynamics by which indi-

viduals’ voting preferences over economic policy are mediated by their social identities and the

strategic behavior of politicians.13 My theory indicates that the ethnic distribution of industrial

activity within a constituency fixes policy outcomes because it determines the swing voters whom

politicians target. When industries are more ethnically homogenous, politicians face greater incen-

tives to court the votes of these workers using identity politics. Yet because identity politics make

workers less responsive to economic policy, it reduces political incentives to offer the industry its

preferred economic policy.

This claim about the countervailing effect of identity mobilization on economic representation

12For theories of core versus swing voters, see: Stokes et al. 2013.13For studies that explore how social identities interact with economic interests, see: Akerlof and Kranton 2000;

Dickson and Scheve 2010; Shayo 2009. For models that explicate the strategic incentives faced by politicians, see:Persson and Tabellini 2000.

5

goes against the grain with conventional wisdom about ethnic representation.14 Theories of eth-

nicity and collective action suggest that ethnic homogeneity increases the likelihood that voters

coordinate and receive policy benefits from the government.15 The literature on ethnic parties also

suggests that politicians are most likely to bestow economic benefits on co-ethnic voters.16 My

theory argues, by contrast, that as workers within industries become more ethnically homogenous,

they should receive fewer economic policy benefits, because politicians find it more advantageous

to court their votes based on ethnicity.

2 A Model of Identity Politics and Economic Policy

The model that I present offers two main contributions. First, it links the politician’s decision to

play the identity card to the politician’s choice of winning votes using economic policy. I show that

political decisions to activate ethnicity in the electoral arena are connected closely to re-election

prospects. These electoral returns depend on (a) the extent to which the identity card increases

average support among voters mobilized on ethnicity, (b) the impact of the identity card on the dis-

tribution of identity-related preferences among mobilized voters, and (c) the demographic weight

of identity groups in constituencies. The dispersion of identity-related preferences connects ethnic

mobilization to economic policymaking. In particular, it influences the rate at which politicians

can win and lose support using the technology of economic policy. Because ethnic mobilization

can render economic policy a less effective technology to win votes, beyond a critical threshold,

politicians find it more effective to win votes using policy than by using identity appeals.

The model’s second contribution lies in the implications that it draws for economic policymak-

14Note, however, that my approach builds upon, and extends in key respects, insights from the literature on multi-dimensional voting. See, e.g.: Roemer 1998; Roemer, Lee and Van der Straeten 2007; Acharya, Roemer and So-manathan Forthcoming.

15Alesina, Baqir and Easterly 1999; Austen-Smith and Wallerstein 2006; Hechter 1974, 1987. Linkages betweenethnic cohesion on the one hand and self-regulation, self-monitoring, trust, reciprocity, and collective action overpublic goods on the other hand are clearly documented in the literature. Habyarimana et al. 2007; Miguel and Gugerty2005; Richman 2006; Robinson 2012.

16According to this line of thought, informational constraints that are endemic in patronage democracies tend to“force voters and politicians to favour co-ethnics in the delivery of benefits and votes” Chandra 2004, p.12.

6

ing. It shows that policy platforms in the absence of identity politics are systematically different

from those in the presence of identity politics. In the absence of ethnic politics, politicians fashion

economic policies by taking into account the numerical weight of voters within industries. When

identity politics prevail, by contrast, the ethnic distribution of workers within and across industry

groupings informs optimal policy outcomes. Identity politics influences policy because it polarizes

the identity preferences of voters in groups that have been activated on ethnicity. Politicians, in

turn, are able to win more votes by catering economic policies away from groups mobilized on eth-

nicity and toward voters in other groups because these latter voters are more sensitive to marginal

changes in policy. In effect, while the decision to mobilize voters on identity depends closely on

economic policymaking dynamics, the choice to set equilibrium economic policies is contingent

on ethnic mobilization dynamics.

2.1 Setting

Consider a domestic economy in which each individual, i, is born into one of two ethnic groups

{a,b}, which partition society and which are indexed by j. There are two office-motivated political

parties {A,B} that compete for office. Each individual is employed by one of two industries

{1,2}, indexed by k, and earns a wage, πk, that is a function of k’s profitability.17 Industries have

competing preferences over the price on 1’s good, such that a higher price for 1 is detrimental to

the profitability of 2. For example, if 1 represents steel manufacturers, 2 could be any of a host

of downstream industries such as construction or automobiles that rely on steel as an intermediate

input during the production process.18 More generally, 2 could represent “consumers” in society,

who are adversely affected when they must pay higher prices for protected goods. Each worker

falls within one of four ethnicity-industry combinations (see Figure 1). Define α as the proportion

17Although wages can in reality be determined by a number of factors, including workers’ opportunity costs, myapproach follows the consistent finding from the labor economics literature that the level of wages within a sectorincrease in response to increases in the sector’s profitably (Blanchflower, Oswald and Sanfey 1996).

18Alternately, 2 might produce a good that is complementary to 1, such that a higher price for 1’s product dampensthe demand for 2’s good.

7

of 1 that is composed of a and β as the proportion of 2 that is composed of a.19 If the proportion

of the total population employed in 1 equals n, then let λ = nα +(1− n)β equal a’s share of the

population. Therefore, b’s share of the population is simply 1−λ .

2.2 Voter Utilities

The government is considering a tariff, τ ∈ [0,1], on 1’s product. Although 1 prefers a higher tariff

in order to exclude international competitors from the domestic market, 2 prefers a lower tariff.20 I

assume that the marginal gain for 1 from an increase in the tariff is smaller when wages are higher,

and that the marginal loss for 2 from this tariff change is larger when wages are lower.21 Represent

the economic payoff for a voter in industry k as vk(τ) = πk(τ).

Individuals can also derive an identity-related utility when a party that represents their ethnic

group is in power.22 I represent this non-economic preference as σi j, which I define as the utility

that voter i of ethnicity j receives when party A is in power. The parameter σi j can take both

positive and negative values, with positive values indicating favorability toward A, negative values

19Consequently, (1−α) is the proportion of 1 that is composed of b, and (1− β ) is the proportion of 2 that iscomposed of b.

20Thus, wages for 1 (π1(τ)) are increasing in the tariff, while wages for 2 (π2(τ)) are decreasing in the tariff.21Formally, wages for 1 are concave (π ′

1(τ)> 0 and π ′′1 (τ)< 0), while wages for 2 are convex (π ′

2(τ)< 0 andπ ′′

2 (τ)> 0). This assumption is based on the intuition that individuals derive greater utility when their wages increasefrom, for example, $1 to $2 than when their wages increase from $100,000 to $100,001. Similarly, a decrease in wagesat lower wage levels is more harmful than a decrease in wages at higher wage levels.

22My setting builds upon the baseline probabilistic voting model. See, Persson and Tabellini 2000, 51-58. See also:Ballard-Rosa 2014.

8

indicating favorability toward B, and zero indicating neutrality. I assume that σi j has a identity

group-specific uniform distribution that is centered around zero when politicians do not play the

identity card. Formally, σi j ∼U [− 12ϕ j ,

12ϕ j ], where j ∈ (a,b). This assumption attempts to approx-

imate a world in which voters on average are neither more nor less likely to vote for a politician

based on identity-related prerogatives, which happens when identity is not at stake in the political

domain. In such a world, elections are simply contested on economic policies. One can interpret

ϕ j as the density of the identity bias of members of different groups. I assume that this density

does not vary across individuals of different ethnic groups (i.e., I assume that ϕ a = ϕ b = ϕ ) when

identity is not salient in the electoral arena.

Additionally, all voters in the electorate might on average also be biased toward one candidate.

This bias can be conceptualized as the valence or overall relative popularity of a particular candi-

date or party in the electorate. The parameter δ , which can also be positive or negative, captures

this population-wide preference by measuring the relative popularity of party A in the entire pop-

ulation. One way to interpret δ is to consider it an indicator that captures the effects of scandals

or other types of unexpected news that increases the popularity of one candidate, while reducing

the popularity of the other. Candidates cannot control this average bias in the electorate prior to an

election, but they know the probability by which a scandal may occur. In expectation, this prob-

ability is simply zero (i.e., δ = 0), indicating that candidates who enact identical policies have an

equal probability of winning the election. Following the literature, I assume that δ ∼U [− 12ψ , 1

2ψ ].

After an election, voter i in industry k and ethnicity j receives the following payoffs:

ui jk(.) =

πk(τA)+σi j +δ i f Awins

πk(τB) i f Bwins.(1)

2.3 Strategic Behavior of Politicians

Politicians in my framework are standard Downsian politicians who only care about winning of-

fice. They obtain a certain amount of utility from holding office, and no utility otherwise. Put

9

differently, politicians care neither about the policy that gets implemented nor about the identity

groups that they represent.23 I now draw on insights from the scholarship on ethnic politics, which

argues that politicians can strategically manipulate identity in the electoral arena for self-serving

electoral purposes, for example, by acting as “identity entrepreneurs.”24 I incorporate the politi-

cian’s strategy of mobilizing voters on ethnicity into my theoretical framework. By playing the

identity card, politicians can manipulate the relative salience of identity. For example, a politi-

cian can deliver an incendiary speech that extolls the superiority of a particular ethnic group, or

highlights the threat of a cultural out-group, or even incites ethnic riots. These and other forms of

ethnic mobilization strategies are commonly observed in electoral settings dominated by identity

politics, and resonate closely with constructivist theories of identity.25

I argue that playing the identity card is at its core a strategic political decision:26 while mobi-

lizing voters on identity can reap certain electoral benefits for politicians, it also triggers explicit

political costs. The benefit of playing the identity card is that it increases the politician’s average

favorability along the dimension of identity among voters belonging to the courted ethnic group.

By triggering a sense of ethnic solidarity or a heightened threat from an ethnic out-group, politi-

cians are able to shift in their favor the average identity bias of individuals within the group. Ethnic

favoritism can be a result of a number of factors. Individuals might, for instance, look at their co-

ethnics as political guarantors who safeguard the interests of their community in the political arena.

More broadly, this assumption attempts to capture the observation that when identity is primed, in-

dividuals become more likely to favor ethnic representatives in the political arena.27 I label this

the “ethnic electoral bounce” effect, as it shifts the mean popularity level of politicians by drawing

individuals closer to their ethnic representatives. Conversely, when a politician rallies one ethnic

group against another, members of the latter group are less likely to favor the politician on the

23Note that this approach differs from Roemer (1998) and Roemer, Lee and Van der Straeten (2007), were partieshave policy preferences—for example, left-leaning parties favor redistribution while right-leaning parties do not—and,in turn, seek to maximize the welfare of their constituents.

24Brass 1997; Varshney 2002; Wilkinson 2004.25Corbridge and Harriss 2000; Jaffrelot 1996; Wilkinson 2004.26This approach builds upon and extends the argument presented in Wilkinson 2004.27See, e.g., Wilkinson 2004.

10

grounds of identity.

Assumption 1 The identity card increases (decreases) the politician’s average favorability alongthe dimension of identity among voters that are courted (attacked) by the politician.

I formalize this implication by allowing the identity card to alter the value of σi j. Define the

identity card as C and the altered identity parameter as σi j. When neither candidate wields the

identity card, C = 0, else C = 1. If C = 1, the expected identity bias of a member of group a

increases by c, while the expected identity bias of a member of group b correspondingly decreases

by c. In other words, members of a are more likely on average to favor candidate A, while members

of b are more inclined on average to vote for B. If any candidate plays the identity card, therefore:

σi j =

σi j +1(C = 1)c i f j = a

σi j −1(C = 1)c i f j = b.(2)

Many scholars have underscored the electoral bounce that politicians receive by playing the

identity card. By contrast, the costs of the identity card have received relatively lesser attention.

I argue that when politicians trigger identity politics in the political domain, they polarize mem-

bers of the courted ethnic group on the dimension of identity. Consider how the identity card

shifts political preferences at both ends of the distribution of identity-related preferences within a

group that is mobilized on ethnicity. On the communitarian end of the spectrum, voters with more

fundamentalist preferences are more likely to favor the candidate on identity grounds when the

candidate promotes their ethnicity. On the secular end of the spectrum, by contrast, progressive

voters are alienated by politicians who engage in communalism. In India, for example, progressive

voters, political pundits, and media commentators are quick to denounce acts of fundamentalism

by politicians; disdain for ethnic politics is voiced by many voters, even in settings where ethnic

parties draw large support. Put simply, while the identity card might make a politician more favor-

able to voters with communitarian leanings, it nonetheless distances the politician from progressive

voters in the electorate. I label this the “identity dispersion” effect, and define it as an increase in

the variation of the identity bias among co-ethnics who are mobilized on identity.

11

Assumption 2 The identity card polarizes mobilized voters along the dimension of ethnicity.

I formalize this effect by allowing the identity card to increase the variance of σi j by decreasing

the density of ϕ j.28 Define the new density of the identity bias as ϕ j. When ϕ j is smaller, identity

preferences are less densely concentrated. Formally, I represent the decrease in the density of σ

when a politician plays the identity card (C) as follows:

ϕ j = ϕ j −1(C = 1)d. (3)

Notice that while the “ethnic electoral bounce” shifts preferences among members of both

ethnic groups, I restrict the “identity dispersion” effect to only the members of the courted ethnic

in-group. This captures the intuition that members of a threatened out-group—while growing

distant from their political tormentors—are not going to favor politicians who discriminate against

them. The dispersion in identity preferences both toward and against the communal politician is

thus a phenomenon that prevails only in the group mobilized on ethnicity. I subsequently show

that the “identity dispersion” effect is a key mechanism underpinning my model; in particular,

the increased variance in the identity bias among members of an ethnic group makes this group

relatively less sensitive to changes in economic policy.

Do ethnic politics alter group-wise political preferences in ways described by Assumptions 1

and 2? Several forms of evidence suggest that voters belonging to victimized communities respond

differently to ethnic politics compared to voters belonging to communities that are privileged by

ethnic politicians. India’s minority Muslim community, for example, is typically at the receiving

end of injustice associated with communal politics. That Muslims tend to vote en bloc against

Hindu-nationalist parties when political threats to their identity emerge is well documented.29

Qualitative evidence supports this claim. Following Gujarat’s Hindu-Muslim riots discussed ear-

lier, Muslims largely consolidated their votes in favor of the party that would most likely defeat

28Recall that σi j ∼U [− 12ϕ j ,

12ϕ j ].

29Wilkinson 2004; Nellis, Weaver and Rosenzweig 2015; Gaikwad and Nellis 2015. See also Bharucha (2003,557), which notes a “fluctuating polarisation of the electorate in terms of identity-based politics” in India.

12

the Hindu-nationalist BJP (in this case, the Congress). In a detailed case study of Modasa district,

Shah (2010) found that “Muslims, irrespective of their social and economic stratification, voted for

the Congress,” even in constituencies where Muslims ran as independent candidates, because (in

the words of one interviewee), “this party is good for minorities" and it “treats everyone equally.”30

But this was not true of Hindus. For some Hindu voters, “Hindutva was important”; one respon-

dent said, “I am for BJP, the party of Hindus.”31 Yet for other Hindus, the BJP had tarnished its

image by participating in the riots. For example, one voter stated:

“For the first time I voted for the BJP in 1995 because the Congress was rotten and theBJP promised to be a party with difference. I again voted for it in 1998 ... But afterseeing the 2002 riots, I realised that the BJP was more dangerous than the Congress. Ithen voted for the Congress in the 2002 elections and this time also.”32

Anecdotal evidence thus points to a polarization of preferences among Hindu voters. Moreover,

as expected, less ethnocentric voters are more likely to abandon ethnic parties; survey evidence on

voting preferences in post-riots Gujarat found that among Hindus, “a majority of those who had

low communal consciousness” favored the Congress.33

Nationally representative data on voting patterns from India reflect similar trends. Evidence

from several rounds of Indian National Election Studies (NES) spanning the years 1967 to 2004

suggests that ethnic politics alter group-wise political preferences in ways described by my theoret-

ical assumptions.34 In each nationally representative survey, voters were asked to name the party

for which they voted. Figure 2 plots the average and standard deviation of support for each elec-

tion’s Hindu-nationalist (“Hindutva”) parties, which have historically drawn support from Hindu

voters by promulgating pro-Hindu ideology and by stoking anti-Muslim threats.35 A stark diver-

gence emerges when we analyze Hindutva party support among Hindu and Muslim voters. In each

30Shah 2010, 59.31Shah 2010, 59.32Shah 2010, 59. These interviews led the author of the study to conclude that “Modassa town has been polarised

socially and politically” (Shah 2010, 59).33Shah 2002, 4843.34The 1967-1985 NES data are publicly available at ICPSR. I thank Pavi Suryanarayan for sharing the NES data

for 1999 and 2004.35For a detailed discussion of Hindutva politics, see: Jaffrelot 1996; Wilkinson 2004.

13

election, pro-Hindu parties are on average more favorable among Hindu voters than among Mus-

lim voters.36 Likewise, preferences toward pro-Hindu parties are relatively more dispersed among

Hindu voters than among Muslim voters.

In sum, Assumptions 1 and 2 imply that when A plays the identity card, the identity-related

preferences of voters in group j = a are σi j ∼U [− 12(ϕ j−d)+c, 1

2(ϕ j−d)+c], while those of voters in

group b are σi j̄ ∼U [− 12ϕ j̄ − c, 1

2ϕ j̄ − c].37 Voter utilities when identity politics are present depart,

in turn, from settings where identity politics are not salient. Members of group j = a derive

a utility, ui jk(.) = πk(τA) + σi j + δ , when A wins; the utility of members of b, meanwhile, is

ui j̄k(.) = πk(τA)+σi j̄ +δ .

36The increasing support over time reflects the steady demise of India’s “one party” system, which was dominatedby the (secular-minded) Indian National Congress for several decades following independence.

37Correspondingly, when B plays the identity card, the identity-related preferences of voters in group j = a areσi j ∼U [− 1

2ϕ j + c, 12ϕ j + c], while those of voters in group b are σi j̄ ∼U [− 1

2(ϕ j̄−d)− c, 1

2(ϕ j̄−d)− c].

14

2.4 Timing

The timing of the game is as follows:

1. The two candidates, A and B, decide simultaneously and non-cooperatively whether or not toplay the identity card. Both candidates know voters’ policy preferences, and the distributionsof σi j and δ , but not their realized values.

2. A and B simultaneously and non-cooperatively propose a “tariff rate”, τA and τB.

3. The actual value of δ is realized and uncertainty is resolved.

4. Elections are held.

5. The winning candidate implements the announced platform.38

I focus on sub-game perfect Nash equilibria (SPNE) and solve by using backwards induction. The

SPNE is a pair of tariff policies (τA and τB) and decisions about whether to play the identity card

(CA and CB). Each candidate’s tariff policy maximizes her utility given the other candidate’s tariff

policy as well as the candidates’ respective decisions to invoke identity in the first stage of the

game. Additionally, a candidate’s choice to invoke identity in the first stage is the best response to

the other candidate’s choice, and is sequentially rational.

2.5 Setting of Economic Policy

Candidates make their decisions to set a tariff policy at stage (2) by evaluating how to maximize

their respective probabilities of winning the election, which, in turn, depend on their overall vote

shares. In order to ascertain the tariff policy that maximizes candidates’ probabilities of win-

ning the election, I identify the swing voter in each ethnicity/industry group combination in the

electorate. The swing voter in group j and industry k is the voter whose identity bias, given the

candidate’s proposed tariff policy, makes her indifferent between both parties. As I show below,

the swing voters and, consequently, policymaking dynamics differ in the absence and presence of

identity politics.38Stage 5 assumes, like standard theories of probabilistic voting, that parties do not deviate from their policy

platforms once elected to office. This assumption captures the notion that parties wish to retain credibility for futureelectoral campaigns.

15

Identifying Swing Voters Equation 1 shows that when identity politics are not salient, a voter

chooses A over B if σi j +δ > πk(τB)−πk(τA). Thus, the swing voter, σ̂ jk, in this case is simply:

σ̂ jk = πk(τB)−πk(τA)−δ . (4)

Put differently, B should capture the votes of any individual i in group j and industry k whose

identity bias is less than the identity bias of the swing voter (σi jk < σ̂ jk), while A should win the

vote of the remainder of the group. By contrast, when identity politics enter the electoral arena,

each ethnic/industry group faces a different swing voter:

σ̂ jk =

πk(τB)−πk(τA)− c−δ f or j = a

πk(τB)−πk(τA)+ c−δ f or j = b.(5)

The above equation captures changes in the average favorability of politicians that relate to

Assumption 1. Once the political arena cleaves along identity lines, voters in group a become on

average more partial to candidate A, while b group voters derive diminished identity-related utility

from A in office.

Economic Policy in Absence of Identity Politics I now calculate a candidate’s vote share, in

order to study how the candidate chooses an economic policy that maximizes her probability of

winning the election. Let VB equal B’s total vote share. VB depends on F(.), the fraction of

individuals in group j and industry k who weakly prefer candidate A, and can be calculated by

summing across the population shares of voters in each ethnicity/industry subgroup.39 Substituting

with voter payoffs, we see that B’s vote share is:

VB = nϕ [π1(τB)−π1(τA)]+(1−n)ϕ [π2(τB)−π2(τA)]−ϕδ +12. (6)

39Observe that VB = nαF(σ̂a1)+ n(1−α)F(σ̂b1)+β (1− n)F(σ̂a2)+ (1−β )(1− n)F(σ̂b2). Given the distribu-

tional assumptions on σ , F(σ̂ jk) =σ̂ jk+

12ϕ j

12ϕ j +

12ϕ j

= ϕ j(σ̂ jk +1

2ϕ j ).

16

The terms in front of π1 and π2 represent the ethnicity-weighted shares of the population in

industry 1 and industry 2, respectively. Note that because ϕ a = ϕ b = ϕ , α and β cancel out;

in other words, when identity politics are not salient, the impact of candidates’ proposed tariff

policies on their expected vote shares is not affected by the ethnic distribution of voters across

industries. The probability that B wins the election is simply the probability that VB(.) ≥ 12 . Let

vB = Prob[VB ≥ 12 ] represent this probability. The probability that A wins the election is, in turn,

1− vB. Given the distributional assumptions on δ , vB can be calculated as:

vB =12+

ψϕ{nϕ [π1(τB)−π1(τA)]+(1−n)ϕ [π2(τB)−π2(τA)]}. (7)

Candidates select a tariff policy that maximizes their respective probabilities of winning the

election, taking the other party’s tariff policy as given. In equilibrium, at stage (2), both parties

converge to the same tariff policy. To observe this policy convergence formally, take the derivative

of vA and vB (A and B’s respective probabilities of winning the election) with respect to τA and τB.

The derivative provides an estimate of each candidate’s best response to the policy proposal of the

other candidate. Because τA and τB always enter vA and vB with opposite signs, both candidates

always face the same optimization problem. Therefore, A’s policy platform is identical to B’s

policy platform in equilibrium.

Does the group-wise distribution of workers affect tariffs in equilibrium? We can evaluate vB

by studying how changes in τ affect the expected probabilities of winning the election for both

parties. Party B raises tariffs only if this increases its probability of winning. Take the derivative

of vB with respect to τB, and setting it equal to zero, obtain:

π ′1(τB)

π ′2(τB)

= (1− 1n). (8)

The above equation shows that equilibrium tariffs are influenced by the numerical strength of

workers within industries.40 The left hand term can be interpreted as the ratio of the impact of

40Notice that Party A faces an identical optimization problem. A raises tariffs only if this increases its probabilityof winning. To study this condition, we can take the derivative of 1− vB with respect to τA, and set it equal to zero,

17

τB on the utility of workers in 1 relative to workers in 2. When n (the proportion of voters in

1) increases, τB increases.41 This is an intuitive result, capturing the observation that politicians

target economic policies toward voters that belong to the numerically stronger industry group. The

reason that α and β do not affect equilibrium tariffs is that the impact of α and β is mediated by ϕ a

and ϕ b. When identity is not salient in the electoral arena, ϕ a = ϕ b = ϕ . In these cases, the terms

containing ϕ a and ϕ b in the equation cancel out, such that an increase or decrease in either α or β

has no impact on τB. The intuition behind this result is that when marginal changes in economic

policy affect voters of each ethnic group equally, the politician cannot improve her vote share by

offering a tariff policy that differentially benefits members of separate ethnic group.

Economic Policy in Presence of Identity Politics Now consider the case where only A plays C

in the first stage of the game. In this case, the swing voter shifts within each ethnic group because

voters in a (b) become on average more likely to favor to A (B) on the identity dimension. In order

to calculate the new vote shares of the candidates, substitute F(.) in 6 with the updated distributions

of party bias within each ethnicity/industry voter subgroup. We find that B’s vote share now equals:

VB =12+n(ϕ −αd)[π1(τB)−π1(τA)]+(1−n)(ϕ −βd)[π2(τB)−π2(τA)]− (9)

(ϕ −λd)δ − [λ (2ϕ −d)]−ϕ ]c.

Equation 9 reveals the electoral implications of the identity card. First, notice that after identity

politics enter the electoral arena, π1, π2, and δ are weighted by the population shares and relative

densities of groups a and b, as well as d, the “identity dispersion” effect. In particular, because

obtaining, π ′1(τA)

π ′2(τA)

= (1− 1n )

[βϕa+(1−β )ϕb]

[αϕa+(1−α)ϕb]= (1− 1

n ).41To observe this effect, note that as n increases, the absolute value of the term on the right hand side of the

equation, which is negative, must become smaller. To maintain the equality, the absolute value of the ratio on theleft hand side, which is negative (recalling that π ′

1(τ)> 0 and π ′2(τ)< 0), must also become smaller. This result can

obtain only if the numerator decreases or the denominator increases. Because π ′′1 (τ)< 0 and π ′′

2 (τ)> 0, we see that thenumerator decreases only if τB increases. We also see that the denominator increases only if τB increases. Therefore,as n increases, τB unambiguously increases.

18

ϕ a = ϕ a −d, d decreases the effect of ϕ a and in turn increases the variance of σ among members

of a.42 The presence of d, in effect, incentivizes politicians to consider α and β while evaluating

their proposed tariff policies on expected vote shares. Second, the parameter c, which captures

the “ethnic electoral bounce” effect, also enters the equation and influences the overall vote share.

This occurs because members of a become on average more likely to favor A while members of

b become on average more likely to favor B along the identity dimension. The probability that B

wins the election now becomes:

vB =12+

ψ(ϕ −λd)

{n(ϕ −αd)[π1(τB)−π1(τA)]+ (10)

(1−n)(ϕ −βd)[π2(τB)−π2(τA)]− [λ (2ϕ −d)−ϕ ]c}.

I show subsequently that candidates make the decision to play the identity card by comparing

their probabilities of winning the election in the presence and in the absence of identity politics.

Comparing equations 7 and 10, we see that these probabilities are different. In particular, when

A plays C, B’s probability of winning decreases by the term containing c on the right hand side

of 10. The effect of c is mediated by the share of a in the population (λ ) and by the dispersion

effect, d; these mediating factors determine whether identity politics are electorally profitable. In

equilibrium, at stage (2), both candidates offer the same economic policy. The intuition is similar

to the case in which neither politician played the identity card. Both candidates possess the same

technology for converting policy into vote shares and hence they converge to the same policy

platform. At the equilibrium policies, neither candidate has an incentive to deviate. Taking the

derivative of vB with respect to τB, and setting the resulting expression equal to zero, we find that:

π ′1(τB)

π ′2(τB)

= (1− 1n)(ϕ −βd)(ϕ −αd)

. (11)

42Because only A wields C in equation 9, the dispersion effect prevails among members of group a. When only Bwields C, by contrast, the dispersion effect prevails only among members of group b. When both candidates wield C,the dispersion effect applies to members of both ethnic groups.

19

The above equation shows that the presence of the “identity dispersion” parameter, d, makes

ethnicity salient in the choice of optimal tariffs. As before, τB increases in n. Yet, the politician

must now consider not only n but also α and β while setting tariffs, because marginal changes

in economic policy affect voters in a and b differently.43 Consider an increase in α , the share of

industry 1 that is composed of a, while keeping fixed n (the proportion of the population in 1) and

β (share of industry 2 that is composed of a). This represents an increase in the number of a group

members, relative to b group members, working in 1.44 Note that in this case α increases due to

an increase in the size of group a in the population. In the Appendix (section 7.2), I show that

similar dynamics are at play when we keep fixed the sizes of the ethnic groups, and simply vary

their distributions across industries.

An increase in α increases the overall share of group a members (λ ) in the electorate.45 Hold-

ing all else constant, as α increases, group a’s share in industry 1 relative to its share in the pop-

ulation (i.e., αλ ) rises, because α increases while β remains unchanged. Next, observe that as α

increases τB decreases for all values of α .46 Combined, these changes generate the following com-

parative static: as the share of an ethnic group in an industry increases relative to its share in the

population, the industry is less likely to receive its preferred economic policy. The intuition behind

this result is that identity-related polarization decreases the number of swing voters in the group

mobilized on ethnicity. Because this group now has relatively fewer swing voters, it is less swayed

by marginal changes in economic policy. In this case, because A wielded the identity card, voters

in a are relatively less sensitive than voters in b to changes in economic policy. Therefore, politi-

43On the right hand side, even though ϕ a = ϕ b = ϕ , α and β continue to exert an impact on equilibrium tariffsthrough their effect on d.

44We might observe a rise in α due to a variety of reasons, such as population growth, or immigration inflows, orskills transfers across groups. For instance, a new cohort of college graduates belonging to group a might enter thework force and join industry 1.

45I show later that this increase in the overall weight of group a generates greater pressures on candidate A toengage in identity politics.

46This comparative static is driven by a similar logic to the case in which identity politics is absent in the electoralarena. Note that as α increases the absolute value of the term on the right hand side, which is negative because1− 1

n < 0, must become larger. For the equality to be maintained, the absolute value of the ratio on the left handside (which, as before, is negative because π ′

1(τ)> 0 and π ′2(τ)< 0) must also become larger. This effect can obtain

if the numerator increases or the denominator decreases. For the numerator to increase, τB must decrease (becauseπ ′′

1 (τ)< 0). Similarly, for the denominator to decrease, τB must decrease (because π ′′2 (τ)> 0). Therefore, as α

increases, τB unambiguously decreases.

20

cians fashion their economic policy platforms away from industries employing group a workers

and toward industries employing group b workers.47

Figure 3 illustrates this effect by charting the distribution of identity-related (σ ) preferences

for members of group a. The solid lines depict the distribution of σia when identity politics are

absent in the electoral arena. This distribution is simply centered around zero and has a height

that corresponds to the density of ϕ a. In equilibrium, the swing voter is the member of a for

whom σa = −δ . B should capture the votes of all individuals for whom σia < −δ , while A

should capture the remainder. By contrast, the dashed lines illustrate the distribution of σia after

A wields the identity card. We see, first, that the average identity bias shifts to the left. This is

a consequence of the “ethnic electoral bounce,” capturing the insight that members of a are on

average more favorable toward A. Intuitively, because the new swing voter is σa = −δ − c, B

captures the votes of fewer individuals (for whom σia < −δ − c), while A wins the support of

a larger group of individuals. We see, also, that the variance of the identity-related preferences

gets wider (i.e., the “identity dispersion” effect). This occurs because the height of the distribution

decreases to ϕ a = ϕ a −d.

Figure 3 shows how identity politics alters policymaking incentives for politicians. When

identity politics are absent, the larger height of the distribution (ϕ a) results in a greater number

of swing voters in group a who switch their political preferences for small changes in economic

policy. In this case, a marginal change in policy wins the politician votes equaling the portions of

the graph represented by 1 and 2. The lower height of the distribution (ϕ b − d) in the presence

of identity politics, however, indicates that a commensurate change in economic policy earns the

politician fewer votes (equaling the portion of the graph represented by 3). Because group a now

has relatively fewer swing voters, politicians attach lesser weight to this group while deciding

policy platforms. They gain more votes if they target their economic policies away from industries

with relatively larger shares of a.

47A similar logic applies to changes in β . Holding all else constant, as β increases, the overall size of group a in thepopulation increases, and group a’s share in 2 relative to its share in the population increases. In this case, politiciansface fewer incentives to offer industry 2 its preferred economic policy.

21

2.6 Playing the Identity Card

To study the decision to play the identity card, note first:

Lemma 1 Regardless of the decision to play the identity card, tariff policy proposals in equilib-rium converge for both candidates.

Lemma 1 is based on the observation that at stage (2), regardless of whether either, both, or neither

candidate has previously played the identity card, A and B court the expected swing voters in the

electorate. Candidates appeal to the swing voters in each voting bloc in order to maximize their

probabilities of winning the election. Because τA and τB always enter vA and vB with opposite

signs, both candidates face the same optimization problem.48 Therefore, A’s policy platform is

always identical to B’s policy platform in equilibrium. Intuitively, both candidates possess the same

technology for converting policy into vote shares and hence they converge to the same policy.49

48In particular, vA and vB always include the weighted terms [π1(τB)−π1(τA)] and [π2(τB)−π2(τA)].49At these equilibrium policies, neither candidate has an incentive to deviate. Consider, for example, a unilateral

deviation by A in favor of higher tariffs. Although A gains more votes from citizens in industry 1 with this deviation,

22

I now claim that this convergence in candidates’ economic policy platforms in stage (2) con-

verts the game into a reduced form game at stage (1).50 This occurs because candidates evaluate

the impact of identity mobilization on their expected probabilities of winning the election at stage

(1).

At stage (1), A makes the choice to activate identity among members of a, while B makes the

choice to activate identity among members of b. This reflects the intuition that one candidate typi-

cally has a greater advantage over the other in mobilizing voters belonging to a particular identity

group—for example, because the candidate shares the “type” or is a vanguard of the group.51 Can-

didates thus weigh the benefits and costs of wielding the identity card on their respective identity

groups. Because of the “ethnic electoral bounce” effect, each candidate realizes that the iden-

tity card increases average support among in-group members, but concurrently dampens support

among out-group voters. From the point of view of the candidates, therefore, the decision to ac-

tivate identity is closely tied to the number of voters in each group. Groups that have a bigger

share of the population potentially deliver more votes than those with a smaller share of the popu-

lation—and are hence more promising targets of identity mobilization.

Yet, candidates are also attuned to the second repercussion of playing the identity card: identity

dispersion among voters mobilized on ethnicity. Because the dispersion effect does not appertain to

members of the other ethnic group, the distribution of their identity preferences remains constant.

By contrast, in the courted ethnic group, the dispersion effect widens the distribution of identity

preferences. Differences in these distributions affect the rate at which politicians win votes from

members of each ethnic group. A politician who plays C loses voters in the ethnic out-group

(due to the “ethnic electoral bounce” effect) at the same rate as before, because the density of their

identity preferences remains unchanged. However, the politician now gains voters in the mobilized

A loses a commensurate number of votes from those in 2. Because A and, similarly, B are not be able to improve theirvotes from deviating, their optimal policy platform in equilibrium remains identical.

50In equilibrium the terms [π1(τB)−π1(τA)] and [π2(τB)−π2(τA)] cancel because both candidates offer the sametariff policy. Put differently, because τA and τB subsequently converge, they do not influence the candidates’ decisionsto play the identity card in stage (1).

51A characteristic feature of ethnic politics—as opposed to politics over economic policy—is that it tends to be“sticky.” Once candidates mobilize particular ethnic groups based on identity, it is difficult for them to switch alle-giances and mobilize members of ethnic out-groups.

23

in-group (due to the “ethnic electoral bounce” effect) at a lower rate than before, because the

spread of these voters is much wider (i.e., because of the “identity dispersion” effect).52

At stage (1), then, the asymmetry between the dispersion effect in both ethnic groups begins to

bite: Politicians who invoke identity lose voters in the other ethnic group at the same rate as before,

yet win additional voters in their own ethnic group at a lower rate. The greater the dispersion

effect, moreover, the less likely is the politician to wield the identity card. Therefore, the number

of votes gained and lost, the rate at which these votes switch, and the share of ethnic groups in a

constituency are key to understanding the politician’s decision to invoke identity.

The candidate who faces an advantage in courting the larger group thus decides whether to

activate identity after considering the size of the ethnic group and the dispersion effect of identity

politics. The second candidate faces a more circumscribed decision. She can try to activate identity

among her group members, but faces the prospect of losing more support from members of the

majority-group. Moreover, once identity politics have been triggered by the first candidate, the

second candidate reaps an electoral windfall among members of her group. Playing the identity

card does not gain her additional support from her group, and instead triggers a dispersion effect

among these voters. Thus, once the candidate who has an advantage in courting the larger group

activates identity, the second candidate is better off refraining from identity mobilization.

To observe these dynamics formally, consider the case (Case 1) involving A’s decision to play

C if B does not play C. The Appendix (section 7.1) discusses each of the alternate cases (Cases

2–4). A plays C if it increases her probability of winning the election (vA = 1− vB). When neither

candidate plays C, vB equals:

vB =12+

ψϕ{nϕ [π1(τB)−π1(τA)]+(1−n)ϕ [π2(τB)−π2(τA)]}. (12)

Because both candidates converge to the same policy platform in the second stage of the game,

52To fix ideas, consider the case in which the dispersion effect is so large that the density of identity preferencesamong the courted ethnic group reaches zero. The distribution of identity preferences among this group of voters is,in effect, infinite. The politician therefore is unable to win any new voters in her own ethnic group. She continues tolose, however, votes among out-group members.

24

τA and τB cancel, and the equation simplifies to 12 . This reflects the intuitive result that in the

absence of identity politics, each candidate has an equal probability of winning. By contrast, when

only A plays C, vB equals:

vB =12+

ψ(ϕ −λd)

{n(ϕ −αd)[π1(τB)−π1(τA)]+(1−n)(ϕ −βd)[π2(τB)−π2(τA)]−

[λ (2ϕ −d)−ϕ ]c}. (13)

A’s equilibrium probability of winning now depends on the “ethnic electoral bounce” effect (c),

the “identity dispersion effect” (d), and a’s share of the population (λ ): 12 +

ψ[ϕ−λd] [λ (2ϕ −d)−ϕ ]c.

A plays C if this probability is greater than 12 , which holds if:

[λ (2ϕ −d)−ϕ ]c > 0. (14)

The condition above points to three key determinants that affect A’s decision to play C: (i) c, the

“ethnic electoral bounce” effect, (ii) d, the “identity dispersion” effect, and (iii) λ , a’s share of the

population. For the condition listed above to hold, the product between the c and [λ (2ϕ −d)−ϕ ]

must be positive. We have already assumed that c is positive (see Assumption 1). Intuitively, A

must earn some electoral benefit from playing C in order to make identity politics profitable. Note,

therefore, that because c is positive, the condition only holds if [λ (2ϕ − d)− ϕ ] is also positive.

Thus, both the “identity dispersion effect” and a’s share of the population are consequential in A’s

decision to invoke identity.

Let us evaluate how a’s share of the population (λ ) affects A’s decision. A invokes identity

so long as λ > ϕ(2ϕ−d) . When λ ≤ 1

2 , A does not play the identity card. To observe this result,

consider the case where there is no identity dispersion effect (d = 0). Even in this case, A plays the

identity card only if a’s share of the population is greater than half (i.e., λ > 12 ). The interpretation

of this result is intuitive. When λ ≤ 12 , A should not play the identity card because the loss in

support from b group members offsets the gain in votes from a group members. Observe, next,

25

that when a is the majority group in the population, A’s decision to play the identity card will

depend crucially on d, the identity dispersion effect. For larger values of d, λ must be larger

for A to reap electoral profits from invoking identity. In fact, there will always be some value of

d that will make identity politics unprofitable. Consider the extreme case where there the entire

population comprises a (λ = 1). Even in this case, if the dispersion effect is large enough to drive

the density of identity-related preferences down to zero (d = ϕ ), A does not play the identity card.

This discussion points to a central insight from the model. The identity dispersion effect (d),

along with the ethnic composition of the electorate (λ ), fixes A’s choice to invoke identity in the

electoral arena. Specifically, A only plays the identity card if d < ϕ(2λ−1λ ). If d is greater than

this critical threshold, A simply does not find it advantageous to play the identity card. The critical

threshold for d is determined by λ and ϕ , the density of identity-related preferences. As noted

above, A does not play the identity card if a’s share of the population (λ ) is smaller than or equal

to 12 . But when λ is larger than 1

2 , d must be smaller than a fraction of ϕ for A to play the identity

card. As λ gets bigger and approaches 1, this critical threshold increases. Yet, even when a

comprises the entire population, d has to be smaller than ϕ for the condition to hold; if d = ϕ , A

will not invoke identity.

In short, d (in relation to ϕ ) determines how responsive voters in the ethnically mobilized group

are to economic policy; it captures how voters in the group reward policy with votes during elec-

tions. Even when invoking identity politics is profitable for A, there will be some decision-making

space where A is better off not playing the identity card. Due to the identity dispersion effect, A

finds it more profitable to refrain from identity politics and use the technology of economic policy

to win additional votes. Although the identity card can boost a candidate’s expected vote share in

an ethnic group by shifting c in the candidate’s favor, the identity-related polarization (d) that it

generates can trigger a loss in votes in the other ethnic group. Thus, a politician’s incentives to play

the identity card are going to become smaller as d becomes larger. Similar dynamics are evident

when we consider B’s decision to invoke identity in the electoral arena (see Appendix 7.1).

26

2.7 Discussion

The framework outlined above points to the game’s equilibrium dynamics.

Proposition 1 As the share of an ethnic group in the population increases, politicians face greaterincentives to court voters in this group using the identity card.

First, the choice to play the identity card is influenced by the ethnic makeup of voters in the

population. Intuitively, the returns to playing the identity card directly depend on the proportions

of group a and b in the electorate. Consider A’s choice to invoke identity. At a basic level, A will

play the identity card only if the majority of voters in the constituency belong to group a. If there

are more b voters than a voters, A’s gains from identity mobilization in group a will be offset by

A’s losses from identity mobilization in group b. In cases where there are a majority of a group

voters in the electorate, A finds it more profitable to play the identity card as the share of group a

voters (λ ) increases.

In these cases, the decision to invoke the identity card depends crucially on the identity dis-

persion effect (d). A only finds it profitable to play the card when a’s share of the population is

large enough to outweigh the dispersion costs associated with communal mobilization. Formally,

this occurs when λ > ϕ(2ϕ−d) . Holding all else constant, we see that as the left hand side becomes

larger, the inequality is more likely bind, and A faces greater incentives to play the identity card.

B faces symmetric incentives. B will only play the identity card if there are more b voters than

a voters. In these cases, as a’s population share decreases, b’s population share increases, and B

faces greater incentives to invoke identity. But B’s decision will ultimately depend on the size of

the identity dispersion effect (d). If d is larger than a certain critical threshold, B will not play the

identity card.

In equilibrium, when a’s share of the population is sufficiently large, but less than 1, A plays the

card and B does not play the card. When a’s share of the population is sufficiently small but greater

than 0, B plays the card but A does not. When a’s share of the population is neither sufficiently

small nor sufficiently large, the politicians do not invoke identity in the electoral arena. Formally,

27

when ϕ(2ϕ−d) < λ < 1, A plays the card and B does not play the card. When 0 < λ < ϕ−d

2ϕ−d , B plays

the card and A does not play the card. When ϕ−d2ϕ−d < λ < ϕ

(2ϕ−d) , neither A nor B play the card.

Proposition 2 When d is sufficiently large, identity politics are not profitable.

The discussion above indicates that the identity dispersion effect (d) will ultimately inform the

politician’s choice to invoke identity. The identity dispersion effect plays a central role in the

politician’s decision because of its relationship with economic policymaking. This is a key contri-

bution of my model. The basic intuition here is that the distribution of identity-related preferences

among voters influences the relative importance that voters attach to identity versus economic fac-

tors while deciding whom to vote for in an election. When politicians mobilize groups of voters

on ethnicity, they win more voters among these groups, but they also increase the dispersion of

identity-related preferences among voters in these groups. Consequently, groups mobilized on eth-

nicity have relatively fewer swing voters who will be willing to switch their support for marginal

changes in economic policy. Politicians lose voters in other ethnic groups without triggering a

concurrent decrease in swing voters.

This discussion underlines the fundamental tradeoff faced by office-seeking politicians. There

is always a critical threshold of identity dispersion beyond which the politician will be better off by

not playing the identity card, but by instead winning votes using economic policy. We can observe

these effects by inspecting the conditions listed above. When d = 0, A (B) play C so long as a’s

(b’s) share of the population is greater than half. But as d becomes larger, a much larger proportion

of the population needs to belong to politicians’ preferred ethnic groups for politicians to find

identity mobilization profitable. In this respect, identity politics and economic policymaking are

symptomatic of the same strategic decision faced by office-motivated politicians. As the identity

dispersion effect magnifies, at a certain point it becomes more profitable for the candidate to refrain

from identity politics and to win votes using economic policy.

Proposition 3 When identity politics are present, industries that contain a larger share of an eth-nic group relative to the share of the group in the population are less likely to receive theirpreferred economic policy.

28

This discussion points to the central insight that arises out of my model: identity politics system-

atically alter the dynamics of policy competition. As discussed above, when neither party plays

the identity card, trade policy is set explicitly according to the number of voters in each indus-

try. Because ϕ a = ϕ b when identity is not salient in the electoral arena, equation 8 reduces toπ ′

1(τ)π ′

2(τ)= (1− 1

n); as n becomes larger, tariffs on 1 increase. This result corroborates a sizable find-

ing in the literature that geographically and politically concentrated industries are more likely to

receive their preferred economic policy in the electoral arena (Busch and Reinhardt 1999; 2000;

2005; McGillivray 2004).

When politicians wield the identity card, however, apart from the numerical strength of an

industry, the ethnic distribution of workers within and across industries also influences equilibrium

tariffs. When only A plays the identity card, equilibrium tariffs are characterized by π ′1(τ)

π ′2(τ)

= (1−1n)

(ϕ−βd)(ϕ−αd) . Holding all else constant, we see that an increase in α decreases the equilibrium tariff

levels.53 This indicates that industries that are over-represented with ethnic groups should receive

fewer economic policy benefits, because politicians find it more advantageous to court voters in

these industries based on ethnicity. This result is surprising. Theories of ethnicity and collective

action suggest that ethnic homogeneity increases the likelihood that voters coordinate and receive

policy benefits from the government.54 The literature on ethnic parties also suggests that politicians

are most likely to bestow economic benefits on co-ethnic voters.55 My theory, by contrast, points

in the other direction.

53Note that in my general mode, we can interpret an increase in α as an increase in the share of an ethnic groupwithin an industry relative to its share in the population. As I show in the Appendix (section 7.2), a qualitativelysimilar result obtains if we keep the sizes of ethnic groups fixed and simply alter their distributions across industries.

54Alesina, Baqir and Easterly 1999; Austen-Smith and Wallerstein 2006; Hechter 1974, 1987. Linkages betweenethnic cohesion on the one hand and self-regulation, self-monitoring, trust, reciprocity, and collective action overpublic goods on the other hand are clearly documented in the literature. Habyarimana et al. 2007; Miguel and Gugerty2005; Richman 2006; Robinson 2012. According to prevailing theories, ethnicity can influence collective actioncapabilities if co-ethnics are better able to cooperate, utilize social networks to sanction free riders, or exhibit altruismtoward one another. Habyarimana, Humphreys and Posner 2009.

55According to this line of thought, informational constraints that are endemic in patronage democracies tend to“force voters and politicians to favour co-ethnics in the delivery of benefits and votes” Chandra 2004, 12.

29

2.8 Deriving Testable Hypotheses:

Combining observations from the theoretical framework, I propose the following hypotheses:

Hypothesis 1 Ethnically homogenous industries are less likely to receive their preferred economicpolicies while ethnically heterogeneous industries are more likely to receive their preferredeconomic policies.

Hypothesis 1 flows directly from Propositions 1 and 3. Hypothesis 1 holds that as an industry

becomes more ethnically concentrated, politicians face greater incentives to court the votes of

its workers using identity. But courting voters based on identity makes them less responsive to

economic policy. Therefore, ethnically homogeneous industries are less likely to receive their

preferred economic policy compared to ethnically heterogenous industries.

Hypothesis 2 The presence of elections should strengthen the relationship between the ethnic dis-tribution of workers within industries and industries’ economic policies.

Hypothesis 2 flows from the observation that electoral competition undergirds the key dynamics of

the model. When politicians compete with one another for office, they face the greatest incentives

to engage both in identity politics and in distributional policymaking. While the model’s predic-

tions likely apply to all settings in which politicians face competitive pressures, they should be

heightened during elections.

3 Evaluating Theoretical Mechanisms

3.1 Survey Experimental Evidence from Elected Politicians

My model generates testable predictions that I sought to evaluate via survey experiments on a

random sample of elected politicians in India. My sample frame comprised municipal-level politi-

cians from the country’s 25 largest cities. These politicians lie one level below state representatives

and two levels below federal representatives. Note that although these politicians are responsible

for a wide array of local-level economic policies that have distributive dimensions, they are not

30

responsible for formulating international-level economic policies. Yet, because they serve as on-

the-ground interfaces between voters and broader party organizations, they have deep knowledge

about campaign and electoral mobilization strategies within their own parties and are intimately

involved with election campaigns at all levels. An added benefit of this sample is that since these

politicians are themselves not federal-level politicians, there is less risk that their responses will be

moderated by social desirability bias.

Using a survey firm, I attempted to contact 1,500 politicians by telephone, and was able to get

responses from 420 councilors (generating a response rate of 27%).56 The survey was offered in

Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Oriya, Tamil, and Telugu, depending on

the language preferences of respondents.57

Experiment 1

The first experiment offered respondents the following vignette:

Imagine an election in some other part of the country. Suppose a political candidatewho is contesting the election belongs to a particular caste. In his constituency, [10 /50 / 80] percent of voters also belong to the same caste.58

Respondents were then asked, “how likely do you think it is that the politician will emphasize

his caste background and identity?” Their answers were coded on a four-point scale, from “very

unlikely” (0) to “very likely” (3). A binary choice answer scheme yielded results that were similar

in terms of substantive and statistical significance.

This experiment was designed to test a key prediction of my model, namely, that as the propor-

tion of an ethnic group (α) increases within a constituency, the politician who has an advantage

in mobilizing that ethnic group by emphasizing identity will face greater incentives to engage in

ethnic politics (Proposition 1). As Table 1 shows, this is indeed the case. When the relative size

56I scraped politicians’ telephone numbers from the websites of the municipal corporations, where they are publiclydisplayed.

57The surveys were translated and back-translated to ensure consistency across languages.58The reference to an election in a distant location is designed to increase the likelihood of honest responses from

survey participants.

31

of an ethnic group increases, holding all else constant, co-ethnic politicians are significantly more

likely to play the identity card during electoral campaigns.

Experiment 2

Next, I sought to examine whether the invoking of identity by one politician creates strategic

incentives for the opposition politician to target voters with economic policy benefits. In the second

experiment, I presented the elected representatives in my sample with the following vignette:

Imagine an election in some other part of the country. There is one major caste groupin the constituency. The first political candidate belongs to this caste, [and has re-peatedly / but has not at all] emphasized his caste and identity background duringthe election. Meanwhile, the second political candidate has promised to provide votersan economic policy benefit if elected.

Following the vignette, respondents were asked, “how likely do you think it is that voters would

choose the second candidate based on the promised economic benefit?” Similar to the previous

experiment, responses were coded on a four-point scale, from “very unlikely” (0) to “very likely”

(3). I obtained substantively and statistically similar results when analyzing responses to a binary

choice version of the answer scheme.

Note that this vignette closely approximates the setting of my model. After signaling that one

ethnic group is in the majority in the constituency, I experimentally manipulate whether a co-ethnic

representative has invoked the identity card during an electoral campaign. My goal is to evaluate

32

the “knock on” effect of identity mobilization on politicians’ strategic incentives to target voters

using economic policy. Respondents are asked to gauge the likelihood that the other candidate will

reap electoral dividends by advancing an economic policy platform. This central mechanism of

my model finds strong support in the experiment. Table 2 shows that once one candidate invokes

identity, the other candidate is better off winning votes with policy. This provides evidence in

support of Proposition 3.

3.2 Survey Experimental Evidence from Trading Firms

I next sought to test the empirical implications of my theoretical model on a random sample of

domestic importing and exporting firms in India. These firms are primarily engaged in international

trade, and are thus closely attuned to the political dynamics surrounding trade policymaking. My

population of interest was all firms listed in the Government of India’s Directory of Importers

and Exporters. India’s Ministry of Commerce and Industry has published this list of firms since

1919 in order to make available information that can facilitate trade and commerce between India

and the rest of the world, and the Directorate General of Commercial Intelligence verifies the

financial standing and credibility of all firms that enter the database. My survey team scraped the

details of all 8,485 firms that are listed as either importing or exporting firms in this Directory and

then attempted to contact approximately 1,000 randomly selected firms on this list. We requested

interviews with either the owners or executive-level managers in the firms. Respondents were

33

provided the following experimental vignette:

During elections, politicians sometimes try to win votes from workers by promisingeconomic benefits. Other times, politicians try to win votes by making religion orcaste appeals. Imagine there is an industry that employs a large number of workers.These workers [mainly belong to one particular religion and caste/ belong to manydifferent religions and castes].

Respondents were then asked: “If you had to guess, do you think that politicians will be more likely

to try and win votes from these workers by promising economic benefits or by making religion or

caste appeals?” Responses were coded 0 (promise economic benefits) or 1 (emphasize religion or

caste background). We also collected ordered responses to this question, which yield qualitatively

similar results.

This experiment provides a simple and straightforward test of my key theoretical hypothesis

(Hypothesis 1) that politicians court workers in ethnically homogenous industries using identity

politics, but target favorable economic policy to workers in ethnically divided industries. I find

strong support for this this hypothesis. Just by switching whether workers in an industry belong

to “one particular” ethnic group versus “many different” ethnic groups, owners and managers of

trading firms in India expect that politicians will swap their electoral policies from courting workers

using identity politics to courting workers through preferential economic policies.

34

4 Illustrative Examples

The insights generated by my model also accord with observed political mobilization strategies in

real-world electoral campaigns. My theory provides a useful lens to interpret the rise of the Shiv

Sena party and the proliferation of identity politics in Mumbai and the broader state of Maharash-

tra, India. The creation of ethnically homogenous constituencies created incentives for the Shiv

Sena to wage election campaigns based on powerful identity appeals. Additionally, the Shiv Sena’s

mobilization strategies closely mirror the predictions of my theory. The party mobilized workers in

ethnically homogenous industries based on identity, but won votes from workers in ethnically het-

erogenous industries based on protectionist economic appeals. Next, I show that this strategic use

of identity to mobilize voters belonging to ethnic in-groups on the one hand and economic policy

to mobilize voters belonging to ethnic out-groups on the other hand is a recurrent ploy employed

by many ethnic parties—across geographical settings and time periods in India.

4.1 Shiv Sena’s Mobilization Strategies

The Shiv Sena, along with its associated political offshoots such as the Maharashtra Navnirman

Sena (MNS), is a prominent ethno-linguistic nativist party that was formed in 1966 in Mumbai

(then Bombay) and that has since controlled city and state politics for long stretches of time.59

Named after an early-modern regional ruler, the party has consistently aimed “to safeguard the

welfare” of the ethnically dominant Marathi speakers.60 The party has regularly played the identity

card against southern Indians, Gujaratis, Muslims, and other minority religious groups in the city.61

Its activists orchestrated riots in Bombay as early as 1969, for example,62 and volunteers associated

with the party participated heavily in the deadly Hindu-Muslim riots of 1992 and 1993, when

59Weiner 1978; Katzenstein 1979.60Weiner, 1978; Masselos, 1994; Pashlikar, 2004. Shiv Sena Speaks (1967), the official statement of the movement,

declared: “The idea of having Linguistic States has its origin in the assumption that a member of a linguistic group willhave greater opportunities for full-fledged development in his linguistic State. They will have benefits proportional totheir numerical strength. They should have their due share in the services, administration, trade, commerce, industry,education and so on.”

61Talwalker, 1996; Billimoria-Zenieris, 1997, 130.62Lele, 1995; Joshi, 1968, 975.

35

approximately 1,000 people were killed, and entire neighborhoods were set on fire.63

Rise of Ethnic Politics What explains the timing of the rise of the Shiv Sena in the mid-1960s?

The answer in large part lies in electoral redistricting changes implemented by the national govern-

ment that dramatically altered the demographic weight of Marathi-speaking voters in state-level

politics. Boundary delimitations implemented in the early 1960s converted native Maharashtri-

ans from a minority group—they represented roughly 40% of the population of Bombay city and

less-than-half of the population of Bombay state at independence—into the state’s overwhelming

majority group. Once Maharashtrians became a politically powerful vote bank, appeals aimed at

enhancing their ethnic status became a lucrative electoral strategy for politicians.

At independence in 1947, the multi-ethnic colonial territory of the Bombay Presidency was

reorganized into the state of Bombay, comprising regions of present-day (Marathi-speaking) Ma-

harashtra, (Gujarati-speaking) Gujarat, and (Kannada-speaking) Karnataka. Following the State

Reorganization Act of 1956, which demarcated large portions of India along linguistic lines, the

Kannada-speaking southern districts were transferred to Mysore State. Bombay State was retained

as an explicitly bi-lingual entity, with Gujarati-speaking districts in the north, Marathi-speaking

districts in the south, and the city of Bombay serving as a joint capital for both sets of districts.

As calls for further linguistic redistribution gained steam, the city’s sizable Gujarati population

and industrial interests lobbied the national government against redistricting, expressing a concern

that the interests of non-Marathi groups would systematically be underrepresented in any Marathi-

dominated state apparatus.64 In 1960, however, Bombay State was dissolved and partitioned along

linguistic lines, with Gujarat claiming the Gujarati-speaking districts and Maharashtra claiming

the Marathi-speaking regions, along with the city of Bombay.

Bombay city, which continued to retain a multi-ethnic population, was transformed overnight

63Masselos 1994; Gaikwad and Nellis 2017.64Describing the period prior to the partition of Bombay State into Gujarat and Maharashtra, Lele (1995) writes,

“The struggle for the city of Bombay brought to the surface the contradiction between the dominant interests inagriculture (the rich and middle farmers of Maharashtra) and those in industry (the non-Marathi commercial andindustrial capital), concentrated in Bombay at this stage but with close links to local commercial capital in ruralwestern Maharashtra.” Lele, 1995, 1521.

36

into the capital of an ethnically dominated Marathi-speaking state. It was precisely against the

backdrop of this increased Marathi-language “homogenization” that the Shiv Sena party rose to

power as an ethnic party in Bombay. As Billimoria-Zenieris (1997) observes:

Until independence in 1947 Maharashtrians in Bombay had been relegated to subor-dinate economic and political roles. Since then the division of the old Bombay Stateinto the separate states of Maharashtra and Gujarat in 1960 boosted the status of Ma-harashtrians, and although Maharashtrians did not succeed to positions of economicdominance, they did gain instant control of the state government. This new politi-cal status released expectations about the prospective position of the Maharashtriancommunity in Bombay to which the Shiv Sena’s emergence can be traced.65

Similarly, Joshi (1968) argues that “the trade, commerce and industry of the city have always

been in the hands of non-Marathi communities. But since the formation of the unilingual state

of Maharashtra, presumably there has been a sharp rise in Marathi economic aspiration whose

non-fulfillment has produced frustration and bitterness...The phenomenon of the rise of the Shiv

Sena and its xenophobia towards South Indians become quite intelligible when viewed in light of

this ‘model’ of the social context.”66 These political developments fit well with my theoretical

prediction (Proposition 1) that as electorates become more ethnically homogeneous (i.e., as α

increases), politicians face greater incentives to court votes using the identity card. Following the

creation of the more relatively homogenous linguistic state of Maharashtra, the Shiv Sena began

engaging profitably in identity politics.

Ethnic Politics and Economic Protectionism The Shiv Sena’s specific mobilization strategies

also varied across economic groups in line with my theory’s predictions pertaining to ethnic di-

versity. The party’s main electoral support bases in the city of Bombay were both middle-class

Maharashtrian and non-Maharashtrian voters on the one hand, and working-class Maharashtrian

voters on the other hand.67 The occupational profiles of these two voting blocs were very different.

Middle-class Maharashtrians were employed in industries such as chemicals, pharmaceuticals,

65Billimoria-Zenieris, 1997, 126. See also Katzenstein, 1979.66Joshi, 1968, 969. See also Patel, 2003, 14.67Katzenstein, 1979.

37

and insurance. These industries, however, were populated with workers belonging to different eth-

nic groups hailing from South India and Gujarat.68 The overall share of Maharashtrian workers

in ethnically diverse industries was far below their share of the population.69 The Shiv Sena en-

ergized these ethnically diverse industries based on promises of economic protectionism. Voters

belonging to these groups greatly preferred protectionist policies and “subscribed almost unani-

mously to the extension of quotas for local residents in universities, government housing, and both

skilled and unskilled jobs.”70 The Sena pressed for, and adopted, a number of preferential policies

such as requiring public and private employers to reserve jobs for local residents.71 In line with

my theory, additionally, the Sena’s middle-class electoral bases did not cleave according to ethnic

lines. These voters were not polarized along the identity dimension, and instead voted for both

ethnic and non-ethnic parties in equal measure.72 Importantly, the Shiv Sena courted the votes of

non-Maharashtrians such as South Indians in these ethnically diverse industries and trade unions.

Gupta (1977, 297) writes, for example, that “because of the Shiva Sena’s work in the corporation,

trade union and shekhas, the Shiva Sainiks have come in contact with people from various back-

grounds and communities." Consequently, party activists began campaigning for ethnic out-group

votes among these groups. In the 1971 election, the Shiv Sena backed General Cariappa, a South

Indian, who was running for office; during the election, party activists “circulated pamphlets in

Malayali to win the support of migrants from Kerala.”73 This mobilization strategy reaped large

dividends. Survey evidence on voting patterns shows that South Indian voters supported the Shiv

Sena in large numbers.74

Yet, an entirely different mobilization strategy is apparent in the Sena’s attempts to court votes

among working-class citizens. These workers were typically employed in industries such as tex-

68Katzenstein, 1979, 63-69.69Katzenstein, 1979, 69.70Katzenstein, 1979, 74.71Katzenstein, 1979, 144.72As Katzenstein (1979, 73) notes: “Almost as interesting are the factors which fail to differentiate the Marathi-

speaking middle-class supporter of Shiv Sena from his [secular] Congress counterpart. Among middle-class Shiv Senavoters there are no particular pockets of strength in certain castes.”

73Gupta, 1977, 297.74Gupta, 1977, 207-208.

38

tiles—industries which were ethnically homogenous and “compartmentalized.”75 Referring to

working-class occupations, Katzenstein (1979, 84) notes that:

There exists a high degree of occupational specialization by industry, with certainethnic groups predominating in commerce, construction, etc. Furthermore, within anindustry there has been and continues to be considerable job specialization. In tex-tile labor, for example, Maharashtrians have traditionally predominated ... Within themills, different ethnic groups are found concentrated in different departments ... Thesame differentiation occurs in other industries ... Both between and within industries,then, there is a high level of ethnic specialization.”

In these ethnically concentrated industries, in line with my theory, political mobilization and sup-

port for the Shiv Sena was based, “not on economic factors” related to policy, “but on the ‘rightist’

appeal of the party,” and on the “anti-Muslim,” and “authoritarian image” that the party has cul-

tivated.76 Prior to the rise of the Shiv Sena, workers in the textile mill industry had been staunch

supporters of Communist Party-led trade unions, which had “played an important role in trade

union politics in the textile mills” and had led successful textile strikes starting in 1928 to de-

mand wage increases.77 But the Shiv Sena transformed the basis of political mobilization in the

textile mill districts of Bombay by focusing on “a few repetitive themes... [like] anticommunism,

Maharashtrian pride, Indian nationalism, and Hindu identity.”78 These pronounced forms of cul-

tural mobilization allowed the Shiv Sena to effectively decimate the strength of the communist

trade union movements and to make electoral inroads into the ethnically homogenous mill worker

communities.79 Katzenstein (1979) points to the Sena’s “party organization” and “extremist ide-

ological position” as key factors that mobilized working-class support.80 Importantly, this ethnic

mobilization was not predicated on economic factors.81

75Katzenstein, 1979, 84.76Katzenstein, 1979, 83.77Shaikh, 2005.78Shaikh, 2005.79Thakkar and Sanghavi, 2011, 154. See also Patel, 2003, 15.80Katzenstein, 1979, 195. Survey evidence shows that whereas the Shiv Sena’s middle-class supporters were

neither more nor less likely to display ethnic prejudice, its working-class supporters displayed “a relatively highpercentage of intolerant...responses on interethnic relations” Katzenstein, 1979, 92.

81Among the working-class supporters of the Sena, the “relatively higher number of Shiv Sena supporters express-ing less tolerant attitudes toward other religious and linguistic communities...appears not to be based on economiccompetition.” Katzenstein, 1979, 92.

39

Overall, the rise of the Shiv Sena and its bifurcated political mobilization strategies provide

evidence in favor of my theory’s main prediction about the link between ethnic diversity, identity

politics, and economic protectionism (Hypothesis 1). Party politicians used identity based mobi-

lization to win votes from workers in ethnically homogenous industries. At the same time, they

used economic protectionism to rally support from voters in ethnically differentiated industries.

4.2 Different Parties, Similar Strategies

The Shiv Sena’s mobilization strategies are by no means unique. Political parties that have histor-

ically relied on identity based appeals to rally support from members of particular ethnic groups

have regularly employed economic policy appeals to court voters from other ethnic groups. Below

I present evidence from the campaign strategies of the BJP and DMK, two ethnic parties that gained

prominence in different regions of the country and at different time periods, to further corroborate

the mechanisms that undergird my model.

BJP’s Mobilization Strategies Consider, for example, the electoral strategies of the Hindu-

nationalist BJP in Gujarat. As discussed before, BJP politicians were alleged to have condoned

religious riots between Hindus and Muslims, among a wide range of symbolic actions to promote

Hindutva ideology, in order to gain the electoral support of fundamentalist Hindu voters. Yet, BJP

politicians have time and again also courted members of Gujarat’s Muslim trading communities us-

ing economic policies such as tax incentives and subsidies. As Jha (2014, 33) notes, five years after

the 2002 Gujarat riots, “Modi explicitly reached out in his election campaign to Muslims from the

Memon, Khoja and Bohra communities,” which are all trading communities in the state. The BJP

was able to win the 2007 and 2012 state elections “with a significant degree of Muslim support,

particularly among trading communities, and even winning in Muslim majority constituencies,

without having fielded a single Muslim candidate.”82 A similar pattern emerged in local elections,

with the BJP winning 13 percent of the Muslim votes in the 2009 elections.83 A major reason

82Jha, 2014, 34, emphasis in original.83Afzal, 2014, 397.

40

for the BJP’s success amongst Muslim trading communities was the party’s economic policy plat-

forms. According to Engineer (2008), “Narendra Modi tried to win over Bohras and Khojas by his

development discourse. He even had special section for Muslims (Bohras, Khojas etc.) in the eco-

nomic exhibition arranged by him to showcase his development”; this “combination of economic

development and Hindutva ideology [was] a sure combination for political win.”84

Modi’s courting of Muslim trading communities in Gujarat was not a new phenomenon for the

BJP. The BJP historically sought to include Muslim traders in its electoral alliances in western In-

dia. In detailed historical ethnographic work, Engineer (1989, 13, 70) found that the Muslim Bohra

and Memon communities—70 percent of workers in these communities were traders in industries

ranging from hardware and stationary to timber, paints, and dyes—contained many members who

belonged to the BJP. Amongst the Memon community, too, there was significant support for the

BJP. A leading Memon industrialist, who served as the Vice President of the BJP’s Gujarat unit,

maintained that “Muslims were wrong to have tried to keep a distance from the BJP, and that was

the reason why the BJP members considered Muslims as anti-national.”85 Interviewees pointed

out that the Syedna, who serves as the religious head of the Bohra community and who works

to deliver the votes of the Bohras en bloc during elections, “has no scruples about associating or

aligning himself with communal parties.”86 Respondents also stated that “Muslim political and

religious leaders assure the respective political parties that they will get their community votes for

their own economic and political gains...Since the Muslim votes are the crucial and balancing fac-

tors during elections in some constituencies, Muslim politicians capitalize on these votes.”87 This

sentiment was shared by many voters, who maintained that “Muslim votes are considered signif-

icant in areas where their population is concentrated,” and that the “BJP exploited the situation in

Gujarat where there was resentment among Muslim politicians who were refused Congress (I) and

84See also: Jha, 2014.85Interview with Mr. S. (Halai Memon, Bombay), Engineer, 1989, 174.86Interview with Mr. B. (Dawoodi Bohra, Bombay), Engineer, 1989, 84. As one example, the religious head of the

Bohras went so far as to oppose a co-ethnic candidate who was the managing committee of a local Bohra School, andinstead support a Hindu BJP leader who ran for election from the locality where this school was situated. (Interviewwith Mr. N., Dawoodi Bohra, Ahmedabad, Engineer, 1989, 91).

87Interview with Mr. K. (Dawoodi Bohra, Bombay), Engineer, 1989, 87.

41

Janata Party tickets.”88

The BJP’s campaign strategies in Gujarat—courting Hindu votes by using ethnic appeals while

simultaneously soliciting Muslim and other ethnically diverse trading communities using economic

pledges—finds resonance in many other parts of the country, and is reflected in the BJP’s broader

electoral approach during the 1990s. Following the BJP’s 1992 movement to demolish the Babri

mosque in Ayodhya and replace it with a Hindu temple—a major flashpoint of Hindutva election-

eering that triggered widespread religious riots—the BJP “adopted a multi-directional strategy” in

elections across the country, using “selectively the Ram Mandir [temple] card in North India” while

also building a campaign that was “dominated by issues of economic reform, stability, and provi-

sion of good governance.”89 It’s economic reform platform centered on the philosophy of Swadeshi

(or economic self sufficiency), which aimed to foster economic nationalism that would cater to the

interests of “the middle class that comprised of banias (traders or merchants), and small-scale

manufacturers,” and “identify itself closely with the economically depressed classes.”90 A key

element of this economic platform was the courting of Muslim and other minority group voters,

after party leaders calculated that “winning over a sizable number of Indian Muslims was essen-

tial to expand the vote-bank of the BJP.”91 As Afzal (2014, 256) documents, “in order to present

itself as a truly national party, the BJP attempted to reach out to the Indian Muslims...It argued

that lack of education and absence of organization, employment, and business opportunities were

the real issues of the Indian Muslims. It promised to resolve these issues through its programme

of taaleem (education), tanzeem (organization), and tijarat (business and employment).” In turn,

the “BJP strategy of explicit Swadeshi rhetoric, tactical courting of the Dalits and Indian Muslims,

and implicit use of the Hindu themes yielded positive electoral results.”92 These strategies were

implemented in state and national elections ranging from 1993 to 2004, in which the BJP “actively

wooed the Indian Muslims...by promising various development programs” related to “economic

88Interview with Mr. P. (Advocate, Dhoraji), Engineer, 1989, 187.89Afzal, 2014, 255-256.90Afzal, 2014, 252-256.91Afzal, 2014, 376.92Afzal, 2014, 254.

42

uplift and employment.”93

These political dynamics resonate well with the core intuitions of my argument. If voters were

simply selecting candidates based on identity, members of persecuted minority groups would have

no motivation to support ethnic parties. But when voters value both identity and material interests,

ethnic parties will face strategic incentives to court minority swing voters by using economic pol-

icy. It is precisely these selective forms of economic targeting that shores up minority support for

ethnic parties and prevents minorities from deflecting en bloc away from them.

DMK’s Mobilization Strategies A similar pattern emerges when we consider the mobilization

strategies of the Dravida Munnetra Kazhagam (DMK) party in the southern Indian state of Tamil

Nadu. The DMK rose to power in the 1960s and 1970s based on language agitations against

Hindi (which is spoken in northern India) and in favor of Tamil and English (which are prevalent

in Tamil Nadu), as well as identity based appeals to revive Tamil and Dravidian (the linguistic

ethnicity of southern Indians) culture. For example, the DMK glorified past Dravidian kingdoms

such as the Chera, Chola, and Pandya kingdoms, spearheaded the Tamil nationalism movement

and what it termed the the Tamil “renaissance,” and claimed to be the “ethnic local” that could

oppose the one-party dominance of the Indian National Congress party, which it portrayed as the

“ethnic outsider.”94 During this period, Tamil society cleaved extensively along caste and religious

lines. Among the non-Brahmanical caste groups, which formed the vast majority of the population,

there were upper and intermediate caste groupings (loosely termed “forward” castes) on the one

hand, and lower and scheduled castes (termed by some as the “backward” castes) on the other hand

hand.95 The latter grouping, along with religious minorities such as Muslims and Christians, were

occupationally concentrated in low-skill industries and agricultural professions.

The DMK’s ethnic appeals and “cultural policy”96 of Tamil nationalism and anti-Hindi/pro-

English propaganda were particularly effective at mobilizing support among voters belonging to

93Afzal, 254, 387.94Agarwala, 2013, 88; Barnett, 1976, 129.95Brahmans represented a small section (approximately four percent) of the population. See Pandian, 1994, 221.96Barnett, 1976, 274-275.

43

the upper distribution of caste hierarchies.97 For example, in January 1965, when the DMK began a

movement to hoist black flags and Tamil flags, and to the burn copies of the Indian Constitution and

Hindi books across the state, it drew fervent support from English-speaking professionals and col-

lege students, who belonged predominantly to the upper castes and to intermediate castes that had

adopted “the cultural outlook of upper caste professionals.”98 These appeals to “regional emotion”

also allowed the DMK to attract pronounced support from voters belonging to the Brahmanical

castes.99

At the same time, the DMK also advanced an economic policy platform that served to advance

the interests of lower castes, scheduled castes, and religious minorities. For example, after the

DMK came to power in 1967, it “utilized every opportunity” to “mobilize agricultural laborers” by

distributing agricultural subsidies and fertilizers, implementing land reforms, and offering loans

from co-operative land development banks” to farmers.100 By implementing policies regarding

“the provision of wage goods, especially rice” and by “introducing a tiered approach to the levy of

food grains for public distribution,” the DMK was able to consolidate its peasant base.101 These

pro-agrarian economic policies heavily favored backward castes and scheduled caste groups, and

allowed the DMK to make strong electoral inroads into these caste communities.102 Similarly, the

DMK created trade unions for workers in various low-skilled industries and sought to break the

monopoly of the Communist Party in advocating for the interests of workers.103 For example, it

created a federation of trade unions, the Thozhilaalar Munnetra Kazhagam (the Federation for the

Progress of Labour–LPF), which became formally associated with the party and which began to

demand favorable wage policies in factories.104 The DMK also “gained some early Muslim support

in the Kaveri valley among traders...and beedi (cigarette) workers,”105 and it’s economic policies

97Agarwala, 2013, 88.98Subramanian, 1999, 195-198.99Forrester, 1976, 287; Barnett, 1976, 267.

100Venkataraman, 1976, 50.101Subramanian, 1999, 205.102Subramanian, 1999, 209.103Venkataraman, 1976, 50. See also Agarwala, 2013, 89.104Subramanian, 1999, 213.105Subramanian, 1999, 203. Muslim support helped the DMK become the strongest or second strongest party in

several regions of the state by 1967. Subramanian, 1999, 204.

44

favoring reservations for scheduled caste converts to Christianity and Islam won it “considerable

support” among Christian and Muslim voters.106

Overall, DMK fashioned a populist economic policy agenda that “coexisted with considerable

social pluralism.”107 The DMK’s electoral strategies support the logic of my theoretical argument.

When political entrepreneurs decide to mobilize some groups of voters using identity appeals, they

will face fewer incentives to fashion their economic policy platforms toward members of these

groups. Instead, they will be better off targeting distributive economic policies toward members of

other groups.

5 Testing Relationship between Ethnicity and Economic Policy

My theoretical framework offers predictions related to economic policy that I now subject to sys-

tematic empirical tests using subnational data from India. India is a good case to study because

the country exhibits a large degree of ethnic and occupational diversity. I leverage this variation in

the overlapping nature of identity and economic cleavages to explore my main hypotheses linking

ethnic diversity to industry-level measures of protection. India also serves as a good case to eval-

uate my theory because political contestation over identity and economic policy are both common

features in the world’s largest democracy.

A vast literature explores the highly salient nature of identity politics in India. Identity politics

run the gamut—from watershed moments of political confrontation, such as the 1984 anti-Sikh

riots in North India, the early-1990s anti-Muslim demonstrations in Ayodhya and Mumbai, and

the 2002 Hindu-Muslim clashes in Gujarat, to less dramatic yet nonetheless pervasive political

campaigns pertaining to religious re-conversion, education reform, and linguistic and regional

nativism. Many scholars have argued that voters follow religious, communal, and caste-based

imperatives while formulating political decisions in India.108

106Subramanian, 1999, 208.107Subramanian, 1999, 210.108Corbridge and Harriss 2000; Chandra 2004; Jaffrelot 1996; Jenkins 1999; Varshney 2002.

45

But political contestation over economic policy is also common. After embarking on a path

to liberalization, tariffs were reinstated and raised on many product lines.109 Notwithstanding a

broader trend toward lower tariffs in India, considerable sectoral and temporal variation in trade

protection persists; India implemented reforms unevenly and even reversed course at several junc-

tures. Important political constituencies such as organized farmer groups and workers in labor-

intensive industries were decisive stakeholders in the policymaking process.110 Political parties of

all stripes responded to these electoral pressures;111 regional parties112 and coalition partners113

played a crucial role in determining the tempo of economic policy reform. Writing in 2002, Montek

Ahluwalia, an Indian Finance Minister, noted that economic reforms were “fitful” and “opportunis-

tic,” and that “progress was made as and when politically feasible.”114 This variation makes India

a good setting for tests of my theoretical predictions.

5.1 Data and Empirical Strategy

Trade Policy My main dependent variable is tariffs data at the six-digit level of the Indian Trade

Classification Harmonized System (HS) Code spanning the period 1983-2000.115 For the period

109See, e.g.: D’Costa 2012.110See, for example: “Trade unions labour for parent parties in electoral arena,” The Times of India, April 20, 2014;

“AITUC wants no foreign brandy, lipsticks or lotions,” The Economic Times, January 13, 2005; “Are voters againstreforms?” The Times of India, March 9, 1998.

111Consider, for example, the Bharatiya Janata Party’s 1998 national election manifesto: “The economy of Indiahas come under tremendous pressure because of misguided tariff reductions and an uneven playing field for the Indianindustry ... India, too, must follow its own national agenda ... Policies of tariff reduction and lifting of quantitativerestrictions will be formulated ... the objective will be to protect the national economy and national interest like allnations do.” BJP Manifesto, 1998.

112For example, in the context of India’s lowering of tariff barriers, see: “Coalition Politics: Business and RegionalDivergence,” The Times of India, May 31, 1996.

113See, for example: “Less than six months [after initiating liberalization], the optimism that the Government willbe able to maintain the tempo of reforms is on the wane ... because of opposition from various quarters ... The Leftparties and the Janata Dal will try to hijack the opposition platform from the BJP and, in the process, put increasingpressure on the latter to make things difficult for the ruling party.” “Reformers On The Retreat: A Minority Within AMinority,” The Times of India, Jan 17, 1992.

114Ahluwalia 2002, 87.115There are some concerns with utilizing tariffs data as the main indicator for trade policy outcomes. Goldberg and

Maggi (1999) point to the pitfalls of using tariffs data in their empirical test of special interests because tariff levelsare largely determined through cooperation in the GATT/WTO setting; in this case, the scope of domestic politicalcontestations in determining tariff rates might be circumscribed. If this is indeed the case, then any results that I findcan be interpreted as conservative estimates because these reflect the lower bound effects of political contests overtrade policy outcomes. Moreover, the main alternative data to tariffs, non-tariff barriers data, are notoriously difficult

46

1988–2000, I use data from Topalova and Khandelwal 2011. For prior periods, I compiled data

from the annual publication series, “Indian Customs Tariff,” released by the Department of Com-

mercial Intelligence and Statistics at India’s Ministry of Commerce and Industry. The publications

were hand-coded and standardized to ensure continuity. In particular, I created manual product-

level concordances to account for changes in tariff classification schemes over time. Additionally,

because the government routinely re-classified products across categories, I systematized these re-

classifications in order to maintain comparability. Over 5,000 product lines are represented in the

data.

Ethnic Composition of Industrial Activity For estimating indicators of ethnic heterogene-

ity among workers within different industries, I used the Government of India’s National Sam-

ple Survey data on Employment and Unemployment in 1983–1984 (n = 120,921), 1987–1988

(n = 129,194), 1993–1994 (n = 115,409), and 1999-2000 (n = 120,578). These nationally rep-

resentative surveys include the occupational category as well as religion and ethnicity status of

respondents.

I calculated the standard measure of ethnic heterogeneity using the fractionalization measure

proposed by Alesina et al (2003). In particular, fractionalization is defined as: EthnicHeterogeneityk =

1−∑Jj s2

jk, where s jk is the share of group j ( j = 1...J) in industry k.116 I considered all the religion

and caste group combinations of classifications listed in the National Sample Survey. Religions

included are Hinduism, Islam, Christianity, Sikhism, Jainism, Buddhism, Zoroastrianism, and Oth-

ers. Caste groups included are Scheduled Castes, Scheduled Tribes, Other Backward Classes, and

Others. Thus, each religion-caste category is considered as a separate social group. I created

manual concordance tables to map the three-digit National Industrial Classification (NIC) codes

utilized in the Employment and Unemployment data with the Harmonized System (HS) codes

utilized in the tariffs data.

to measure and quantify, especially in developing nations. For example, coverage ratios often capture non-bindingquotas that might overstate or understate levels of real protection depending on industry-specific contexts (Gawandeand Krishna 2003).

116Thus, fractionalization is one minus the sum of squares of shares of ethnic groups.

47

Covariates I use subnational industry-level annual covariate data from the Government of India’s

Annual Survey of Industries. Following Khandelwal and Topalova (2010), I include the follow-

ing controls in my estimations: Log Real Wage; Share of Non-Production (Skilled) Workers; Log

Output; Log Employment; Factory Size; and Capital Labor Ratio. I include data on employment

because larger workforces may lead to increased electoral power; output and wages, because pol-

icymakers might wish to protect industries with low income workers; and concentration, which is

captured by factory size, because concentrated industries might be more likely to organize politi-

cally for protection.

Electoral Data National and state level electoral data comes from the EOPP Database.

Industrial Geography Data The Government of India’s Fourth Economic Census of India (1998)

includes geographical data for all agricultural and manufacturing commercial enterprises in India.

The data covers unit-level responses from over 17 million rural enterprises and 12 million urban

enterprises. Based on all responses, I identified the state that has the most number of commercial

enterprises belonging to each industrial activity code.

5.2 Estimation Strategy

I first test if there is a partial correlation between levels of ethnic heterogeneity within industries

and industry-level protection by using the following baseline specification:

Tari f fkt = α +β1 ∗EthnicHeterogeneitykt +ϕ ∗Xkt +θt +λk + εkt

where k indexes each industry in year t, Tari f fkt represents the tariff rate accorded to an in-

dustry, EthnicHeterogeneitykt represents the level of ethnic fragmentation among workers in the

industry, Xtk is a vector of time-varying control variables and is excluded in some specifications,

θt are year fixed effects, λk are industry fixed effects, and εkt is the error term.117 The coefficient

117The year fixed effects control for common shocks to trade policy at any given time; therefore, my estimation

48

of interest is β1, which captures the relationship between the levels of ethnic diversity within an in-

dustry and the protection accorded to the industry. I present OLS estimates of the specification and

report standard errors clustered at the industry level to account for within-industry correlations,

including serial autocorrelation, in the data. Following the predictions of my theoretical model,

the primary hypothesis that I evaluate is whether greater degrees of ethnic heterogeneity within

industries increase the level of trade protection accorded to industries (i.e., β1 > 0).

There are some important threats to inference that we should be concerned about.118 The es-

timates of β1 would be biased if there are time-varying unobserved factors that impact tariffs and

are correlated with ethnic heterogeneity. It is also possible that reverse causality might be at play.

If trade policy protection causes higher levels of ethnic diversity within industries, for example, I

might overestimate the positive effect of diversity on trade protection. Intuitively, however, pro-

tection tends to go to less competitive industries. If we expect more competitive industries to have

greater degrees of diversity than less competitive industries, then any potential effect of trade pro-

tection on ethnic diversity would bias estimates in a negative direction, and my results would, if

anything, underestimate a positive effect. Yet, it is difficult to evaluate such claims definitively;

as noted above, additionally, other confounding factors might also be relevant. For these reasons,

the results do not permit me to make strong causal claims, although I view my results as being

consistent with the predictions of my theoretical model.

In a second econometric specification, I include the lagged dependent variable.119 This spec-

ification adopts a different strategy to concerns about potential time-varying unobservables that

might bias my estimates of β1. In particular, it conditions on the lagged value of the tariff rate,

which reflects an industry’s most recent trade policy. Of course, similar concerns that apply to the

first specification might also apply to the second specification. Note, additionally, that the presence

strategy accounts for watershed moments of policy change, such as India’s accession to the World Trade Organizationin 1994 or India’s implementation of an economic liberalization program in 1991-1992.

118Although fixed effects help overcome several inferential challenges, they are dependent on their own set ofassumptions. Fixed effects account for time-invariant variables and those that do not vary across industries. Yet, it ispossible that they do not capture other important factors. See: Angrist and Pischke 2008.

119Note that OLS estimates are biased in models containing both lagged dependent variables and fixed effects. Ithus remove industry fixed effects, although my results are qualitatively the same when I include industry-fixed effectsin these models.

49

of serial correlation in the error term will bias the estimation of the coefficient of the lagged tariffs.

Yet, the lagged dependent variable controls for additional time-varying unobservables about which

we might be concerned.

Next, I study whether the presence of elections in a state in any given year predicts the level

of protection accorded to industries that are concentrated in the state. To do so, I create a dummy

variable that takes a value of one if the state that is home to the most number of commercial enter-

prises in industry k had an election in year t. After 1971, national and state elections in India were

de-coupled; I exploit this temporal variation in elections in my empirical strategy. Because elec-

tions occurred at different times for states associated with different industries, the panel structure

of the data lends itself well to the study of the effects of elections. Moreover, compared to data on

individual industries, multi-industry evidence should be less affected by confounding arising from

industry-specific policy interventions that might have occurred during the period. For these tests, I

use the specification:

Tari f fkt = α +β2 ∗Election inIndustry′sStatekt +ϕ ∗Xtk +θt +λk + εkt

Last, I study if an interaction effect exists between the presence of elections in a state and the

ethnic heterogeneity of the industry, using the specification:

Tari f fkt = α +β1 ∗EthnicHeterogeneitykt +β2 ∗Election inIndustry′sStatekt +

β3 ∗ (EthnicHeterogeneitykt ∗Election inIndustry′sStatekt)+ϕ ∗Xtk +θt +λk + εkt

Here, β1 and β2 are the conditional marginal effects of the variables capturing ethnic hetero-

geneity and elections. We can interpret β3 as an observational “differences-in-differences” estima-

tor. The marginal effect of EthnicHeterogeneity is captured by β1 when there are no elections in

a state, and by β1 +β3 when there are elections in the state.

50

5.3 Results

Table 4 presents results for OLS specifications exploring the relationship between the ethnic het-

erogeneity of an industry’s workforce and the levels of trade protection afforded to that industry. In

Column 1, I restrict the analysis to the primary independent variable of interest, EthnicHeterogeneitykt ,

and include year-fixed effects and industry-fixed effects. Column 2 adds industry-level covariate

data used in seminal studies of trade policymaking in India (see Khandelwal and Topalova 2010).

Column 3 adds a one-year lag of the dependent variable, but deletes the industry fixed effects.

Columns 4 and 5 replicate the analysis by excluding industries where levels of heterogeneity are

greater than 0.9 or lesser than 0.1 in order to check whether the results are being driven by out-

liers. Finally, Columns 6 and 7 restrict the sample to non-agricultural products. Because land is

a relatively abundant factor of production in a developing country such as India, industries that

do not use land intensively should face greater incentives to demand protection from international

competition; Columns 6 & 7 check whether my results hold among these industries. In each spec-

ification, we observe a positive, qualitatively meaningful, and statistically significant relationship

between the ethnic diversity of an industry and the level of protection provided to the industry.120

In Table 5, I explore the partial correlation between the presence of elections in a state in

any given year and the trade policy protection provided to the industry. If the state where the

majority of commercial enterprises belonging to an industry had an election in a given year, the

variable Election inIndustry′sStatekt takes a value of one. If not, it takes a value of zero. Column

1 presents the results of a regression of industry-level tariffs on elections in the industry’s main

state, along with a lagged version of the dependent variable and fixed effects. Column 2 includes

industry-level covariate data. Columns 3 and 4 evaluate whether the relationship between ethnic

heterogeneity and trade protection is mediated by the presence or absence of electoral politics.

While Column 3 does not include covariate data, Column 4 includes the full vector of controls.

120Note that for the time period analyzed in Table 1, industry-level data for ethnic diversity is only available forspecific years (1983–1984, 1987–1988, 1993–1994, and 1999-2000). Thus, my sample remains restricted to thesetemporal snapshots. When I use linear interpolation to extend the ethnic diversity to other years during this period, Iobtain qualitatively similar results (results not shown).

51

Inspecting Column 4, we see that when elections are not present (Election inIndustry′sStatekt =

0), the marginal effect of ethnic heterogeneity is positive. By contrast, when elections are present

(Election inIndustry′sStatekt = 1), the marginal effect of ethnic heterogeneity remains positive

but is more pronounced. Overall, then, the results presented in Table 5 provide further evidence

in favor of my theoretical argument. Electoral cycles magnify the relationship between the ethnic

diversity of an industry’s workforce and the level of trade protection accorded to the industry. The

empirical evidence presented in this section establishes only a partial correlation between ethnicity

and trade policy outcomes. I view these results as an important first step in theory validation.

However, to establish a causal relationship among these variables, additional tests are required.

52

53

6 Discussion

This paper develops a new theory to explicate how identity politics impact the politics of economic

policymaking in ethnically divided societies. I show that ethnic politics have “knock-on” effects on

the formulation of politicians’ policy platforms. Because identity mobilization hardens voter pref-

erences along the dimension of identity, it makes these voters relatively less sensitive to marginal

changes in economic policy. Therefore, once politicians wield the identity card on a particular

ethnic group, they face electoral incentives to target their economic policies to voters among other

groups. Conventional wisdom holds that politicians in ethnically divided societies always provide

economic goods and policy benefits to co-ethnic voters.121 This might be because co-ethnics are

better able to overcome collective action problems and secure beneficial policies from the state.122

It might also reflect the tendency of both voters and politicians to utilize ethnicity as a signal of

shared allegiance in information poor environments.123 The theory developed in this paper of-

fers an alternate perspective. Politicians try to win support from ethnically homogenous economic

groups using identity appeals. They, in turn, target distributive policies to ethnically heterogeneous

groups that contain non-co-ethnic voters.

The hypotheses derived from the formal model are tested on industry-level ethnicity and trade

policy data from India, a country where identity politics proliferate in the economic arena, and

where trade protectionism is uneven and poorly understood.124 My findings thus help advance the

study of economic policymaking. Understanding the sources of variation in trade protection can

better equip policymakers overcome the gridlock that continues to plague global trade negotiations.

Additionally, because trade-related regulatory transformations have reshaped the global economy

and altered welfare standards for millions, comprehending their socio-political antecedents is cru-

cial for understanding economic development trends. This paper offers a novel explanation for

observed sources of policy variation, thereby generating insights that are of interest to scholars and

121But, see: Kasara, 2007; Roemer, 1998; The Control of Politicians in Divided Societies: The Politics of Fear,2007.

122Alesina, Baqir and Easterly 1999; Austen-Smith and Wallerstein 2006; Hechter 1974, 1987.123Chandra 2004.124See, for example, Milner and Kubota 2005, p. 138.

54

policymakers alike.

My account helps explain when and why politics over economic policy and identity emerge in

settings where identity cleavages crisscross with industry-based economic cleavages. The cross-

cutting nature of the cleavages I study points to a potential scope condition of the argument. It

is possible that when economic divisions neatly overlap with ethnic fault lines, politicians might

mobilize co-ethnics based on identity and provide preferential economic policies to their voting

blocs. By a related logic, political agents might downplay identity conflict when ethnically het-

erodox communities share common economic interests. Yet, when ethnic and economic cleavages

crosscut—a feature that is common to most ethnically divided societies—my theory predicts a

countervailing relationship between ethnic mobilization and economic representation. My paper

suggests that in order to explain political competition in these societies, we should pay attention to

how voters’ economic interests interact with their identity-related interests, and to how politicians

strategically manipulate the relative salience of these preferences for self-serving purposes.125

One benefit of the theory that I develop is that is allows us to examine political conflicts related

to economic policymaking and ethnic conflict within a single framework. By incorporating identity

politics into prevailing theories of societal coalition politics, my argument offers new insights

into the social and political foundations of regulatory capture in democratic systems. Yet the

implications of my argument are far from theoretical. There has been a sharp rise in identity politics

across the world in recent decades. Distributional gaps—stemming from poverty, inequality, land

and capital ownership, and skills-based opportunities—abound precisely in those places where

identity politics have been most pronounced. Prevailing academic and policy approaches focus

almost exclusively on economic factors while seeking to explain and resolve these distributional

conflicts. This paper suggests, however, that incorporating the role of identity politics into the

analysis of economic policymaking might be necessary for developing a holistic approach to the

study of economic contestation in ethnically divided societies.

125See, also: Jha 2013; Hechter 1974.

55

ReferencesAcharya, Avidit, John Roemer and Rohini Somanathan. Forthcoming. “Caste, Corruption and

Political Competition in India.” Research in Economics .

Afzal, Muhammad Mujeeb. 2014. Bharatiya Janata Party and the Indian Muslims. Oxford Uni-versity Press.

Agarwala, Rina. 2013. Informal Labor, Formal Politics, and Dignified Discontent in India. Cam-bridge University Press.

Ahluwalia, Montek S. 2002. “Economic Reforms in India Since 1991: Has Gradualism Worked?”Journal of Economic Perspectives 16(3):67–88.URL: http://www.aeaweb.org/articles.php?doi=10.1257/089533002760278721

Akerlof, G. A. and R. E. Kranton. 2000. “Economics and identity.” Quarterly Journal of Eco-nomics 115(3):715–753.

Alesina, A., R. Baqir and W. Easterly. 1999. “Public goods and ethnic divisions.” Quarterly Jour-nal of Economics 114(4):1243–1284.

Alt, J. E., J. Frieden, M. J. Gilligan, D. Rodrik and R. Rogowski. 1996. “The political economy ofinternational trade - Enduring puzzles and an agenda for inquiry.” Comparative Political Studies29(6):689–717.

Austen-Smith, D. and M. Wallerstein. 2006. “Redistribution and affirmative action.” Journal ofPublic Economics 90(10-11):1789–1823.

Bagwell, K. and R. W. Staiger. 1999. “An economic theory of GATT.” American Economic Review89(1):215–248.

Bailey, M. A., J. Goldstein and B. R. Weingast. 1997. “The institutional roots of American tradepolicy.” World Politics 49(3).

Barnett, Marguerite Ross. 1976. The Politics of Cultural Nationalism in South India. PrincetonUniversity Press.

Bharucha, Kruti. 2003. “Impact of Identity Politics on Differential Voter Outcomes: What Deter-mines India’s Voting Behaviour?” Economic and Political Weekly XXXVIII(6).

Billimoria-Zenieris, Jer. 1997. Primordial Violence in India in the 1990s. PhD thesis University ofOklahoma.

Blanchflower, David G., Andrew J. Oswald and Peter Sanfey. 1996. “Wages, Profits, and Rent-Sharing.” The Quarterly Journal of Economics 111(1):227–251.URL: http://qje.oxfordjournals.org/content/111/1/227.abstract

Brass, Paul. 1997. Theft of an Idol. Princeton University Press.

56

Chandra, Kanchan. 2004. Why ethnic parties succeed : patronage and ethnic headcounts in India.Cambridge, UK ; New York: Cambridge University Press.

Chwieroth, J. 2007. “Neoliberal economists and capital account liberalization in emerging mar-kets.” International Organization 61(2):443–463.

Cohen, Lizabeth. 2008. Making a new deal : industrial workers in Chicago, 1919-1939. 2nd ed.Cambridge ; New York: Cambridge University Press.

Corbridge, Stuart and John Harriss. 2000. Reinventing India : liberalization, Hindu nationalismand popular democracy. Cambridge, UK Malden, MA: Polity Press ; Blackwell.

D’Costa, Anthony P. 2012. Globalization and Economic Nationalism in Asia. Oxford UniversityPress.

Dickson, E. S. and K. Scheve. 2006. “Social identity, political speech, and electoral competition.”Journal of Theoretical Politics 18(1):5–39.

Dickson, E. S. and K. Scheve. 2010. “Social Identity, Electoral Institutions and the Number ofCandidates.” British Journal of Political Science 40:349–375.

Dunning, T. and L. Harrison. 2010. “Cross-cutting Cleavages and Ethnic Voting: An ExperimentalStudy of Cousinage in Mali.” American Political Science Review 104(1):21–39.

Dutil, Patrice and David MacKenzie. 2011. Canada 1911: The Decisive Election that Shaped theCountry. New York, NY: Dundurn.

Engineer, Asghar Ali. 1989. The Muslim Communities of Gujarat: An Exploratory Study ofBohras, Khojas, and Memons. Ajanta Publications.

Engineer, Asghar Ali. 2008. “Gujarat Elections and Aftermath.” Secular Perspectives .

Forrester, Duncan. 1976. “Factions and Filmstars: Tamil Nadu Politics since 1971.” Asian Survey16(3):283–296.

Gawande, Kishore and Pravin Krishna. 2003. Handbook of international trade. vol. 1. Malden,MA: Blackwell Pub.

Girvin, Brian. 1989. Between two worlds : politics and economy in independent Ireland. Dublin:Gill and Macmillan.

Goldberg, Pinelopi Koujianou and Giovanni Maggi. 1999. “Protection for Sale: An EmpiricalInvestigation.” American Economic Review 89(5):1135–1155.

Gupta, Dipankar. 1977. The Shiva Sena Movement 1966-1974: A Sociological Analysis PhDthesis Jawaharlal Nehru University.

Habyarimana, J., M. Humphreys, D. N. Posner and J. M. Weinstein. 2007. “Why does ethnicdiversity undermine public goods provision?” American Political Science Review 101(4):709–725.

57

Habyarimana, James P., M. Humphreys and D. N. Posner. 2009. Coethnicity : diversity and thedilemmas of collective action. New York: Russell Sage Foundation.

Hechter, M. 1974. “Political Economy of Ethnic Change.” American Journal of Sociology79(5):1151–1178.

Hechter, M. 1976. “Ethnicity and Industrialization - Proliferation of Cultural Division of Labor.”Ethnicity 3(3):214–224.

Hechter, Michael. 1987. Principles of group solidarity. Berkeley: University of California Press.

Heisler, M. O. 1977. “Managing Ethnic Conflict in Belgium.” Annals of the American Academy ofPolitical and Social Science 433(Sep):32–46.

Helpman, E., M. J. Melitz and S. R. Yeaple. 2004. “Export versus FDI with heterogeneous firms.”American Economic Review 94(1):300–316.

Hiscox, M. J. 1999. “The magic bullet? The RTAA, institutional reform, and trade liberalization.”International Organization 53(4).

Hiscox, M. J. 2002a. “Commerce, coalitions, and factor mobility: Evidence from congressionalvotes on trade legislation.” American Political Science Review 96(3):593–608.

Hiscox, Michael J. 2002b. International trade and political conflict : commerce, coalitions, andmobility. Princeton, N.J.: Princeton University Press.

Hume, S. E. 2003. “Belgian settlement and society in the Indiana Rust Belt.” Geographical Review93(1):30–50.

Irwin, Douglas A. 1996. Against the tide : an intellectual history of free trade. Princeton, N.J.:Princeton University Press.

Jaffrelot, Christophe. 1996. The Hindu nationalist movement and Indian politics : 1925 to the1990s : strategies of identity-building, implantation and mobilisation (with special reference toCentral India). London: Hurst.

Jenkins, Rob. 1999. Democratic politics and economic reform in India. New York: CambridgeUniversity Press.

Jha, Saumitra. 2013. “Trade, Institutions and Ethnic Tolerance: Evidence from South Asia.” Amer-ican Political Science Review 107(4):806–832.

Jha, Saumitra. 2014. “’Unfinished business’: Historic complementarities, political competitionand ethnic violence in Gujarat.” Journal of Economic Behavior and Organization 104:18–36.

Joshi, Ram. 1968. “The Shiv Sena: A Movement in Search of Legitimacy.” Asian Survey10(11):967–978.

Kasara, Kimuli. 2007. “Tax Me If You Can: Ethnic Geography, Democracy, and the Taxation ofAgriculture in Africa.” American Political Science Review pp. 159–172.

58

Katzenstein, Mary Fainsod. 1979. Ethnicity and Equality: the Shiv Sena Party and PreferentialPolicies in Bombay. Ithaca: Cornell University Press.

Khandelwal, Amit and Petia Topalova. 2010. “Trade Liberalization and Firm Productivity: TheCase of India.” The Review of Economics and Statistics .

Lele, Jayant. 1995. “Saffronisation of Shiv Sena: Political Economy of City, State and Nation.”Economic and Political Weekly 30(25):1520–1528.

Mansfield, E. D., H. V. Milner and B. P. Rosendorff. 2000. “Free to trade: Democracies, autocra-cies, and international trade.” American Political Science Review 94(2):305–321.

Masselos, Jim. 1994. “The Bombay riots of January 1993: The politics of urban conflagration.”Journal of South Asian Studies 17(s1):79–95.

Mayda, A. M. and D. Rodrik. 2005. “Why are some people (and countries) more protectionist thanothers?” European Economic Review 49(6):1393–1430.

Mayer, W. 1984. “Endogenous Tariff Formation.” American Economic Review 74(5):970–985.

McGillivray, Fiona. 2004. Privileging industry : the comparative politics of trade and industrialpolicy. Princeton, N.J. ; Oxford: Princeton University Press.

Melitz, M. J. 2003. “The impact of trade on intra-industry reallocations and aggregate industryproductivity.” Econometrica 71(6):1695–1725.

Miguel, E. and M. K. Gugerty. 2005. “Ethnic diversity, social sanctions, and public goods inKenya.” Journal of Public Economics 89(11-12):2325–2368.

Milner, Helen and Keiko Kubota. 2005. “Why the Move to Free Trade? Democracy and TradePolicy in the Developing Countries.” International Organization 59(1):107–143.

Milner, Helen V. 1988. Resisting protectionism : global industries and the politics of internationaltrade. Princeton, N.J.: Princeton University Press.

Nellis, Gareth, Michael Weaver and Steven Rosenzweig. 2015. “Do parties matter for ethnicviolence? Evidence from India.” Yale University Working Paper.

Pandian, M.S.S. 1994. “Crisis in DMK.” Economic and Political Weekly 29(5):221–223.

Pashlikar, Suhas. 2004. “Shiv Sena: A Tiger with Many Faces?” Economic and Political Weekly39(14):1497–1507.

Patel, Sujata. 2003. Bombay and Mumbai: The City in Transition. Oxford University Press.

Persson, Torsten and Guido Tabellini. 2000. Political Economics: Explaining Economic Policy.Cambridge, Mass.: Massachusetts Institute of Technology Press.

Richman, B. D. 2006. “How community institutions create economic advantage: Jewish diamondmerchants in New York.” Law and Social Inquiry 31(2):383–420.

59

Robinson, Amanda. 2012. National Identification and Interpersonal Trust in Diverse Societies PhDthesis Stanford University.

Roemer, John E. 1998. “Why the poor do not expropriate the rich: an old argument in new garb.”Journal of Public Economics 70(3):399 – 424.

Roemer, John, Woojin Lee and Karine Van der Straeten. 2007. Racism, Xenophobia, and Distri-bution: Multi-Issue Politics in Advanced Democracies. Harvard University Press.

Rogowski, Ronald. 1989. Commerce and coalitions : how trade affects domestic political align-ments. Princeton, N.J.: Princeton University Press.

Rose, A. K. 2004. “Do we really know that the WTO increases trade?” American EconomicReview 94(1):98–114.

Scheve, K. F. and M. J. Slaughter. 2001. “What determines individual trade-policy preferences?”Journal of International Economics 54(2):267–292.

Schonhardt-Bailey, Cheryl. 2006. From the corn laws to free trade interests, ideas, and institutionsin historical perspective. Cambridge, Mass.: MIT Press.

Shah, Ghanshyam. 2002. “Contestation and Negotiations: Hindutva Sentiments and TemporalInterests in Gujarat Elections.” Economic and Political Weekly XXXVII(48).

Shah, Ghanshyam. 2010. “Beyond Caste Voting: Modasa, Gujarat revisited.” Economic and Polit-ical Weekly XLV(4).

Shaikh, Juned. 2005. “Worker Politics, Trade Unions and the Shiv Sena’s Rise in Central Bombay.”Economic and Political Weekly pp. 1893–1900.

Shayo, M. 2009. “A Model of Social Identity with an Application to Political Economy: Nation,Class, and Redistribution.” American Political Science Review 103(2):147–174.

Stokes, Susan, Thad Dunning, Marcelo Nazareno and Valeria Brusco. 2013. Brokers, Voters, andClientelism: The Puzzle of Distributive Politics. Princeton, N.J.: Cambridge University Press.

Subramanian, Narendra. 1999. Ethnicity and Populist Mobilization: Political Parties, Citizens,and Democracy in South India. Oxford University Press.

Talwalker, Clare. 1996. “Shivaji’s Army and Other “Natives” in Bombay.” Comparative Studies ofSouth Asia, Africa and the Middle East XVI(2):114–122.

Thakkar, Usha and Nagindas Sanghavi. 2011. Interrogating Reorganisation of States: Culture,Identity and Politics in India. Routledge.

The Control of Politicians in Divided Societies: The Politics of Fear. 2007. The Review of Eco-nomic Studies 74(4):pp. 1259–1274.URL: http://www.jstor.org/stable/4626180

60

Tomz, M., J. L. Goldstein and D. Rivers. 2007. “Do we really know that the WTO increases trade?Comment.” American Economic Review 97(5):2005–2018.

Topalova, P. and A. Khandelwal. 2011. “Trade Liberalization and Firm Productivity: The Case ofIndia.” Review of Economics and Statistics 93(3):995–1009.

Varshney, Ashutosh. 2002. Ethnic conflict and civic life Hindus and Muslims in India. New Haven,CT: Yale University Press.

Venkataraman, G. 1976. Role of the DMK in Trade Union Movement of Tamil Nade PhD thesisJawaharlal Nehru University.

Weiner, Myron. 1978. Sons of the soil: migration and ethnic conflict in India. Princeton, N.J.:Princeton University Press.

Wilkinson, Steven. 2004. Votes and violence : electoral competition and ethnic riots in India.Cambridge, U.K. ; New York: Cambridge University Press.

Wiskemann, Elizabeth. 1967. Czechs and Germans: a study of the struggle in the historic provincesof Bohemia and Moravia. 2nd ed. London, Melbourne etc. New York,: Macmillan.

61

7 Appendix

7.1 Candidates’ Decisions to Invoke IdentityIn Section 2.6 above, I discussed the case involving A’s decision to play C if B does not play C(Case 1). Below, I discuss each of the additional cases in which candidates decide whether or notto invoke identity.

Case 2 B’s decision if A does not play C A parallel logic applies to B’s decision to invokeidentity in the electoral arena. When A does not play C, B plays C if it enhances B’s probabilityof winning the election. In the absence of identity politics, as before, the election is a tossup.However, if B were to play C, B’s probability of winning would be:

vB =12+

ψ[ϕ +(λ −1)d]

{n[ϕ +(α −1)d][π1(τB)−π1(τA)]+

(1−n)[ϕ +(β −1)d][π2(τB)−π2(τA)]− [λ (2ϕ −d)− (ϕ −d)]c}. (15)

In equilibrium, this probability equals 12 −

ψ[ϕ+(λ−1)d] [λ (2ϕ −d)− (ϕ −d)]c. Comparing with

the tossup probability of 12 , B decides to play C if:

ψ[ϕ +(λ −1)d]

{[λ (2ϕ −d)− (ϕ −d)]c}< 0. (16)

This condition simplifies to [λ (2ϕ − d)− (ϕ − d)]c < 0. For the condition to hold, since cis positive according to Assumption 1, [λ (2ϕ − d)− (ϕ − d)] must be negative. This conditionis intuitive. Recall that the average identity bias is the preference toward candidate A; when apolitician plays the identity card the expected identity bias of a member of group a increases by c,while the expected identity bias of a member of group b correspondingly decreases by c. Therefore,B will only invoke identity if B can tilt the average identity bias in the electorate away from A andtoward B.

The condition implies that B plays C if λ (2ϕ − d)− (ϕ − d) < 0. We see again that both theidentity dispersion effect (d) and a’s share of the population (λ ) are consequential in B’s decisionto invoke identity. Let us first evaluate the role of ethnic demography, keeping in mind that b’sshare of the population is simply 1−λ . B plays C if λ < ϕ−d

2ϕ−d . That is, B will invoke identityonly when a’s share of the population is lesser than a half. To observe this effect, assume that theidentity dispersion effect is zero (d = 0); in this case, λ < 1

2 needs to be true for the condition tohold. B therefore faces greater incentives to play C as a’s share grows smaller and as b’s sharegrows larger. When a’s share of the population is less than half, B’s decision to play C will dependon the identity dispersion effect. As the identity dispersion effect becomes larger, a’s share of thepopulation needs to become smaller for the condition to hold. Even when the entire populationconsists of b group members (i.e., λ = 0), B will not invoke identity in cases where the dispersioneffect is large enough to drive the density of identity-related preferences down to zero (d = ϕ ).

We see, therefore, that once again the identity dispersion effect fixes B’s decision to play C.Formally, B will invoke identity so long as d < ϕ (1−2λ )

(1−λ ) . When λ ≥ 12 , B will not invoke identity.

However, when λ < 12 , B will play C only when d is smaller than a certain critical threshold. As

62

λ becomes smaller (i.e., as b’s share of the population becomes larger), this threshold increases.However, even when the entire population is composed of b, d needs to be lesser than ϕ for thecondition to hold. In cases where d = ϕ , B will not invoke identity. Overall then, akin to A, theidentity dispersion effect also binds for B: as d increases, B finds fewer incentives to play C. Whenonly B plays C, the identity-related preferences of b group voters become dispersed. B thus winsnew voters in this group at a slower rate, while losing a group voters at a similar rate as before.

Case 3 A’s decision if B plays C Next, consider A’s decision to plays C if B has already wieldedC. I show here that if B plays C, A does not find it profitable to play C. When only B plays C, vBequals:

vB =12+

ψ[ϕ +(λ −1)d]

{n[ϕ +(α −1)d][π1(τB)−π1(τA)]+

(1−n)[ϕ +(β −1)d][π2(τB)−π2(τA)]− [λ (2ϕ −d)− (ϕ −d)]c}. (17)

In equilibrium, A’s probability of winning the election simplifies to 12 +

ψ[ϕ+(λ−1)d]{[λ (2ϕ −

d)− (ϕ −d)]c}. By contrast, if A were to also play C, then vB would equal:

vB =12+

ψ(ϕ −d)

{n(ϕ −d)[π1(τB)−π1(τA)]+(1−n)(ϕ −d)[π2(τB)−π2(τA)]−

[(2λ −1)(ϕ −d)]c}. (18)

A’s equilibrium probability of winning the election in this instance would be 12 +

ψ(ϕ−d){[(2λ −

1)(ϕ − d)]c}. As before, A only plays C if it were to increase her probability of winning theelection. Comparing each probability, we see that this occurs if:

ψ(ϕ −d)

{[(2λ −1)(ϕ −d)]c} >ψ

[ϕ +(λ −1)d]{[λ (2ϕ −d)− (ϕ −d)]c}. (19)

This condition simplifies to λ < 0. Because a’s share of the population cannot be negative,the condition does not hold. Put simply, when B plays the identity card, A’s best response is torefrain from playing the card in equilibrium. Intuitively, although the identity card can increasea candidate’s average identity-related favorability (c) among co-ethnics, it also decreases the can-didate’s average identity-related favorability among voters belonging to the ethnic “out group.”When one candidate introduces identity politics into the electoral arena, the other candidate ineffect also reaps an “ethnic electoral bounce” without having to incur the costs related to “identitydispersion” that are associated with wielding the identity card. Therefore, it is not profitable forthe second candidate to play the identity card in this case.126

126Note that this observation concords with reality. In most electoral settings, when one party wields the identitycard the other party tends to adopt an explicitly non-communal worldview. In India, for example, while the Hindunationalist BJP party might adopt campaign strategies steeped in religious exclusionism, the Congress party tends toembrace an explicitly secular platform. Although the BJP can boost its average vote shares among Hindus by playingthe identity card, it loses Muslim votes en bloc to the Congress party, which gains these Muslim votes without having

63

Case 4 B’s decision if A plays C Finally, consider B’s decision to play C, given that A playsC. Comparing B’s probability of winning when both candidates invoke identity with the case inwhich only A plays C, we see that B decides to play C if:

ψ(ϕ −d)

{−[(2λ −1)(ϕ −d)]c} >ψ

(ϕ −λd){−[λ (2ϕ −d)−ϕ ]c}. (20)

This condition simplifies to λ > 1. Because a’s share of the population can never be largerthan 1, this condition never holds. Like in Case 2, when one candidate plays the identity card, theother candidate does not play the identity card because the electoral costs of doing so outweigh thebenefits.

7.2 An Example Holding Ethnic Group Sizes FixedWhat are the model’s predictions if we kept the sizes of the ethnic groups fixed and varied onlytheir distributions across industries? I discuss below a special case that provides an intuitive answerto this question. The example shows how equilibrium tariffs change as we move from a settingin which an industry is split exactly in half between two ethnic groups to a setting in which theindustry is comprised solely of one ethnic group. In this special case, I make three assumptions:

1. Industry 1 is larger than industry 2.

2. Group a is larger than industry 1.

3. Industry 2 is large enough such that a 50% ethnic split in industry 1 is possible.

Let n be the size of industry 1, sa the number of voters belonging to group a, and sb = 1− sathe number of voters belonging to group b. If sa1 =

n2 + ε , sb1 =

n2 − ε , sa2 = sa − sa1 and sb2 =

(1− sa)− sb1 (see Figure 4), then increasing ε has the effect of making industry 1 more ethnicallyhomogeneous while keeping industry and group sizes fixed.

to play the identity card.

64

Does the ethnic distribution of workers across industries impact equilibrium policies? Whenidentity politics are not present in the electoral arena, B’s probability of winning the election issimply:

vB =12+

ψϕ{nϕ [π1(τB)−π1(τA)]+(ϕ −nϕ)[π2(τB)−π2(τA)]}. (21)

Observe that ε affects neither the candidates’ probabilities of winning the election, nor the

equilibrium tariff rates. In this case, equilibrium policies are characterized by π ′1(τ)

π ′2(τ)

= 1− 1n . Similar

to the finding from the general setup, when identity politics are absent, only the numerical strengthof voters working in an industry shapes equilibrium outcomes. Now consider the case in whichidentity politics enters the political arena. When A plays the identity card, we find that ε begins toinfluence electoral dynamics. Consider B’s probability of winning the election in this case:

vB =12+

ψϕ − sad

{[nϕ − n2

d − εd][π1(τB)−π1(τA)]

+[ϕ − sad −nϕ +n2

d + εd][π2(τB)−π2(τA)]− [sa(2ϕ −d)−ϕ ]c}. (22)

In equilibrium, tariff policies are characterized by π ′1(τ)

π ′2(τ)

= 1− ϕ−sadnϕ−( n

2+ε)d . Here, an increase in

ε (i.e., an increase in the ethnic homogeneity of industry 1), holding all else constant, decreasestariffs for industry 1—a similar finding to the broader setup. This special case shows, then, thatin the presence of identity politics, simply varying the distribution of ethnicities across industriescan shift equilibrium policies. The more ethnically concentrated an industry, the less likely it is toreceive its preferred economic policy. Intuitively, due to the identity dispersion effect, politiciansface fewer incentives to give an industry preferential policies as it becomes more concentratedwith voters who have been mobilized on identity. These voters have more dispersed identity-related preferences, and are hence relatively less sensitive to marginal changes in economic policy.Instead, the politicians are better off targeting their economic policies toward the other industry inwhich there are relatively fewer voters who have been mobilized on ethnicity.

Note that the politician’s strategic calculation to play the identity card in this special case alsoparallels the earlier finding. Consider A’s strategy. A plays C if it increases her probability ofwinning the election. If neither candidate plays C, the probability that A wins is 1

2 . By contrast, ifonly A plays C, A’s equilibrium probability of winning equals 1

2 +ψ

ϕ−sad [sa(2ϕ −d)−ϕ ]c. Thus,A plays C if:

[sa(2ϕ −d)−ϕ ]c > 0. (23)

Just as before, we see that as c increases, A faces greater incentives to play C. Additionally,when c is positive, A plays C when sa >

ϕ(2ϕ−d) . A faces greater incentives to play C as the size of

group a in the electorate increases and as the identity dispersion effect decreases. By using simpleparameterizations, this special case illustrates the key intuitions arising from the broader model.

65