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Party-candidate linkages and Anti-Incumbency Voting:Evidence from the Indian States∗

Francesca R. Jensenius†and Pavithra Suryanarayan‡

April 30, 2017

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Abstract

Scholars studying developing democracies have been puzzled by high levels of elec-toral instability. An often overlooked factor in studies of voting behavior is the strengthof party-candidate linkages: the extent to which parties and candidates maintain sta-ble alliances in consecutive elections. In this paper we argue that weak linkages splitvoters’ loyalties between parties and candidates and diffuse the responsibility for whois to be held accountable for the performance in office, resulting in higher levels ofanti-incumbency, higher electoral volatility, and weaker economic voting. We show ev-idence for our claims using constituency-level electoral data from Indian state assemblyelections between 1987 and 2007 as well as individual-level survey data from the IndianNational Election Study from 2004. These results suggest that given stable electoralalternatives, voters in a developing democracy make their vote choice on the basis ofthe performance of the incumbent in much the same way as in developed democracies.

∗The authors would like to thank Rikhil Bhavnani, Jennifer Bussell, Pradeep Chhibber, Tina Freyburg,Irfan Nooruddin, Neelanjan Sircar, Milan Vaishnav, Rahul Verma and Steven Wilkinson for their valuablecomments on previous versions of this paper. The work on this paper was made possible by support fromthe Research Council of Norway. We thank Lokniti, New Delhi for making the National Election Study dataavailable to us.†Norwegian Institute of International Affairs (NUPI), email: [email protected]‡Johns Hopkins University, email: [email protected]

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1 Introduction

Developing democracies are often characterized as being afflicted by electoral instability.Scholars in regions as diverse as Latin America, Eastern Europe and South Asia have doc-umented two types of instability in particular – anti-incumbency voting and high electoralvolatility. High levels of electoral instability is troubling because it suggests that politicalrepresentation is failing and that the institutional bonds between parties, candidates, andthe constituents they are meant to represent are weak.

An extensive literature on electoral instability in developed democracies has emphasizedthe role of economic evaluation as a key factor in shaping how voters reward or punish incum-bents (Key and Cummings, 1966; Lewis-Beck, 1990; Tufte, 1980; Kramer, 1983; Anderson,2007). These studies find that when the economy is doing well, incumbents do well in elec-tions, and when the economy is doing poorly the voters respond by “throwing the rascals outof the office.” Where scholars have tried to link economic factors to electoral instability indeveloping countries, the evidence of the relationship has been more mixed (Remmer, 1991;Tavits, 2005; Tucker, 2002).

This paper provides an explanation for why we observe higher levels of electoral insta-bility, and why the relationship between the economy and electoral outcomes is weaker insome places than in others. An overlooked factor in studies of both electoral instability andeconomic voting is the strength of party-candidate linkages – the extent to which partiesand candidates maintain stable electoral alliances in consecutive elections. The idea thatstable party-candidate linkages is an important dimension of well functioning parties andparty systems is fairly intuitive. Yet, as noted by McElroy (2003, p. 2), this phenomenon“has received surprisingly little attention in the canon of political parties.” This omissionis unsurprising because studies of parties and elections typically focus on Northern Europeand the United States, regions where candidates usually run for re-election, and generally forthe same party.1 However, recent research from a wide range of countries, including Brazil,Ecuador, France, Italy, and Russia, finds that weak party–candidate linkages are, in fact,a relatively common phenomenon in both developed and developing democracies (Kreuzerand Pettai, 2003; Herron, 2002; Desposato, 2006; Heller and Mershon, 2005; Shabad andSlomczynski, 2004).

We examine party-candidate linkages and electoral instability in the world’s largestdemocracy – India. Elections in the Indian states are viewed as unusually chaotic withhigh levels of anti-incumbency voting in both national and state elections, and with lit-tle evidence of economic voting (Linden, 2004; Uppal, 2009; Ravishankar, 2009; Suri, 2009;Verma, 2012). While scholarship on Indian elections has primarily focused on fluid socialcleavages, clientelism, and the structural features of the states’ political economy to explaininstability, this paper builds on studies that focuses on the role of party organization inexplaining electoral outcomes – studies that argue that high levels of electoral volatility andfragmented party systems arise as a result of the inability of parties to accommodate the

1Party switching has been very uncommon in the United States in recent times, with only 20 membersof Congress changing parties between 1947 and 1994 (Nokken and Poole, 2004).

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career aspirations of candidates due to weak internal organization (Chhibber, Jensenius andSuryanarayan, 2014) or a reliance on dynastic candidates (Chhibber 2011).

In this paper, we argue that the stability of linkages between parties and candidates inconsecutive elections is an important dimension of party organization and a key factor inexplaining electoral instability in Indian elections. Party-candidate linkages mediate waysin which party organization matters for vote choice. First, they shape the extent to whichthe incumbent party benefits from the “personal vote.” Second, they affect party-voter link-ages or the extent to which voters value partisanship. Finally, they shape the extent towhich incumbent parties can bank on the incumbent’s performance record in office. Thus,party-candidate linkages exert both a direct effect on vote choice through the weakening offactors that bind voters to parties, and an indirect effect through the difficulty of assigningresponsibility for economic events and thereby vote economically.

We study party-candidate linkages by tracking the rerunning patterns of candidates instate assembly elections in India in 25 states and approximately 3,800 constituencies (elec-toral districts) in consecutive elections held from 1987 to 2007. First, we show that the muchdocumented anti-incumbency phenomenon in the Indian states disappears in constituen-cies where the incumbent politician reran for the same party as in the previous election.Reversely, anti-incumbency is higher that commonly thought in constituencies where theincumbent politician reran for another party or did not rerun at all. We also show thatconstituencies where the incumbent party, the first runner-up, and the second runner-upfielded the same candidates were associated with lower electoral volatility than constituen-cies where the first, second and third placed candidate either switched parties or did not runfor re-elections.

Next, using district-level rainfall as an exogenous proxy for the state of the economy, weshow that places where incumbent parties fielded the incumbent candidate were associatedwith stronger economic voting compared with places where candidates did not rerun orcandidates switched parties. We find that these same patterns hold at the individual-leveltoo, using survey data from the Indian National Election Study (NES) from 2004. Togetherthese findings demonstrate that weak party-candidate linkages are strongly associated withelectoral instability, and that given stable electoral alternatives, voters in the Indian statesexhibit economic voting patterns that resemble those in developed democracies.

This paper’s primary contribution is in demonstrating the role party organization at thelocal level plays in stable electoral dynamics. Writing about Latin America, (Roberts andWibbels, 1999, p. 587) pointed to the importance of the economy on voting is deeply affectedby institutional and structural factors in the country: “In much of the region, party systemsare neither well institutionalized nor grounded in social cleavages, and they do not closeoff the electoral marketplace by encapsulating voters or articulating clearly differentiatedideological and programmatic platforms. In the absence of strong organizational ties andcollective identities, individual voter mobility is very high, and the social foundations ofelectoral competition are fluid and unstable.” In their study they do not, however, look atthe interactions between institutionalization and voting patterns. In this paper we furtherdevelop the ideas about how party institutionalization is linked to voting patterns and test

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these claims at the constituency-level, with a new large dataset that traces the rerunningpatterns of almost 80,000 political candiadtes across India.

This paper also contributes to an extensive scholarship on incumbency voting, and inparticular a growing number of studies that document the curious phenomenon of “anti-incumbency” voting in the developing world (Linden, 2004; Uppal, 2009; Klasnja, 2015;Klasnja and Titiunik, 2017). While these empirical studies have primarily focused on thedaunting empirical task of identifying the very existence of an incumbency disadvantage, orhave looked to the performance of politicians in office for explaining their electoral disad-vantage, we offer a mechanism grounded in party organization that explains where such aphenomenon may arise.

We also contribute to a growing literature on economic voting in the Indian states (Ravis-hankar, 2009; Suri, 2009; Verma, 2012). Ethnic identity, patronage, and clientelistic exchangehave played a central role in studies of Indian electoral politics. The effect of economic factorshas been underplayed because politics is viewed as highly transactional at the local-level,and centralized at the party-level, with leaders making decisions about policy as well asticket allocations to contest elections at the local level. The findings of this paper indicatethat economic voting is an important aspect of politics in Indian state elections – but, thatthe extent to which the economy matters is mediated by the durability of party-candidatelinkages at the local level.

Finally, this paper speaks to studies of party switching, that typically have been focusedon legislative floor-crossing. For example, Heller and Mershon (2005) find that over one-quarter of legislators in the Italian lower house changed parties between 1996 and 2001.Whereas floor-crossing is an important manifestation of weak party-candidate linkages, ourdata from India – where legislative floor-crossing was made illegal in 1986 – allows us to shedlight on other forms of weak linkages such as party splits or mergers, parties fielding newcandidates, or candidates changing parties from one election to the next. The findings inthis paper show that enhancing our knowledge of these other manifestations of weak party-candidate linkages is vital for understanding electoral dynamics in much of the democraticworld.

2 The importance of party-candidate linkages

Anti-incumbency in Indian elections is a well-documented phenomenon. Using aggregateelection results and a regression discontinuity design (RDD), Linden (2004) and Uppal (2009)found that incumbents are at a disadvantage in both national and state elections. The left-hand plot in Figure 1 – which is a replication of Figure 1 in Uppal’s article2 – shows that

2The plot is an approximate replication based on the information provided in the article. Following him,we use state assembly level data from 1991–2003. He included all the states in India except Jammu andKashmir. We include all except Jammu and Kashmir and Arunachal Pradesh. Our data also differs slightlyfrom his in that he only included candidates that got at least 5% of the vote share in a constituency in hisdataset. We consistently include the top five candidates in our dataset, meaning that we include a highernumber of candidates. Our data and coding is further described in Section 3.1 and Appendix B.

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after 1991 incumbent politicians in India were less likely to be re-elected than a similarlyqualified runner-up from the previous election. Contrary to what has been observed in otherparts of the world, Indian politicians have not been found to have any electoral advantagefrom holding office, but rather a small disadvantage. The right-hand plot shows the sameanti-incumbency pattern for incumbent parties during the same period. Here too we see aclear pattern of anti-incumbency voting.

Figure 1: Anti-incumbency voting in Indian state elections, 1991–2003

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(a) Note: The plots show that incumbent candidates and parties were at a disadvantage in stateassembly elections held in India 1991–2003. This is demonstrated by the discontinuity in theprobability of winning the current election as the Margin of Victory tended towards zero in theprevious election. Incumbents who had won by a close margin in the previous election were lesslikely to win the next election than their closest opponents.

Anti-incumbency is surprising because it turns on its head a long-standing finding instudies of incumbency in developed countries. Incumbents are expected to benefit electorallybecause they on average are likely to be higher quality candidates, are able to signal theirquality through the service they performed while in office, can use the state apparatus to theirelectoral advantage, and are more likely to benefit from weak partisan attachments. Giventhe appeal of these arguments, it is puzzling why incumbents in India are at a disadvantage.This suggests that there are systematic reasons for incumbents to be viewed less favorablyby voters. Recent work aimed at explaining this phenomenon in the developing world hasfocused on factors such as corruption in office (Klasnja, 2015) and structural factors such asterm limits (Klasnja and Titiunik, 2017). Voters facing a pool of poor quality candidates,who have short time-horizons and use political office to enrich themselves, are reluctant toreelect politicians. In a similar vein, scholars of Indian politics have suggested that votersuse the electoral ballot box as an accountability mechanism and facing corrupt candidates,

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“throw the rascals out” in every cycle.We turn to another literature, on party organization, to explain anti-incumbency voting

in India. A large body of research has examined the effects of party institutionalization onelectoral stability, focusing primarily on electoral volatility and party-system fragmentation.Authors have argued that stable linkages between parties and voters, the organizational rou-tinization of parties through standardized rules for candidate nomination and career develop-ment, and the clarity of parties’ brands and their policy positions will be more likely to leadto stable electoral dynamics (Huntington, 1968; Mainwaring and Scully, 1997; Panebianco,1988; Janda and King, 1985). Institutionalization of parties matters in two ways. First, anorganization’s practices such as internal elections, leadership selection processes, career de-velopment and the extent to which a party is internally democratic, cohesive and routinizedare likely to shape candidate’s calculations about staying with a party or leaving a partyto seek better career prospects. These dynamics are visible in the Indian case, where stateswith more organized parties have been found to have lower levels of electoral volatility andlower effective number of parties (Chhibber, Jensenius and Suryanarayan, 2014). Second itmatters how voters view parties. Through stable electoral alternatives and clear linkagesbetween parties and candidates, voters are able assess a party’s performance in office andits prospects for the future. A party’s internal organization is likely to shape how a partyis viewed by voters and what they come to know and believe about their politicians’ back-ground, their policy preferences and their electoral platform. Harmel and Svasand (1993)suggests that this dimension of party organization is the extent to which a party becomes“reified in the public mind.”

We argue that an important aspect of becoming reified in the public mind – a routinepart of the system – is continuity in the electoral options that voters face in consecutiveelections. This involves (1) parties presenting themselves to the public in every election, (2)the same candidates appearing in elections, and (3) and stable links between parties andcandidates: in other words, strong party-candidate linkages.

We believe the strength of party-candidate linkages to be an important predictor ofelectoral instability for three key reasons. First, a significant factor, particularly in first-past-the-post electoral systems is the role of the incumbent candidate’s “personal vote”in determining the incumbent party’s advantage. When an incumbent switches parties ordoes not rerun, this can partly or wholly eliminate a party’s incumbent vote advantagewhich is a result of familiarity with a particular incumbent politician. Second, the strengthof party-candidate linkages is likely to be related to the strength of party-voter linkages.Weakly institutionalized parties enable candidates to move across parties and allow partiesto field candidates of different ideological leanings and ascriptive backgrounds from electionto election. This is likely to weaken voter’s sense of partisanship and thereby the linkagesbetween parties and voters.

Finally, if the candidate changes, the party may not be able to retain the associationwith the incumbent politician’s constituency service record – such as helping constituentssecure public goods, navigate the administrative labyrinth, or secure jobs – a record whichis exclusively her own to bank on. A well performing incumbent politician may be able to

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command a significant vote-bank regardless of party and is even more likely to be popularwhen the economic conditions are good. Inversely, when a candidate is unable to deliver ongoods and services or whose term coincides with weak economic conditions, then a party can“shed the baggage” and seek a new candidate. It may therefore be less likely to suffer a lossof vote from a weakly performing incumbent.

Figure 2: Candidate incumbency in Indian state elections, 1991–2003, divided by rerunningpatterns

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Figure 3: Party incumbency in Indian state elections, 1991–2003, divided by rerunningpatterns

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Given these arguments, we should expect weak party-candidate linkages to be associatedwith higher levels of anti-incumbency, higher levels of electoral volatility, and less economicvoting. In Figures 2 and 3 we illustrate how the RDD-estimate of anti-incumbency votingin Indian state elections to a large extent seems to be driven by the rerunning patterns of

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the incumbent politicians. Using the same data as in Figure 1, Figure 2 shows that whencandidate runs for the same party as in the previous election the incumbency disadvantagedisappears. However, when the incumbent candidate changes party affiliation we observe alarge incumbent disadvantage. In Figure 3 we show the incumbency effects from the partyperspective, and similarly find that the incumbency disadvantage by far is the most severewhen an incumbent politician switches parties and runs against the incumbent party. Whenthe incumbent party and candidate maintain their electoral alliance, the disadvantage isnegligible.

Weak party-candidate linkages also matter for economic voting. In developed democra-cies it is a well established fact that voters tend to support rerunning incumbents when theeconomy is doing well (Key and Cummings, 1966; Lewis-Beck, 1990; Tufte, 1980; Kramer,1983; Anderson, 2007). On the other hand, studies of economic voting in developing democra-cies have been far from conclusive. Remmer (1991) examined 21 elections in Latin Americabetween 1982 and 1990 and found that adverse economic conditions are associated withhigher levels of electoral volatility. Other studies, however, are less suggestive of a link be-tween performance and outcomes. In a study of electoral volatility in Latin America in the20th century, Coppedge (1995) found a limited effect of economic performance on electoralvolatility. Similarly, in a study of 15 Eastern European democracies Tavits (2005) showedthat while higher GDP growth and lower inflation seem to reduce volatility, the overall effectof economic factors on volatility dissipate as the democracy matures. In a review of thevoting literature in Eastern Europe, Tucker (2002) reported that there was a divergence inthe answers from those who do macro-level work — and find a correlation between economicconditions and election outcomes — and micro-level studies — where no clear relationshipis found.

Studies of Indian politics too have found some weak evidence of economic voting. Rav-ishankar (2009) found limited overall evidence for an effect of economic performance on thesupport for the incumbent, but showed that voters tend to punish parties at both levels ofgovernment if they are unhappy with the performance of politicians at any level.3 Analyzingdata from the NES from 2004 and 2009, Verma (2012) similarly found evidence that vot-ers’ propensity to support the incumbent was associated with how satisfied they said theywere with the economy, but that it also depended on their evaluation of the performanceof their Member of Parliament (MP), their satisfaction with the performance of the statelevel cabinet, as well as satisfaction with the government at the national level. Studyingdata from the NES 2009, Suri (2009) reported of a weak positive association between voter’sperception of the national economy and their propensity to vote for parties in the rulingcoalition. He found a stronger relationship, however, between voter’s perception of theirhousehold economy and their propensity to vote for parties in the ruling coalition. But it isunclear to what extent these patterns are driven by post-justification bias, i.e., the extent towhich voters say they are satisfied with the economy when the party or person they voter

3Interestingly, she reported a reverse pattern in “honeymoon” elections where a state election follows anational election or vice versa, as in such elections voters have an incentive to put the same party into powerat both levels. This incentive decreases as parties stay in power longer.

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for is in power.Our contention is that the link between economic conditions and voting is shaped by

the party institutional environment. When parties are organizationally weak, and the tiesbetween parties and candidates are tenuous, it is likely that incumbent parties will be unableto convincingly articulate their economic credentials to voters. In turn, voters may rewardor punish either the candidates or the party for economic performance, reducing aggregatesupport for the incumbent parties when incumbent candidates do not run for the same party.In the next section we test these claims using data from Indian state elections.

3 Party-candidate linkages and electoral instability in

the Indian states

To test the theoretical argument laid out in the previous section, we look at the associationbetween party-candidate linkages and electoral instability – anti-incumbency voting andelectoral volatility – as well as patterns of economic voting in Indian state elections.

India is an important country for the study of party and party system institutionaliza-tion, as it challenges many of our typical explanations of democratic stability, party systemconfigurations, and electoral outcomes. With its first-past the post electoral system, thestandard expectation in the political science literature would be a coordination around a fewparties at the constituency level, which would aggregate up to a few parties at the state andnational level (Duverger, 1959; Cox, 1997). We should also expect to see the party systemstabilizing over time as India has become a consolidated democracy (Mainwaring and Zoco,2007). Nevertheless, India has gone from a fairly stable party system dominated by one party– the ‘Congress System’ (Kothari, 1964) – to a fragmented system with a large number ofparties dominating different parts of the country.

India is also a country known for its weak party-candidate linkages, including factionalsplits of parties and ‘defections’ (or floor-crossing) in state assemblies as well as in theparliament (Kashyap, 1970). This trend grew stronger as the Congress party gradually lostpower and politicians saw opportunities by exiting to other parties. The result was thepassing of the Anti-Defection Act in 1985, which disqualified elected members of parliamentor state assemblies who defected to other parties during their time in office.4 This reducedthe occurrence of legislative floor-crossing, but did not prevent other manifestations of weakparty-candidate linkages, such as party splits, low re-running rates, and candidates runningfor other parties.

4This was implemented as the 52nd Amendment to the Indian Constitution. The Act had a loop-hole: it was deemed a party-split (and not a defection) if more than 1/3 of a party left an ex-isting party. There have, in fact, been several disqualifications as a result of this Act (see [URL]http://www.prsindia.org/administrator/uploads/general/1370583077 Anti-Defection %20Law.pdf).

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3.1 Data and key variables

We operationalize party–candidate linkages by examining the rerunning patterns of partiesand candidates in India’s state assembly elections. The dataset covers 92 state assemblyelections held in 25 Indian states between 1987 and 2007.5 This includes information aboutclose to 3,800 constituencies and 16,625 constituency-level electoral contests. The stateelections included in the sample are listed in Table 4 in Appendix A.

In the period we examine boundaries of the constituencies remained unchanged acrossIndia, allowing us to trace what happens in the same constituencies over time. Focusing inon this period also has the advantage that we avoid the particularly turbulent years fromthe mid-1970s until the mid-1980s when there were several party splits and mergers resultingfrom controversies around the rule of the Prime Minister Indira Gandhi. When parties split,almost all the politicians ended up running under different party labels from one election tothe next, resulting in extremely high levels of electoral volatility. The period we are lookingat had less extreme values, making it easier to look at how the variation in party-candidatelinkages from one constituency to another affected voting patterns. Additionally, since theanti-defection law was passed in 1986 we know that weak party-candidate linkages that weobserve is not just a by-product of legislative floor-crossing.

In our data there was on average about 10.6 candidates in each constituency, but thisaverage is pulled up by a few cases with a large number of candidates and the median numberof candidates is about 9.6 However, most votes usually go to only a few candidates and onaverage the effective number of parties calculated by votes is about 3 at the constituencylevel.

For each of the electoral races in our sample we identified the vote-share for the incumbentparty and also manually coded each of the top five candidates as rerunning if they wereamong the top five candidates in the previous election too, coded what position they held inthe previous election and whether or not they ran for the same party. This manual codingcovered the rerunning patterns of some 79,530 candidates.7 Based on this manual codingwe identified whether the candidates that had run in the previous elections reran for thesame party, reran for another party, or did not run for re-election.8 In this paper we look at

5These are almost all the Indian states during this period, with the exception of Arunachal Pradesh(due to missing data), Jammu and Kashmir (due to a delimitation of electoral boundaries in 1996), andUttarakhand (because of a delimitation in 2001), and a few elections that are missing for Northeast India.The election data are available in PDF format at www.eci.gov.in, but were scraped, parsed, and cleanedof errors (see Jensenius, 2016).

6The highest number of candidates during this time period was in a constituency in Tamil Nadu, wherethey had as many as 1,033 contesting candidates during the 1996 state assembly elections.

7We chose to use the top five candidates since as candidates further down on the list rarely get morethan a few percentage points of the vote, and manually checking all the candidates (up to more than 1,000candidates in a single constituencies) would be a massive task. In the median constituency our codingincludes the candidates that got 99% of all the votes (meaning that we are excluding candidates that gotabout 1%) of the votes. In 93% of the constituencies we capture more than 90% of the votes. The codingwork is further described in Appendix B.

8In the cases where candidates were found to rerun for the same or a different party we are certain abouttheir rerunning status. Where politicians were not found among the top five candidates they may have either

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these patterns for the incumbent politician, as well as the first and second runners-up in theprevious election.

Of the 16,625 electoral races included in the dataset 56% included an incumbent politi-cians rerunning under the same party label, in 17% of the cases the incumbent politicianran under a different party label, while in the remaining cases the incumbent politician didnot run for re-election. There is therefore a considerable number of incumbents who ran forre-election for another party. In some cases this was a change from being a member of aparty to running as an independent (or vice versa), in other cases politicians changed partybecause parties split or merged, but in many cases incumbents also completely jumped shipto another established political party. As we can see if Figure 4, the share of incumbentpoliticians running for re-election was fairly stable across the years, with a slight trend ofmore of them running for the same party over time.

Figure 4 also includes information about the rerunning patterns of the incumbents mainelectoral opponents in the previous election. An average of about 26% of runner-ups ran forre-election for the same party, and another 15% for other parties. Most of the runner-ups didnot run for re-election. Of third-ups, only about 9% ran for re-election for the same party andanother 8% for another party. For the fourth and fifth candidates, few were found to haverun for re-election in the same constituency. Altogether this shows there was little continuityin the candidates across elections, and even less continuity in which parties candidates ran– there are weak linkages between parties and candidates.

Figure 4: Rerunning patterns for politicians in Indian state elections, 1987–2007

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Rerunning patterns is our main explanatory variable of interest. From the election datawe also create measures for the outcome variable we are interested in – electoral instability,operationalized as the vote share for the incumbent party and electoral volatility at theconstituency level. We also create important control variables, the number of candidatesand the number of electors in each election and the margin of victory and the turnout in theprevious election. The creation of each of these variables are described in Appendix B.

3.2 Anti-incumbency voting

In Figures 2 and 3 we illustrated how the RDD-estimate of anti-incumency voting in Indiato a large extent seems to be driven by the rerunning patterns of incumbent politicians.Dividing the RD estimate according to rerunning patterns of the incumbent politician isinformative, but should not be seen as a causal estimate, since parties’ choices about can-didate nominations and candidate rerunning choices are endogenous to how well they thinkthey will do in an election. The RD estimates also focus in on competitive elections, andparticularly the comparison between the incumbent and the runner-up, rather than considerthe full range of electoral contests. To further explore the association between rerunningpatterns in the vote share for the incumbent party, we turn to multilevel regression models(MLM).

Table 1 shows the output from MLM models of the vote-share of the incumbent party re-gressed on candidate rerunning patterns. Our constituency-year observations are nested intoassembly constituency (AC) and year levels. In other words, we estimate a varying-interceptmodel where we allow intercepts to vary by AC and year. This modeling specification allowsus to get around the problem of introducing AC level fixed effects that decrease the degreesof freedom of the models, and also allows us to include AC-level control variables that areslow moving over time.9

Model 1 has the rerunning patterns of incumbent politicians as the only explanatoryvariable in addition to the higher-level variables. The incumbent candidate running for theincumbent party is the excluded category.10 The intercept of 39.4 indicates the average voteshare for the incumbent party, given that the incumbent politician reruns for the incumbentparty. The incumbent politician running for another party within the same constituency isassociated with a drop of 16.7 percentage points, and the incumbent politician not runningfor re-election at all with a 3.7 percentage point drop. These large and highly statisticallysignificant coefficients reflect the large differences in the party incumbency disadvantage thatwe illustrated in Figure 3.

9Time-Series Cross-Section datasets have generated much debate in the political science field. Differentauthors suggest a sequence of diagnostics to be able to include lag-variables, error correction routines and toarbitrate between a multitude of standard error corrections such as PCSE, WLS and FGLS. MLM modelshave also become popular as it has been found that multilevel estimates perform better than OLS and FixedEffects models in Monte Carlo simulations (Shor et al., 2007).

10The outcome variable we use is the vote share of the incumbent party, conditional upon the incumbentparty running for re-election. In Appendix D show the same models with the vote share of the incumbentparty set to 0 if the party did not run for re-election.

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Model 2 includes further control variables to check the robustness of the patterns: thevote share for the incumbent party in the previous election, the number of electors in theconstituency, the number of candidates running in the same election, as well as the turnoutand margin of victory (MoV) in the previous election. Despite the inclusion of these addi-tional control variables, the coefficients for the rerunning patterns of the incumbent politicianremain similarly large and highly statistically significant.

Whereas the rerunning pattern of the incumbent politician may be thought to be of mostimportance for the fate of the incumbent party, the party-candidate linkages of other partiesmight also matter for electoral instability. It may be to the advantage of the incumbent partyif the main contenders from the previous election do not run for re-election. This intuition isconfirmed in Model 3 and 4, where we also include information about the rerunning patternsof the runner-ups and third-ups in the same constituency in the previous election. Theexcluded categories are the candidates rerunning for the same party – the lower intercept istherefore a reflection of the disadvantage the incumbent party faces when their opponent runthe same candidates. In this case, we see that it is to the advantage of the incumbent partywhen the main competitors do not run for re-election, while it makes less of a difference ifthese competitors run for the same party or for another party.

Weak party-candidate linkages among other parties does also greatly affect the overallelectoral volatility in the constituency.11 As electoral volatility is calculated on the basisof vote shared for parties, it will be greatly affected by shifting party-candidate alliances ifthese shift vote choice from one party to another. This, in fact, seems to be the case, as thererunning pattern of the incumbent politician and the runners-up in the previous election areall strong predictors of electoral volatility at the constituency level, as shown in AppendixC.

3.3 Party-candidate linkages and Economic Voting

To test for our second hypothesis, that economic voting is likely to be more pronouncedin more institutionalized contexts, we are interested in the association between incumbentrerunning patterns and the vote share for the incumbent party in the state of a good economicenvironment and a poor one. India is to a large extent a rural economy with a large part ofthe population working in the agricultural sector. The amount of rainfall than an area gets istherefore an important determinant of income in the agrarian sector and also a determinantof food prices both the rural and urban population. Rainfall can therefore be seen as a goodproxy for local-level fluctuations in the economy affecting both rich and poor voters, andthis is what we turn to as an exogenous measure of the local-level state of the economy.

The measure we use to capture variation in rainfall is Lagged Rainfall Deviation: theabsolute value of the standard deviation from good rainfall at the administrative districtlevel in the year before an election.12 In our data, this variable runs from 0 to about 4.5,

11Following Pedersen (1983), electoral volatility is calculated as EV = 12Σn

i=1|pit − pi(t−1)|.12This variable is based on monthly gridded precipitation and temperature data produced by the Indian

Meteorological Department (Rajeevan et al., 2005; Srivastava, Rajeevan and Kshirsagar, 2009), convertedto yearly district-wise figures by area-weighted averaging over grid points falling within a given district

13

Table 1: Vote share for the incumbent party given rerunning patterns of politicians, India1977–2007

Model 1 Model 2 Model 3 Model 4

(Intercept) 39.4∗∗∗ 39.1∗∗∗ 35.1∗∗∗ 36.0∗∗∗

(0.9) (0.7) (1.0) (0.8)Incumbent runs other party −16.7∗∗∗ −15.9∗∗∗ −16.8∗∗∗ −16.0∗∗∗

(0.4) (0.4) (0.4) (0.3)Incumbent does not rerun −3.7∗∗∗ −3.6∗∗∗ −3.5∗∗∗ −3.5∗∗∗

(0.2) (0.2) (0.2) (0.2)Runnerup reruns other party 0.1 0.5

(0.3) (0.3)Runnerup does not rerun 3.2∗∗∗ 2.9∗∗∗

(0.2) (0.2)Third-up reruns other party 0.2 0.7

(0.5) (0.5)Third-up does not rerun 2.7∗∗∗ 1.5∗∗∗

(0.4) (0.4)

AC and Year Random Effects Y Y Y YControl variables N Y N YN 14339 14339 14339 14339

Log-likelihood −56763.5 −55893.3 −56614.1 −55801.0Deviance 113527.0 111786.6 113228.2 111601.9AIC 113539.0 111808.6 113248.2 111631.9BIC 113584.4 111891.8 113323.9 111745.5

Note: Multilevel regression models, where constituency-year observations are nested in constituencies andyears. Constituency-years where the incumbent parties did not run for re-election are excluded. Controlvariables are vote share for the incumbent party in the previous election, the number of electors in theconstituency in the same election, the number of candidates running for election, as well as the electoralturnout and margin of victory in the previous election.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

where 0 signifies good rainfall and higher values means unusually high or low rainfall. Wehave the rainfall data for India’s 15 largest states, and are therefore using a somewhat smallersample here than in the previous analyses. The state-year elections included in these analysesare listed in Appendix A (Table 5).

Table 2 shows the output from MLM models of the vote-share of the incumbent party re-gressed on candidate rerunning patterns and rainfall. Model 1 shows the association betweenRainfall deviation and the vote share of the incumbent party. While previous literature hasreported of very limited evidence of economic voting, we observe a negative association:the vote share for the incumbent party was somewhat lower in places that had experi-ences unusually good or bad rainfall in the year before the election. When we introduce

(Blakeslee and Fishman, 2014). Following, Cole, Healy and Werker (2012) we used these data to calculatethe absolute deviation of normalized rainfall from the optimum (which they find to be 1 standard deviation

above the district mean): | Raindt−Raindt

Sd− 1 |.

14

constituency-level control variables in Model 2, this association is statistically significant.Our expectation is for economic voting to be mediated by the rerunning patterns of the

incumbent politician. To see whether this is the case, we look at the interaction betweenrerunning patterns and rainfall in Models 3 and 4. Here we see that the coefficient for rain-fall grows larger – meaning that there is more evidence for economic voting in constituencieswhere the incumbent politician reran for the incumbent party. There is also a highly sta-tistically significant positive interaction term between Rainfall deviation and the incumbentpolitician running for another party. This means that where the economy has been doingbadly, the incumbent party benefits from their incumbent politician running against themfor another party. There is a positive interaction between the incumbent politician not re-running and rainfall too – the economic voting pattern is attenuated when the party fieldsa new candidate. However, this association is not statistically significant at conventionallevels.

Table 2: Economic voting in India given rerunning patterns of politicians

1977–2005 1977–1990 1991–2005 1991–2005

(Intercept) 36.4∗∗∗ 36.6∗∗∗ 39.4∗∗∗ 39.4∗∗∗

(1.0) (0.9) (1.0) (0.8)Rainfall deviation −0.3 −0.5∗∗ −0.6∗∗ −0.8∗∗∗

(0.2) (0.2) (0.2) (0.2)Incumbent runs other party −20.0∗∗∗ −19.2∗∗∗

(0.8) (0.7)Incumbent does not rerun −4.4∗∗∗ −4.0∗∗∗

(0.5) (0.5)Rainfall dev. × incumb. runs other party 2.0∗∗∗ 2.2∗∗∗

(0.6) (0.5)Rainfall dev. × incumb. does not rerun 0.5 0.4

(0.4) (0.4)



Note: Multilevel regression models, where constituency-year observations are nested in constituen-cies and years. Constituency-years where the incumbent parties did not run for re-election are excluded.Control variables are vote share for the incumbent party in the previous election, the number of electors inthe constituency in the same election, the number of candidates running for election, as well as the electoralturnout and margin of victory in the previous election.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

This relationship is illustrated in Figure 5. Here we see the prediction from Model 4 inTable 2 for the situation of the incumbent politician rerunning for the same party or for

15

another party.13 The third option of the incumbent politician not running for re-election liesbetween these two scenarios. Here we can see quite clearly that in constituencies with goodrainfall, the incumbent party benefitted from rerunning the same candidate. However, athigh levels of rainfall deviation (more than about two standard deviation from good rainfall)the incumbent party was better off electorally if they ran a new candidate and the incumbentpolitician ran against them for another party.

Figure 5: Economic voting given the rerunning patterns of politicians, 1987–2005

0 1 2 3 4

3035

4045

Rainfall deviation

Vot

e sh

are

for

incu

mbe

nt p

arty

Incumbent runs for same partyIncumbent runs for other party

To further explore this pattern, we turn to survey data. We use individual-level responsesfrom the 2004 National Election Study (NES) conducted by Lokniti, Center for the Studyof Developing Societies, New Delhi. The NES survey was conducted in the aftermath of theparliamentary elections of 2004 and has data on a random sample of 27,189 electors fromacross the Indian states.14 To make this analysis comparable to the analysis presented inTable 2 we restrict the sample to the 15 largest states for which we have rainfall data. Ourdata therefore consists of 14,675 respondents from 361 parliamentary constituencies (PCs)across 15 Indian states.

13The estimates and confidence intervals are based 10,000 simulated values generated using the variance-covariance matrix of Model 4. The intercept and the relevant rerunning variable were set to 1 and theremaining variables were set to their mean.

14The survey was conducted in 22 languages and census data from the 2001 Indian census was used toensure that there was adequate representative of ethno-linguistic communities in the states with a particularfocus on ensuring sufficient sampling from marginalized groups such as scheduled castes and tribes. Seewww.lokniti.org for further information about the survey.

16

The outcome we are looking at is whether or not an individual voted for the incumbentparty in their PC. The main explanatory variables are the rerunning pattern of the incumbentpoliticians, coded at the PC level, and the same measure for rainfall deviation as we usedin the previous section.15 The survey also includes measures for voters’ perception of theeconomy, as has been explored by among others Suri (2009). These measures are correlatedwith vote choice and with rainfall. However, to avoid post-justification bias we use rainfallas an exogenous measure of the state of the economy.

Table 3 shows the output from MLM models looking at the association between incum-bent politicians’ rerunning patterns and voter’s propensity to vote for the incumbent partyin their PC. Individuals are nested in PCs. At the PC level, the majority (238, or 66%)of incumbent politicians reran for the same party, 22 (6%) ran for another party, and 101(28%) did not rerun. When we nest individuals in PCs we therefore have little power forthe category of incumbents running for another party. In these models we have thereforecollapsed Incumbent rerunning for another party and Incumbent does not rerun into a singlecategory: Other Party/Not rerunning. This change gives us a bit more power for the esti-mates, but does not substantially change the size or direction of the coefficients, as shownin Table 9 in Appendix D.

In Model 1 in Table 3 we show the association between rainfall deviation and voters’propensity to vote for the incumbent party. If voters voted on the basis of the state of theeconomy we should expect a negative coefficient. The coefficient is positive, but not statis-tically significant. In Model 2 we include individual level controls: indicators for whether ornot the person voted for the incumbent party in the previous election, for whether the voterwas a man or a woman, the community of the person (Muslim/SC/ST/other), and whetherthey lived in a rural or urban area. The controls flip the coefficient for rainfall deviation tonegative, but it is still far for statistically significant. In Models 3 and 4 we interact rainfalldeviation with whether the incumbent politician ran for the same party or not. In Model 4,where we also include controls, this yields a much larger negative coefficient for rainfall. Thiscoefficient is in the direction we should expect and is close to being statistically significantat conventional levels. As expected, we also see a strong, positive, and statistically signif-icant interaction between rainfall deviation and rerunning patterns. These individual-levelpatterns are therefore consistent with what we observed in the AC-level data.

Figure 6 illustrates the interaction between rainfall deviation and rerunning patterns.The plot show 10,000 simulated values generated using the variance-covariance matrix ofModel 4 in Table 3. The predictions are set to having an individual either living in a PCwhere the incumbent politician reran for the same party or not. Across both these scenarios,individuals are set to having voted for the incumbent party in the previous election, beingmale, from a rural area, and being from the category “other” in the community variable.The plot illustrates the pattern we should expected on the basis of our theoretical discussion:That in PCs where the incumbent politician reran for the incumbent party, the incumbentparty does better when the economy is doing well. Inversely, when the economy is doing

15The rerunning data at the PC level was coded in the same way as the AC-level data. See Appendix Bfor further information about these data.

17

badly, the incumbent party benefits electorally from running a new candidate.

Table 3: Propensity to vote for the incumbent party, given rainfall and candidate runningfor the incumbent party


(Intercept) −0.45∗∗∗ −2.30∗∗∗ −0.22∗ −1.96∗∗∗

(0.08) (0.13) (0.10) (0.16)Rainfall deviation 0.07 −0.02 −0.02 −0.12

(0.05) (0.07) (0.07) (0.09)Other Party/Not rerunning −0.63∗∗∗ −0.61∗∗

(0.17) (0.23)Rainfall dev. × Other Party/Not rerun 0.25∗ 0.32∗

(0.11) (0.15)

PC Random Effects Y Y Y YControls N Y N YN PCs 361 361 361 361N respondents 14675 11515 14675 11515


Note: Multilevel logit model. The data are at the individual level, but are nested in PCs. Control variablesare whether the person voted for the incumbent in the previous election, woman/man, Muslim/SC/ST/otherand Urban/Rural.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

18

Figure 6: Economic voting given the rerunning patterns of politicians, NES 2004

0 1 2 3 4

0.6

0.7

0.8

0.9

1.0

Rainfall deviation

Pre

d. P

rob.

vot

ing

for

incu

mbe

nt

Incumbent runs for same partyOther party/Not rerunnning

4 Conclusions

In developed democracies it is a well established fact that incumbents tend to have an ad-vantage on election day, particularly if the economy is doing well. In developing democraciesthese patterns are not as evident: there is evidence of anti-incumbency voting, high electoralinstability, and little economic voting. In this paper we have argued that party-candidatelinkages – the extent to which voters face stable party and candidate options from one elec-tion to the next – is key to understanding such outcomes. Whereas stable party-candidatelinkages seem to be taken for granted in much of the literature on elections and voting, stud-ies from across the world report of different forms of weak linkages. In some countries partiesregularly split, merge, or change their names. In others, legislative floor-crossing is rampant.And in others again, like in the Indian case we have discussed in this paper, incumbent par-ties change out many of their candidates from election to election and incumbent politiciansoften end up running against the incumbent party. From the voter point of view this resultsin ever-shifting and confusing electoral options – breaking party-voter linkages and makingit unclear whmo to reward or punish for the economic performance of incumbents.

In this paper we have demonstrated the prevalence of weak party-candidate linkagesin India and how this is associated with electoral instability and economic voting. Usingconstituency-level electoral data from Indian state assembly elections between 1987 and2007, we have shown that anti-incumbency voting to be more common where the incumbentpolitician either did not rerun or reran for another party. Using both constituency-level

19

data and individual-level data from the NES 2004 we also showed that where incumbentpoliticians reran for the same party there was evidence of economic voting. Overall, ourfindings indicate that given stable electoral alternatives and clear party-candidate linkages,voters in a developing democracy make their vote choice on the basis of the performance ofthe incumbent in much the same way as in developed democracies.

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A Elections included in the data

Table 4: State-elections included in our dataset and analysis

State Elections included in the datasetAndhra Pradesh 1989 1994 1999 2004

Assam 1991 1996 2001 2006Bihar* 1990 1995 2000 2005

Chhattisgarh 1990 1993 1998 2003Goa 1994 1999

Gujarat 1990 1995 1998 2002 2007Haryana 1987 1991 1996 2000 2005

Himachal Pradesh 1990 1993 1998 2003 2007Jharkhand 1990 1995 2000 2005Karnataka 1989 1994 1999 2004

Kerala 1987 1991 1996 2001 2006Madhya Pradesh** 1990 1993 1998 2003

Maharashtra 1990 1995 1999 2004Manipur 1990 1995

Meghalaya 1988 1993 1998Mizoram 1989 1993 1998

Nagaland 1987 1989 1993 1998Orissa 1990 1995 2000 2004

Punjab 1992 1997 2002 2007Rajasthan 1990 1993 1998 2003

Sikkim 1989 1994 1999Tamil Nadu 1989 1991 1996 2001 2006

Tripura 1988 1993 1998Uttar Pradesh*** 1989 1991 1993 1996 2002 2007

West Bengal 1987 1991 1996 2001 2006*Excluding the part that became Jharkhand in 2001.**Excluding the part that became Chhattisgarh in 2001.***Excluding the part that became Uttaranchal in 2001.

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Table 5: State-elections included in the analysis of economic voting

State Elections included in the datasetAndhra Pradesh 1989 1994 1999 2004Assam 1991 1996 2001Bihar* 1990 1995 2000 2005Gujarat 1990 1995 1998 2002Haryana 1987 1991 1996 2000 2005Karnataka 1989 1994 1999 2004Kerala 1987 1991 1996 2001Madhya Pradesh** 1990 1993 1998 2003Maharashtra 1990 1995 1999 2004Orissa 1990 1995 2000 2004Punjab 1992 1997 2002Rajasthan 1990 1993 1998 2003Tamil Nadu 1989 1991 1996 2001Uttar Pradesh*** 1989 1991 1993 1996 2002West Bengal 1987 1991 1996 2001

*Excluding the part that became Jharkhand in 2001.**Excluding the part that became Chhattisgarh in 2001.***Excluding the part that became Uttaranchal in 2001.

B Data and coding of variables (in progress)

B.1 AC-level data

Rerunning candidates: To create the rerunning variables, the top five candidates in eachconstituency were manually coded as rerunning if they had been among the top fivecandidates in the same constituency in the previous election as well. We also recordedthe positions of the rerunning candidates in the elections and whether they ran againfor the same party. We chose to use the top five candidates since the vast majorityof votes across constituencies go to the top five candidates, and manually checkingall the candidates would be a massive task. We opted to look for rerunning patternsonly within the same constituency because of the difficulty of identifying people byname in other constituencies. There are always many candidates with similar namesin a given state, and if someone runs in another constituency for another party it ishard to know whether it is the same person. Similarly, it is hard to know whether acandidate is the same as someone with the same name who ran several elections earlier.This measure minimizes erroneous coding of candidates as rerunning when they arein fact not rerunning, but probably underreports how many candidates were in factrunning again. Considerable efforts were made to ensure data reliability. For moststates, the work of coding up rerunning patterns was done separately by two different

24

data companies, and the data were compared and corrected until the two versionscorresponded. In cases where the coders were in doubt, we went through the codingourselves—in practice, for ten of the states in the dataset. After that, the most reliablecoder was tasked with finishing the rest of the data.

INCLUDE TABLE WITH SUMMARY STATISTICS

B.2 PC-level data

FILL IN INFO ON OUR PC LEVEL DATA HERE, SUMMARY STATISTICS

B.3 NES data

FILL IN INFO ON OUR NES DATA HERE, INCUDING SUMMARY STATISTICS

25

C Party-Candidate Linkages and Electoral Volatility

Table 6: Constituency-level electoral volatility given rerunning patterns of politicians, India1977–2007


(Intercept) 37.0∗∗∗ 37.9∗∗∗ 29.0∗∗∗ 30.5∗∗∗

(1.7) (1.5) (1.7) (1.5)Incumbent runs other party 19.4∗∗∗ 19.5∗∗∗ 19.9∗∗∗ 19.7∗∗∗

(0.4) (0.4) (0.4) (0.4)Incumbent does not rerun 6.9∗∗∗ 6.8∗∗∗ 6.9∗∗∗ 6.7∗∗∗

(0.3) (0.3) (0.3) (0.3)Runnerup reruns other party 16.4∗∗∗ 15.6∗∗∗


(0.3) (0.3)Third-up reruns other party 6.7∗∗∗ 6.5∗∗∗

(0.6) (0.6)Third-up does not rerun 1.4∗∗ 1.4∗∗

(0.5) (0.5)



Note: Multilevel regression models, where constituency-year observations are nested in constituencies andyears. Control variables are electoral volatility in the constituency in the previous election, the number ofelectors in the constituency in the same election, the number of candidates running for election, as well asthe electoral turnout and margin of victory in the previous election.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

26

D Robustness checks

Table 7: Vote share for the incumbent party given rerunning patterns of politicians, India1987–2007, not rerunning parties included with a vote share of 0


(Intercept) 39.2∗∗∗ 38.7∗∗∗ 34.3∗∗∗ 35.1∗∗∗

(1.0) (1.0) (1.1) (1.1)Incumbent runs other party −26.9∗∗∗ −26.2∗∗∗ −27.0∗∗∗ −26.3∗∗∗

(0.3) (0.3) (0.3) (0.3)Incumbent does not rerun −9.5∗∗∗ −9.4∗∗∗ −9.3∗∗∗ −9.3∗∗∗

(0.3) (0.3) (0.3) (0.3)Runnerup reruns other party 1.5∗∗∗ 1.7∗∗∗


(0.3) (0.3)Third-up reruns other party 1.0 1.3∗∗

(0.5) (0.5)Third-up does not rerun 2.9∗∗∗ 1.7∗∗∗

(0.4) (0.4)



Note: Multilevel regression models, where constituency-year observations are nested in constituencies andyears. Incumbent parties that did not run for re-election are included and assigned 0% of the vote. Controlvariables are vote share for the incumbent party in the previous election, the number of electors in theconstituency in the same election, the number of candidates running for election, as well as the electoralturnout and margin of victory in the previous election.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

27

Table 8: Economic voting in India given rerunning patterns of politicians, 1987–2005, notrerunning parties included with a vote share of 0

1977–2005 1977–1990 1991–2005 1991–2005

(Intercept) 36.4∗∗∗ 36.6∗∗∗ 39.4∗∗∗ 39.4∗∗∗

(1.0) (0.9) (1.0) (0.8)Rainfall deviation −0.3 −0.5∗∗ −0.6∗∗ −0.8∗∗∗

(0.2) (0.2) (0.2) (0.2)Incumbent runs other party −20.0∗∗∗ −19.2∗∗∗

(0.8) (0.7)Incumbent does not rerun −4.4∗∗∗ −4.0∗∗∗

(0.5) (0.5)Rainfall dev. × incumb. runs other party 2.0∗∗∗ 2.2∗∗∗

(0.6) (0.5)Rainfall dev. × incumb. does not rerun 0.5 0.4

(0.4) (0.4)



Note: Multilevel regression models, where constituency-year observations are nested in constituen-cies and years. Incumbent parties that did not run for re-election are included and assigned 0% of the vote.Control variables are vote share for the incumbent party in the previous election, the number of electors inthe constituency in the same election, the number of candidates running for election, as well as the electoralturnout and margin of victory in the previous election.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

28

Table 9: Propensity to vote for the incumbent party, given rainfall and candidate runningfor the incumbent party, NES 2004, full coding of rerunning variable


(Intercept) −0.45∗∗∗ −2.30∗∗∗ −0.22∗ −1.96∗∗∗

(0.08) (0.13) (0.10) (0.16)Rainfall deviation 0.07 −0.02 −0.02 −0.12

(0.05) (0.07) (0.07) (0.09)Incumbent reruns other party −1.04∗∗ −0.79

(0.40) (0.54)Incumbent does not rerun −0.56∗∗ −0.56∗

(0.18) (0.24)Rainfall dev. × incumb. reruns other party 0.24 0.20

(0.26) (0.35)Rainfall dev. × incumb. does not rerun 0.27∗ 0.34∗

(0.12) (0.15)

AC Random Effects Y Y Y YControls N Y N YN 14675 11515 14675 11515N PCs 361 361 361 361


Note: Multilevel logit model. The data are at the individual level, but are nested in ACs. Control variablesare whether the person voted for the incumbent in the previous election, woman/man, Muslim/SC/ST/otherand Urban/Rural.† significant at p < .10; ∗p < .05; ∗∗p < .01; ∗∗∗p < .001

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party-candidate linkages and anti-incumbency voting ... · party-candidate linkages and...

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