Unstable Politics: Fiscal Space and Electoral Volatility in the Indian States
Abstract
What explains variations in electoral volatility? The authors argue that fiscal space—availability of financial resources to enact policy initiatives and provide public programs—possessed by governments can explain the level of electoral volatility. Where governments have fiscal space, citizens reward incumbent parties with their continued support. But when fiscal space is constrained, the incumbent government's ability to provide state resources is drastically reduced. Citizens are therefore less likely to reward the party at the polls and are available to opposition politicians and alternative appeals. Vote-switching ensues, and the incumbent government is voted out of the office. The authors test this argument and others in the existing literature on electoral returns from state assembly elections across 15 major Indian states from 1967 to 2004. The results support the argument that fiscal space influences electoral volatility.
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1.
1. This trade, so to speak, has been linked to the growth in the size of the public sector. This growth has been linked to the extension of the franchise, electoral incentives, and party competition, all of which pressure the state to cater to the demands of the masses and of organized interests (Aidt, Dutta, & Loukoianova, 2006; Boix, 2001; Meltzer & Richard, 1981; Tanzi & Schuknecht, 2000).
2.
2. This basis of this assumption is no different than the standard claim in other democratic contexts that elected politicians seek to provide pork to their constituencies (Weingast, Shepsle, & Johnsen, 1981). Constituency service therefore becomes essential to politicians' re-election fortunes (see also Fenno, 1978). Because any individual politician cannot generate and direct pork to his or her constituency without the collaboration of others in the legislature, a politician's ability to do so is a function of his or her ability to forge a winning coalition within the legislature. By being a member of a party that has a majority of seats in the legislature or that can enter a coalition with other parties, individual legislatures can enter logrolls and provide their constituencies the service needed to secure their votes. This is especially true in majoritarian systems, such as those in place in Indian states, where the majority party can implement its policy agenda without much opposition. Therefore, backing a candidate from the majority party is important if the voter is hoping to benefit from government policies.
3.
3. Governments can choose to create public policy programs aimed at delivering collective goods or focus on the delivery of patronage to their clients. In either case, their promise to erstwhile supporters to do so is only credible if the state possesses the necessary resources. As such, beyond the basic democratic requirement that a party must secure the support of a plurality of voters to win office, our argument does not require us to assume that governments prefer public good provision to patronage or vice versa. Both strategies—or any mixture of them—still requires fiscal space.
4.
4. One option available to a cash-strapped government is to improve its fiscal situation by reducing expenditures or increasing tax revenues. The former strategy is politically difficult, and most governments are loathe to cut spending on law and order services or to lay off government services. Similarly, governments must continue to meet their debt servicing obligations or run the risk of losing future access to credit. Furthermore, research by the International Monetary Fund (2003) has shown that few governments are able to reduce their budget deficits by increasing tax collection. A natural extension of the research presented here would be to endogenize the fiscal space available to governments. For now, we focus on establishing the analytical utility of the concept for explaining variations in electoral volatility.
5.
5. Linden (2004), in a study of incumbency rates for elections to state assemblies, finds that the incumbency rates for individual politicians have been relatively low and that they have not changed much since the 1970s.
6.
6. It is in fact possible for there to be electoral volatility at the aggregate volatility without any individuals changing their votes—due to the entry of new voters—and for there to be complete individual volatility without any aggregate volatility, if all the individual vote shifts perfectly balance each other. However, Bartolini and Mair (1990) conclude that aggregate electoral volatility is an appropriate indicator of individual vote shifts.
7.
7. We have data for 138 elections, but the first observation for each state is dropped, because we cannot calculate the change from the previous election. The states included in this analysis are Andhra Pradesh (AP), Assam (AS), Bihar (BI), Gujarat (GJ), Haryana (HA), Karnataka (KA), Kerala (KE), Madhya Pradesh (MP), Maharashtra (MA), Orissa (OR), Punjab (PU), Rajasthan (RA), Tamil Nadu (TN), Uttar Pradesh (UP), and West Bengal (WB). These states together are home to over 90% of the Indian population. A complete listing of elections for which we collected data is available from the authors. All electoral data are drawn from the Electoral Commission of India (http://www.eci.gov.in).
8.
8. Throughout the article, we use “ruling party,” “incumbent party” and “incumbent” synonymously to refer to the party that has formed the government at the state level. Because the largest party does not always form the government, we identified the ruling party by checking the party affiliation of the chief minister of the state.
9.
9. Nor is this an artifact simply of anti-Congress swings after Indira Gandhi's imposition of Emergency in the mid-1970s. The elections that took place during the Janata reign of 1977-1980 certainly had large anti-Congress swings, but even when elections held in this period are excluded from the analysis, the mean incumbency swing is 5.6 percentage points against, and the median swing is 1.2 points against.
10.
10. Linden (2004) finds that, after 1991, incumbent members of the legislative assemblies were 14% less likely to win in legislative assembly elections in India.
11.
11. Tamil Nadu also has a high variance around the mean, marking it as particularly unstable and volatile.
12.
12. Note, however, that Andhra Pradesh has a high variance around the mean, which suggests that it has had a few destabilizing elections amid a record of overall stability.
13.
13. We interviewed finance commissioners of the states of Assam and Bihar. For the analysis in this article, we used revenue expenses that were not part of the planning process (i.e., nonplan) and were also not categorized as developmental. The finances of state governments in India are divided into two broad categories—social and economic services constitute developmental expenditures—whereas expenditure on general services is treated as nondevelopmental.
14.
14. The components of fiscal space might also change over time. We would argue, for instance, that the question of how foreign direct investment (FDI) and other resource inflows affect the fiscal space of Indian states is likely to be an interesting question for future research. We do not include such resource inflows in our analysis because, at this point in time, actual revenues from FDI projects, although increasing, are still a very small portion of overall state budgets. To illustrate this point, consider Tamil Nadu, the third-largest destination for FDI in India. For the fiscal year 2004-2005, Tamil Nadu's total revenue receipts were approximately $6.3 billion (at 45 rupees per dollar), which is the same as the total cumulative amount of approved FDI projects in the state since 1991 (author's calculations, and Tamil Nadu government's Tenth 5-Year Plan, respectively). Most of these approved projects are still in the process of being realized, and their benefits are even further in the future. Moreover, in the 6-month period from April to September 2006, Tamil Nadu generated $437.3 million in FDI inflows, which is under 7% of the 2004-2005 revenue receipts (“FDI inflows double,” 2006). Again, we provide these figures not to suggest that FDI inflows are not an increasingly important aspect of the Indian political economy, but rather that, for almost all of the period covered in our article, they comprise but a small part of the story. Furthermore, FDI is not money in the discretionary coffers of the state government.
15.
15. This definition is derived from our knowledge of the fiscal situations of the Indian states and our interviews with the finance commissioners of Assam and Bihar. Although other categories of spending might be argued to be fixed and recurring, we would argue that the three categories identified here form the largest share of nondiscretionary spending. In 2004-2005, these categories accounted for 85% of the general services expenditure by the Tamil Nadu government (authors' calculations). Scholars wishing to apply the notion of fiscal space in other settings would need to tailor the set of categories deemed “fixed and recurring” according to the specifics of that situation.
16.
16. See also Khemani (2007). The literature on fiscal federalism is growing. We refer interested readers to Rodden (2002, 2003) and Rodden and Wibbels (2002) for recent surveys of and contributions to this literature.
17.
17. All subnational fiscal data are drawn from annual issues of the Reserve Bank of India (1967-2004).
18.
18. The data for the independent variables are annual in their original format. Here, we construct averages for each interelection period to include in the regression model. To take the most relevant example: To predict electoral volatility in election year t, we use the average fiscal space enjoyed by the state across the years since the last election. This is true for all the independent variables. Doing so provides some check against reverse causation, because the variables are temporally ordered and also because we are not capturing the effects of a single bad year.
19.
19. Data are available from the authors.
20.
20. A similar argument was later advanced by Sjöblum (1983), who theorized that increasing social and spatial mobility of voters resulting from economic development in industrial societies should lead to higher levels of electoral volatility. As voters became more mobile, their political preferences regarding government policy were likely to become more fluid. Moreover, the growth of the public sector and the increasing complexity of the economy made government economic policy less certain, leading voters to be available to alternative appeals.
21.
21. Tests of the mobilization hypothesis have been limited by lack of accurate data over time cross-nationally (but see Bartolini & Mair, 1990, and Przeworski, 1975, for early efforts).
22.
22. The voting age in India was lowered from 21 to 18 in 1989. Although this change did add to the electoral rolls, there is no evidence that it changed the rates of turnout or the composition of the electorate in any systematic manner. Indeed, to the extent that existing theories argue that younger voters are more fluid, a plausible expectation would be that the change in voting age should have led to increased volatility post-1989. However, our data suggest that the opposite is true.
23.
23. Using survey data, Heath (2005) finds that people living in Indian states with multiparty systems are more likely to report having switched their votes from one election to the next (p. 183).
24.
24. The effective number of parties in a given election is calculated as N = 1/Σvi2, where N is the effective number of parties, and vi is the vote share of party i. Our results are robust to using instead the effective number of parties represented in the legislature, which substitutes seat shares for vote shares in the above formula.
25.
25. Bartolini and Mair (1990) argue that European party systems have been fairly stable if one examines block volatility rather than total volatility. Similar claims about the influence of coalitional politics in influencing electoral results in India are made by Sridharan (2004) and Heath (2005). In this analysis, we focus on party-level electoral volatility, because coalitional politics has been a relatively recent phenomenon in Indian politics and moreover has been mainly observed at the national level rather than the state level.
26.
26. Remmer (1991) points to the vulnerability of minor extreme parties as one reason such more polarized systems may be more volatile over time (p. 791). An interesting empirical question for future research is therefore whether the volatility-dampening effect of increased polarization is counteracted by the volatility-inducing effect of increased party fragmentation.
27.
27. See Heath (2005, pp. 186-188 and footnote 12) for more detail on the construction of this measure.
28.
28. Our results are robust to the exclusion of this variable. Results are available on request.
29.
29. We thank Steven Wilkinson for sharing these data with us. As an alternative indicator of the social cleavage structure in each state, we used Heath's (2005) measure of the number of effective clusters in each state, which captures “the number of politically mobilized cleavage groups” (pp. 186-188, footnote 12) in each state. Our results are not affected. We prefer the Wilkinson and Yadav data, because they vary over time.
30.
30. The inflation variable, in either its level or change form, is statistically significant in only one of six specifications predicting electoral volatility and in just one of three models predicting incumbent vote change (Roberts & Wibbels, 1999, Tables 2, 3, and 4).
31.
31. Data on income refer to per capita net state domestic product at current prices, which we convert to real figures using national-level inflation data. The source for these data is the Indian Budget, available online at http://indiabudget.nic.in.
32.
32. A possible concern arises in controlling for these economic variables, because they are likely correlated with a state's fiscal space. In our sample, a state's growth rate is correlated with fiscal space as a percentage of total revenue at a level of 0.25; when we do not normalize the measure of fiscal space, the correlation increases to 0.38. Likewise, the correlation of per capita income with the two measures of fiscal space is 0.44 and 0.57, respectively. There is therefore little risk of multicollinearity being a problem, and this is borne out by the variance inflation factors.
33.
33. Remmer (1991) considers the age of the regime in her analysis and finds little evidence for the claim that new democracies were particularly vulnerable to crisis. Rather, she argues that the “relative immunity of the older democracies” (p. 785) reflects the stabilizing influence of their two-party systems. Roberts and Wibbels (1999) measure the average age of parties receiving more than 10% of the vote in the previous election, while Tavits (2005) controls for the average age of parties in Parliament. Tavits also includes a trend variable that counts the number of years since the first democratic election. Most recently, Mainwaring and Zoco (2007) conclude that the critical factor is when democracy was instituted, but not necessarily its age.
34.
34. The regressions reported in Table 1 are estimated on a sample of 108 elections. Electoral volatility captures aggregate changes between two elections; therefore, we cannot calculate the volatility score for the first election in each state, which requires us to drop the 15 observations (1 election per state). Including a lagged dependent variable results in the loss of another 15 observations by a similar logic. Our results do not change if we drop the lagged dependent variable from the model, but we report the versions with it, because these are more conservative.
35.
35. For technical articles justifying this choice of technique, see Banerjee, Galbraith, and Dolado (1990), Beck (1991, in press), and Beck and Katz (1995). Examples of recent articles using these techniques are Chhibber and Nooruddin (2004), Mainwaring and Zoco (2007), and Nooruddin and Simmons (2006).
36.
36. The results do not change if we estimate the models without random effects. We do not include state fixed effects, because our purpose is to exploit cross-state variations in fiscal space to explain variation in electoral volatility, the cleavage polarization measure is constant over time, and the other social cleavage variables change very slightly over time.
37.
37. Our data do not allow us to investigate whether this volatility-dampening effect of the 1990s is due to changes in the electorate, party system, or economic performance, and we leave this question for future research.
38.
38. These predictions are generated by moving the variable in question from its minimum to maximum in-sample value and holding all other variables at their mean or modal values.
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