At the outset, it is essential to show the aggregate level of self-reported party identification in Indonesia based on my post-election survey of voters in April 2014. While there is much divergence of opinion on the nature and measurement of party closeness (Blais et al., 2001; Greene, 2002), this study measures the degree of partisanship regarding a political party by using the three items introduced in Chapter 3. Through the first measure, respondents were asked whether they feel close to any political party. In my post-2014 legislative election survey, only 14.9 percent (herein we round up to 15 percent) nationally reported having such closeness –a low figure by international standards (featured in vertical stripes within Figure 4.1). As discussed in Chapter 2, there were around 187 million registered domestic voters in the 2014 legislative election. Hence, the 15 percent would mean an estimated 28 million voters nationwide felt close to a party.
Figure 4.1 Proportion of voters feeling close to a political party? (%)
For the purpose of this study, I categorised as ‘non-partisan’ those respondents who either gave a straight negative response or could not answer this question. Consequently, the number of non-partisans is –at 85 percent– extremely high, constituting the vast majority of the electorate, or about 159 million voters. As will be further demonstrated in Chapter 5, this pattern was confirmed in a series of nationwide surveys during the run-up to 2014 elections.
Those who answered the opening question with “yes” were requested to name the specific party they feel close to. Figure 4.2 shows that mass partisanship in Indonesia varies widely across party distribution. Of those expressing partisanship, a quarter felt some degree of attachment to PDI-P. Following PDI-P was Golkar with 21.8 percent, and then Gerindra
with 13.5percent. Thus, among those identifying partisanship, more than 60 percent of
respondents felt close to one of three largest parties. At the other extreme of the spectrum,
we find parties with almost no partisans: PBB (0 percent) and PKPI (0.6 percent). To
some extent, the distribution of party loyalty reflects the distribution of votes in the 2014 parliamentary elections. The big three of partisan identifiers, PDI-P, Golkar, and Gerindra, were placed in the top three spots and in the same order in the election results. However, it is important to note that the vote totals for all parties were several times larger than the number of voters who expressed allegiance to those parties.
Figure 4.2 Distribution of partisanship across political parties (%)
Source: My post-election survey, 22 – 26 April 2014
In the third and final measure, those who reported being close to a political party were asked to rate the strength of this affiliation on a three-point scale: “How close do you
feel toward the party?” Those who said “very close” to the party were classified as
strong partisans. Those who replied “quite or fairly close” to the relevant party were
categorised as moderate partisans, while those who reported “a little close” to a party
were classified as weak partisans. Among the 15 percent of the respondents who felt
close to any party, moderate partisans were the largest subgroup (58 percent), with weak partisans (23.1 percent) and strong partisans (17.4 percent) constituting much smaller segments. Note that those who reported having varying levels of closeness to a party are distributed across political parties.
Earlier works on party identification suggest that demographic variables can shape partisanship (Campbell et al., 1960; Converse, 1969). It is therefore essential to explore the demographic features of party identifiers in Indonesia. In this study, given the limited number of voters who identify themselves with the relevant parties, I divided the classification of party identifiers into two big categories: those who display some partisanship and those who do not. Based on the bivariate test with Pearson’s Chi-Square, we see very few strong relationships between demographic variables and party identification ––only 2 of the 10 coefficients reach the 0.05 level of statistical significance.
The first two rows of Table 4.1 shows that these two coefficients relate to gender and socio-geographic residency. Concretely, party identifiers are more likely to be men and to live in urban areas. Popular belief holds that men in Indonesia tend to be more politically active and assertive than women, given the still patriarchal social structures in many parts of the country (Robinson, 2009; Bessell, 2005). However, previous works argued that rural dwellers seem to be more partisan (e.g. Mujani, 2007: 210), contradicting the finding in this study. Part of the explanation for this difference could be the ongoing reclassification of rural citizens as urban. The 2010 census showed that the urban population grew from 26 percent in 1970s to 49.7 percent in the last 40 years, with this increase partly due to the reclassification
of once rural village areas as urban in the last census (Firman, 2012).1 Hence, the
increasingly blurred boundaries between urban and rural (especially in suburbs of larger urban centres) might have contributed to this study’s identification of urban voters as being more partisan, in contrast to previous findings that rural citizens have stronger party attachments.
1For a general discussion of the dynamics of urbanisation, see Tommy Firman, “Urbanisation and Urban
Table 4.1 Percentage of party identification by demography and chi-square analysis
Source: My post-election survey, 22 – 26 April 2014
The result for age requires elaboration. Literature on party identification in established democracies suggests a strong and positive relationship between age and partisanship through both socialisation (Jennings and Niemi, 1974; Shively, 1979) and life cycle processes (Converse, 1969; Dalton and Weldon, 2007). Both models lead to a conclusion that older voters tend to be more partisan, especially in older democracies. However, these models cannot be generally applied to younger democracies as Indonesia since their citizens have not experienced democratic polities for their entire life cycles (Samuels,
2006; Mujani and Liddle, 2012; Mujani and Prasetyo, 2012).2 Although the third row of
Table 4.1 shows that there is some support for this hypothesis, suggesting older voters have a slightly higher likelihood of being partisan than younger ones, the Chi-Square analysis clearly reveals that age is unrelated with partisanship.
2 In his influential article “Of Time and Partisan Stability” (1969), Philip Converse argued that party
identification results largely from a combination of parental socialisation and life-cycle processes. In short, following these models, older democracies exhibit higher levels of partisanship because their voters inherit what Converse (1969) coined as a “partisan push” from their parents. In contrast, voters in relatively younger democracies are assumed to have a lower level of party attachment because they lack this partisan push.
The result for education also merits further exploration. The coefficient of education
even fails to reach statistical significance in the mildest sense (p < 0.1). Even though
some authors claimed that the best informed are the most partisan (Campbell et al., 1960; Converse, 1964; Miller and Shanks 1996), I found little evidence for this hypothesis in Indonesia. The connection between education and party identification is often established as part of the rational information-seeking approach which highlights that better-informed individuals tend to have a partisan identity. The rationale is that since education is important for obtaining political information and knowledge, it is therefore central to the acquisition of partisanship. However, this is not the case in Indonesia. The insignificance of education is consistent with Samuels’ (2006) findings in Brazil. Coincidentally, the two countries face similar problems in which citizens have relatively limited degrees of education and both have adopted presidentialism and an extreme multiparty system.
In terms of monthly income correlates, the Chi-Square test found that the relationship between income (defined in this study by two categories as shown in Table 4.1) and party identification is not statistically significant. It is worth noting that in many cases, distinguishing the effect of income from closely related variables such as education and occupation is extremely difficult. Given the relationship between partisanship and income and education is weak, it is therefore unsurprising that profession (divided into two categories: blue or white collar employment) is not associated with partisanship either. Ethnic, religious affiliation and regional divisions also appear entirely unrelated to partisanship. Arguably, these findings also have implications for the debate on the link between social cleavages and the existing party system. In the case of India, for example, Chhibber (2001) argued that the type of party competition shapes the politicisation of social differences. Since the decline of Indian catch-all parties in the 1990s, social divisions have become more salient and electoral competition has been highly influenced by religious and caste-based issues. In Indonesia, by contrast, most parties in Indonesia have increasingly assumed a catch-all party posture (Mietzner, 2013; Mietzner and Muhtadi, forthcoming), and this tendency discourages them to politicise any of those social cleavages.
The low scores of mass partisanship as discussed above leave a number of unanswered questions: if there are so few voters with clear and declared loyalty towards a particular party, why were candidates very keen to target such voters? In the same vein, considering the large proportion of non-partisans with a greater potential to change their voting decisions if given benefits (Lindbeck and Weibull, 1987; Dixit
and Londregan, 1996; Stokes, 2005), as thoroughly discussed in Chapter 1, why did political machines profess that these voters were secondary to their vote buying strategies? And finally, given that in total numbers more non-partisans than partisans experienced vote buying attempts, does that mean that candidates and brokers misdirected their vote buying operations? But first, I will discuss whether or not voters’ partisan closeness is entirely a result of their receiving electoral rewards.