INDIVIDUAL PREFERENCES VERSUS SOCIAL DRIVERS OF POLITICAL PARTICIPATION IN MALAWI Ellen Lust, P
rogram on Governance and Local Development, University of Gothenburg Pierre F. Landry, New York University ­Shanghai for presenta on at ISA‐Hong Kong, June 2017 I. I ntroduction Is vo ng determined by individual a ributes and preferences, or is it driven by social interac ons? To what extent, and when, should it be considered an individual or communal act? The extent to which individuals base their vo ng choice on individual interests or are influenced by those around them is a ques on of perennial debate in literature spanning from American vo ng behavior to clientelism in Africa. This paper interrogates this ques on in a study of voters’ choices in Malawi’s 2016 presiden al, parliamentary and local elec ons. To do so, we analyze data collected in Malawi in 2016, including a unique household survey of over 8000 respondents, and over 350 interviews with local‐level elites. These data have two advantages: First, they provide highly clustered observa ons, making it possible for us to dis nguish between the local and individual level effects. Second, they include ques ons that tap into local level norms and social ins tu ons, as well as the individual‐level characteris cs. Together, this makes it possible to adjudicate between explana ons of voter choice based on individual‐level variables and those based on village‐level context. The study (to date) reveals important findings. First, there is considerable village‐level varia on in voter choice that is not simply explained by differences in individual‐level characteris cs. Second, where the preferences of individuals and those in the community surrounding them diverge, individuals are not equally likely to choose to vote their preference or to vote with those in the community. Third (we an cipate) that it is both individual‐ and village‐level characteris cs that determine whether or not individuals vote like those around them. This proto‐paper proceeds as follows. Sec on two sketches the main scholarly debates at the basis of this study and derives relevant hypotheses. Second three describes the poli cal context in Malawi, paying par cular a en on to the nature of elec ons, and the poli cal role of village heads. Sec on four examines the extent to which varia on in vo ng behavior is determined by individual or communal factors. II. I s Voting an Individual or Communal Act? Vo ng is always ul mately an individual act – with voters cas ng ballots for candidates in the vo ng polls – but to what extent is it driven by individuals’ a ributes, or determined by those around them? Scholars examining vo ng turnout, choice and clientelism have grappled with these ques ons, arriving at very different answers. The literature on vo ng turnout has noted that vo ng is arguably costly, and the likelihood that any individual’s vote determines the outcome of the elec ons is remote; thus, why does one vote? For some, the answer lies in individual, psychological benefits or mispercep ons about their own influence (XXX). However, others point to the importance of group norms that see vo ng as a civic duty. For instance, a large‐scale experiment conducted in Michigan found that turnout increased when individuals were no fied that news of their vo ng (or absten on) would be publicized to their neighbors following the elec on.1 In this case, social norms ma er. The ques ons then are when the community believes that vo ng is important (e.g., vo ng is the social norm) and the act of vo ng is visible enough for individuals to fear sanc oning if they abstain. Scholars examining vo ng choice have also debated the extent to which votes are driven by individual factors or community influences. On the one hand, there was a en on to individual a ributes underpinning the three main schools of American vo ng behavior (which, subsequently, underlies scholarship on vo ng behavior elsewhere as well.) Lazarsfeld (Lazarsfeld, Berelson, & Gaudet, 1944; Lazarsfeld 1968), founding the Columbia school of vo ng behavior, argued that individual characteris cs –and especially personality and exposure to media –impacted voters’ choices; Campbell, Converse, Miller and Stokes (1960), founding what came to be known as the Michigan school, examined the impact of psycho‐social factors – especially party iden fica on – drove vo ng; and the scholars at Rochester (including most notably Downs (1960)) suggested that individual‐incen ves – including policy choices – drove decision‐making. At the same me, however, even classic work on vo ng behavior has suggested that community factors make a difference. Lazarsfeld and his colleagues (1968) found that individuals were par cularly swayed by those with whom they were in contact – not simply by the media messages that they received. This led them to conclude that A
lan S. Gerber, Donald P. Green, and Christopher W. Larimer “Social Pressure and Voter Turnout: Evidence from a Large‐ scale Field Experiment,” American Political Science Review, 102 (February 2008): 22‐48. 1
1 “people vote, not only with their social group, but also for it” (Lazarsfeld et al., 1968, p. 148). The Michigan school found that the best predictor of individual party iden fica on was their parental iden fica on, again sugges ng the importance of social influence. And even the ra onal choice models of the Rochester School implied that community‐level factors can impact outcomes when communi es shape the incen ves around vo ng and voter choice. To some extent pu軀�ng these perspec ves together, Verba, Schlozman and Brady (1995) classify returns on par cipa on as selec ve material benefits, selec ve social gra fica ons, selec ve civic gra fica ons and collec ve policy outcomes. More recent literature on vo ng behavior also lends strong support for the idea that vo ng choices are driven by both individual and community level factors. Examining the UK, for instance, Johnston and colleagues (2007: 642) conclude that, “similar people—according to their class and other individual characteris cs—voted differently in different regions and changed their minds to different extents in different regions.”2 It is thus not surprising that the more recent literature on clientelism and vo ng is also ambivalent regarding the role of individual and group factors. On the one side are arguments that focus on how individual factors – such as poverty, educa on or gender – make people more likely to be influenced by clientelis c offers ( Stokes 2007, Kitschelt 2002; for review, see Mares and Young 2016). In part, this is because this view of clientelism emphasizes the possibility of coercion, and vulnerable popula ons are more likely suscep ble to such pressures. On the other are those that focus on how the strength of group influence may vary. For instance, Koter (2015) argues that ethnic vo ng is used to mobilize voters in the absence of strong local brokers who, otherwise, can mobilize cross‐cu軀�ng coali ons of support. In this view, clientelism is a strategy used across voters and elec ons, but the ethnic nature of it varies depending on the power structure of communi es.3 Baldwin (2013) suggests somewhat similarly that the nature of linkages between local patrons and Members of Parliament affects the extent to which the patrons’ preferences drive voters’ choices. Where rela onships are close, villagers have a reason to believe that following their local patron’s lead in vo ng will lead to be er delivery of services. Overall, the literature suggests that we need to consider two main ques ons. First, to R
on Johnston, Kelvyn Jones, Carol Propper, Simon Burgess, “Region, Local Context, and Vo ng at the 1997 General Elec on in England,” A
merican Journal of Political Science , Vol. 51, No. 3, July 2007: 640–654. 2
F
or research that links ethnic vo
Kramon 2016; Lust‐Okar 2006. 3
ng to clientelism, see Posner 2005; Carlson 2015; 2 what extent are voters driven by individual incen ves (wholly divorced from the desires of their community) and to what extent does the community influence their choices? Second, if community‐level factors ma er, how and when do they influence individuals? Do differences in individual characteris cs affect the extent to which people – located in the same community – are influenced? And do differences in communi es impact how individuals ‐‐who are otherwise similar ‐‐ will behave? To sketch out some hypotheses and expecta ons (most to be explored in the future): Hypothesis Set 1: Individual vs. Community Level Drivers 1. Community level varia on will be a significant determinant of vote choice. (That is, in voter choice models, community/village level variables should be significant.) Hypotheses Set 2. Individual­Level Variation in Community Influence We can expect that local context ma ers, and test three ways in which this is possible. First, we can consider the impact of individual varia on in terms of the individual’s vulnerability to pressure (if a coercive model of village‐level varia on applies, a la Brusco, Nazareno, and Stokes 2004; Medina and Stokes 2007), more willing or obliged (if a loyalty model of community influence applies, ala Sco 1972; Lemarchand and Legg 1972; Auyero 2000), or have greater belief that the village should act cohesively (if driven by a poli cal influence model, akin to that of Baldwin 2015). More specifically, 1. Individuals who are more vulnerable – poorer, landless, less educated, more dependent on others for help, are more fearful of confron ng superiors, are dependent on the chief or others for their livelihood (ex. Agricultural workers vs. school teachers) – will be more likely to be swayed by village preferences. (Coercive model) 2. Individuals who are more connected to other members in the village – have more connec ons to influen al people in the village, have greater contact with others in the village, have lived in the village longer, have greater trust in their village head – will be more likely to be swayed by village preferences. (Loyalty model) 3. Individuals who have greater beliefs in the importance of village cohesion or communalism – believe it is important that the village vote together, value the village reputa on, embrace norms of reciprocity – are more likely to be swayed by the village. (Poli cal opera ve model) Hypotheses Set 3: Community­Level Variation in Community Influence We can also consider how there is varia on in the village that impacts the extent to 3 which individuals vote with the village. 1. Villages in which power is more centralized—have fewer members on the village advisory council, have less diversity in the members of health, educa on and other commi ees, have had village heads in power for more years, have village heads who came to power as the eldest son/daughter – are more likely to sway individuals’ vote choices.4 (Coercion model) 2. Villages that have strong social networks –in which more people know the village head, know and interact with each other ‐‐ are more likely to sway individuals’ vo ng choices. (Loyalty model) 3. Villages in which more people believe that vo ng together is important (and/or they believe that others in the village think this is important) are more likely to vote together. (Poli cal opera ve model) 4. Villages in which the belief is that people should vote together and networks are denser (that is, in which these interact) are more likely to sway individuals’ vote choices.5 (Poli cal opera ve model)6 es have meaningful hierarchical es and not all chiefs or religious leaders are suited to become electoral intermediaries.” p. 195 4
5
A
s Dominika Koter (2013) noted, “Yet not all communi
N
ote, for instance, that David Campbell argues that “Social norms, including a sense of civic responsibility, are “enforced” (some me benignly, some mes less so) within social networks.” David E. Campbell, “Social Networks and Poli cal Par cipa on,” A
nnual Review of Political Science, Vol. 16: 33‐48. 6
T
here is more to write regarding networks. See for instance, Argument that there is a ‘diffusion” effect – people ‘learn’ and ‘observe’ (See also Wendy K Tam Cho and Thomas Rudolph, “Emana ng poli cal par cipa on: Untangling the spa al structure behind par cipa on,” B.J.Pol.S. 3
8, 273‐289 4 III. V
oting in Malawi Malawi’s May 2014 elec ons provide an excellent opportunity to study the influence of individual‐ and community‐level factors on vo ng. The elec ons were the fi h general elec ons to be held since Malawi became a mul ‐party system in 1993, but the first me that the voters simultaneously cast ballots for local, parliamentary and presiden al elec ons. Moreover, they did so under a single, majoritarian electoral system. Thus, we can assume that any difference in the impact of village‐ or individual‐level influences is due to the nature of elec ons rather than to the ming of the polls.7 Malawi’s elec ons since 1993 have generally been considered free and fair, although it is important to recognize that ci zens vo ng for parliamentary and local representa ves have li le reason to believe that they will have a strong influence on policy. The Parliamentary oversight is weak (Patel and Tostensen, 2007; Dionne and Dulani 2013), and the parliament neither controls its budget nor decides when it convenes. This discourages them from pursuing policy agendas and instead provides incen ves for them to emphasize benefits for their districts or par cularis c benefits for their supporters (Rakner and Svåsand 2013; Ejdemyr, Kramon, and Robinson 2015). As a result, there is li le reason to an cipate that policy posi ons and preferences drive voters’ choices. In contrast, ethnicity and regionalism does appear to be a salient driver of poli cal choice (Hussein 2009, p. 348). Malawi is home to eleven major ethnic groups, including three main ethnic‐regional iden es: the Tumbuka in the north, the Chewa in the center and the Yao in the south (Kaspin 1995; Posner 2004). Malawian poli cal par es are regionally based as well. Since 1994 voters in the North have generally supported the Alliance for Democracy (Aford) or its successors; voters in the Central region vote for Malawi Congress party (MCP); and voters in the Southern region vote United Democra c Front (UDF) or other par es with a “Southern profile” (Hussein 2009, Rakner et al. 2007, Dionne and Horowitz 2011, Ferree and Horowitz).8 We do not, at this point, have any expecta on over differen al pulls regarding local, parliamentary and presiden al elec ons, although we do expect that individuals vote on different candidate factors for elec ons at different levels. We find some evidence of this in a conjoint experiment embedded in the 2016 Local Governance Performance Index. (See Harris, Kao and Lust, 2017) 8
K
aren Ferree and Jeremy Horowitz , “Iden ty Vo ng and the Regional Census in 7
5 Public opinion also demonstrates a level of duty toward co‐ethnics. The LGPI found that 75% of Malawians reported that they feel it is important or very important to elect someone from their ethnic group. Malawians feel very or somewhat obligated to help out co‐ethnics at a rate of 76%, compared to 69% for a Malawian with whom they have no connec ons. Moreover, 91% of Malawians think it is very important to uphold the reputa on of their ethnic group and 59% a gree or agree strongly that MPs respond more quickly to their co‐ethnics. Localism is important in Malawi as well. Seventy percent of Malawians feel somewhat or very obligated to help co‐locals. Addi onally, 90% of Malawians think it is very important to uphold the reputa on of their village. Regarding elec ons, 62% a gree or agree strongly that MPs respond more quickly to their village members, and 79% of Malawians reported that they feel it is important or very important to elect someone from their village. Perhaps most importantly, there is reason to believe that village heads a empt to influence elec ons. As in Senegal, Benin (Koter 2013), South Africa, Zambia (Baldwin 2015) and elsewhere, village heads and other local elites a empt to influence elec ons. Technically poli cal engagement of village heads in Malawi is illegal, and direct ques oning of village heads regarding their engagement in poli cs or a empts to influence their villages were –perhaps not surprisingly –met with denial. However, there was also widespread condemna on of the use of poli cal favors from the ruling party to influence village heads. A report by Patel and Wahmen (2015: 25)9 is worth quo ng at length: More controversial was the use of chiefs in political activities. Endorsement by a traditional leader plays an important part in the selection of elected or unelected officials at the local level, despite the general argument that chiefs should be politically neutral. Election observation reports by both local and international observers indicated widespread misuse of chiefs by the ruling party to intimidate opposition party supporters and candidates. Some opposition politicians, albeit less frequently, used the same strategy to frustrate the efforts of the party in power. President Banda warned her Malawi,” Afro‐Barometer Working Paper No. 72, h p://afrobarometer.org/sites/default/files/publica ons/Working%20paper/Afropaper
No72.pdf P
atel, Nandini and Wahman, Michael (2015) The presiden al, parliamentary and local elec ons in Malawi, May 2014. A
frica Spectrum , 50 (1). pp. 79‐92. ISSN 0002‐0397 h p://eprints.lse.ac.uk/62306/1/The_presiden al.pdf 9
6 fellow politicians against ‘using chiefs to score political mileage’. Paradoxically, President Banda herself appointed and promoted more chiefs than any other Malawian president before her, and used them in her distribution of patronage and political campaigns. In the run­up to the 2014 elections, the Joyce Banda administration elevated the highest number of traditional leaders in the history of the country. In two years it elevated 40 000 village headmen and group village headmen, which were almost equally spread across the country. Furthermore, the administration elevated other levels of traditional leaders (Kayuni: 2014). Some critics, particularly in civil society and the media, argued that the appointment and promotion of large numbers of chiefs amounted to political manipulation and a ‘political gimmick’ that advantaged President Banda during the election period. The ques on, however, is not whether village heads a empt to influence the voters – or whether ethnic iden ty or other factors play a role – but rather the rela ve importance of these factors, and under what condi ons they ma er. The analysis of the Malawi 2016 LGPI gives us an opportunity to analyze the rela ve power of these influences. Doing so provides an opportunity to examine vo ng models based on individual and communal factors, and whether these are best understood in models of coercion, loyalty, or poli cal considera ons. IV. Individual­ and Communal Determinants of Voting in Malawi Our empirical strategy consists in first iden fying respondents whose reported vote did not seemingly conform to a standard model of individual choice condi oned by standard measures of demographic and socio‐economic indicators. We first es mate such a mul nomial logit model of vote choice, and then generate forecasts of votes that would likely have been cast as if the respondent had not been influenced by any village‐level or other ecological factors. We can thus compare how each voter’s “naive” forecast compares with the Party or candidate that she reported choosing on the ‘tripar te ballot’ for presiden al, parliamentary and local elec ons. We use individual characteris cs of the respondents to es mate the likelihood that they will choose a given party for each of the votes cast on Elec on Day. The probability of a vote between k op ons condi onal upon a matrix of X covariates is es mated through a mul nomial logit model: 7 P (V i = k ) =
1
K −1
1+ ∑ eβ k X i
k=1
In order to facilitate the es ma on process, the choice set was reduced to each of the four main candidates or par es (DPP, MCP, People’s Party and UDF). Minor par es were all recoded as a single ‘other’ category, while refusals to answer were retained in the choice set in order to avoid genera ng biased es mates due to non‐response. TABLE 1­­ Tabulation of reported vote choices, by ballot category 1 Democra c Progressive Party (DPP) 2 Malawian Congress Party (MCP) 3 People’s Party (PP) 4 United Democra c Front (UDF) 77 Other 98 Refused to answer n=6340. Unweighted es mates. Source: LGPI‐Malawi President 53.56 13.5 20.87 8.63 0.44 3 Parliament 38.63 11.83 16.37 10.19 16.51 6.47 Local 39.01 10.95 17.74 9.18 9.92 13.2 Table 1 summarizes how LGPI respondents reported their votes. We note that the distribu on of the presiden al ballots is quite different from the other two ballots, which reflects the unusual dynamics of the presiden al race in which the incumbent Joyce Banda (People’s Party) was challenged and ul mately defeated by the DPP’s candidate, Peter Muharika. Parliamentary and local races a racted a wider spectrum of candidates (coded OTHER), resul ng in a much lower DDP score of about 39% than the party’s share of presiden al ballots (53%). For the local ballot, respondents who expressed dissa sfac on with the subsidy program (either because deserving families were unable to obtain them or because undeserving ones did) . Both women and older voters were less likely to recall/reveal their vote, and those who did were less likely than men or younger voters to turn to independent candidates and small par es. Be er educated voters tended to gravitate away from the DPP and were unlikely to refuse to answer this item on the survey. We fail to detect any independent impact of income, though collinearity between income and educa on may 8 be the reason why educa on coefficients alone are significant at the .05 level in all but one instance (UDF vote). The overall MNL es mates suggest that individual traits of Malawian are important drivers of voter choice. We can thus es mate‐‐using exclusively these individual a ributes‐‐who they would be expected to vote for in the absence of other variables (such as village‐level factors), and do so for each ballot type. Contras ng predicted votes with actual ones allows us to iden fy the subset of voters who are likely to have been sufficiently influenced by other social forces that ul mately made them select candidates and par es that are not predicted by a simple model of individual choice. One can think of such voters as persuadable, and we therefore focus the remained of our analysis on this group because it is pivotal to the success or failure candidates. We are not claiming that campaigns ignore the “base” of reliable voters at the expense of “swing” voters. Par es and candidates obviously try to ensure that core supporters will turnout at the polls. Our claim is that if one seeks to observe and measure how social forces and ins tu ons sway voters, focusing on the sub‐group of persuadable voters is a produc ve way to be er understand how these forces operate. Persuadable voters are by no means marginal. By cross‐tabula ng expected votes derived from our individual MNL models with the reported votes of respondents, it is obvious that the share of persuadable voters is decisive for both parliamentary and local ballots. The MNL model fails to correctly predict 50.5% of the la er, though only 40.3% of presiden al voters can be viewed as persuadable. Thus, both the rank‐order of votes cast for each party and the ul mate ballot winner were massively influenced by the sub‐popula on of voters whose eventual choice did not conform to a standard model of individual vote‐choice. 9 Table 2: MNL estimates of vote choice, by ballot type PRESIDENTIAL BALLOT VARIABLES PRES.: MCP PRES.: PP PRES.: UDF PRES.: Other PRES.: R.A. Age ‐0.00147 0.00294 ‐0.00808 0.0108 0.0230*** (0.00438) (0.00354) (0.00492) (0.0123) (0.00425) Female ‐0.358*** 0.117 ‐0.237 ‐0.380 0.836*** (0.126) (0.0769) (0.172) (0.321) (0.238) Educa on 0.0770 0.0611 0.0643 ‐0.0123 ‐0.294** (0.131) (0.125) (0.120) (0.268) (0.119) Lomwe ‐3.901*** ‐1.275*** ‐0.286 ‐1.155 ‐2.234*** (0.341) (0.271) (0.326) (1.227) (0.391) Yao ‐2.899*** 0.152 3.070*** ‐0.987 ‐0.0582 (0.349) (0.237) (0.407) (1.453) (0.295) Ngoni ‐1.666*** ‐0.291 0.110 0.103 ‐1.455*** (0.251) (0.242) (0.334) (0.951) (0.407) Tumbuka ‐1.610*** 1.286*** ‐1.318*** 0.147 ‐0.693** (0.224) (0.236) (0.505) (1.124) (0.288) Mang'anja ‐5.121*** ‐0.978*** ‐0.137 ‐1.495 ‐3.222*** (0.532) (0.336) (0.408) (1.351) (0.578) Sena ‐4.476*** ‐0.950*** ‐0.363 0.406 ‐2.721*** (0.422) (0.238) (0.372) (1.089) (0.480) Tonga ‐1.595*** 2.127*** 0.209 1.030 ‐0.953 (0.448) (0.380) (0.549) (1.183) (0.585) Nkhonde ‐1.421*** 1.038 ‐16.19*** 1.465 ‐0.558 10 (0.447) (0.655) (0.521) (1.391) (1.021) Lambya ‐2.409*** 1.058*** ‐15.40*** ‐16.20*** ‐1.671** (0.534) (0.245) (0.616) (1.086) (0.712) Sukwa ‐1.047 1.239 ‐15.27*** ‐16.26*** ‐16.33*** (1.252) (0.961) (0.846) (1.112) (0.686) Senga ‐1.623*** 20.15*** 1.159*** ‐0.390 ‐2.282*** (0.242) (1.018) (0.335) (1.104) (0.300) Nyanja ‐4.920*** 0.212 0.765** ‐16.41*** ‐17.40*** (0.869) (0.179) (0.380) (1.073) (0.467) Malawian Only [does not iden fy with any group] ‐1.733 ‐0.183 ‐15.51*** ‐16.15*** ‐17.22*** (1.131) (1.142) (0.615) (1.147) (0.759) Other ‐3.342*** 0.345 ‐2.142* ‐0.345 ‐2.427*** (0.358) (0.252) (1.107) (1.373) (0.627) DK/RA ‐1.536* ‐17.62*** 1.505 ‐17.63*** 1.123 (0.817) (0.630) (1.077) (1.208) (1.046) Sufficient Income 0.0872 ‐0.0347 0.0965 1.141*** ‐0.249 (0.109) (0.119) (0.150) (0.331) (0.235) Nega ve assessment of subsidy program ‐0.0418 ‐0.0288 ‐0.0320 ‐0.589 ‐0.673*** (0.147) (0.0895) (0.107) (0.428) (0.164) Constant 0.535 ‐1.547*** ‐2.378*** ‐4.666*** ‐2.312*** (0.458) (0.416) (0.529) (1.733) (0.588) Observa ons 6,267 6,267 6,267 6,267 6,267 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 11 PARLIAMENTARY BALLOT VARIABLES PARL.: MCP PARL.: PP PARL.: UDF PARL.: Other PARL.: R.A. Age 0.00746** ‐0.00421 ‐0.00177 ‐0.00406 0.0165*** (0.00352) (0.00278) (0.00302) (0.00276) (0.00341) Female ‐0.121 ‐0.0868 ‐0.206* ‐0.0959 0.856*** (0.106) (0.0975) (0.107) (0.0774) (0.148) Educa on 0.173*** 0.155*** 0.145** 0.164*** ‐0.139 (0.0578) (0.0508) (0.0611) (0.0527) (0.0964) Lomwe ‐3.949*** ‐1.115*** ‐0.509* ‐0.543*** ‐1.566*** (0.387) (0.255) (0.304) (0.190) (0.265) Yao ‐2.055*** 0.0834 3.002*** 0.163 0.118 (0.368) (0.263) (0.312) (0.222) (0.231) Ngoni ‐1.971*** ‐0.808*** ‐0.508 ‐0.421 ‐1.160*** (0.310) (0.259) (0.381) (0.343) (0.312) Tumbuka ‐1.905*** 0.976*** ‐1.934*** 1.336*** ‐0.909*** (0.291) (0.242) (0.616) (0.281) (0.285) Mang'anja ‐4.703*** ‐1.084*** ‐0.628* ‐0.927** ‐2.095*** (0.565) (0.278) (0.367) (0.413) (0.377) Sena ‐5.335*** ‐0.543 ‐0.764*** ‐0.327 ‐1.944*** (0.588) (0.332) (0.291) (0.346) (0.286) Tonga ‐2.207*** 1.488*** ‐0.590 1.418*** ‐0.219 (0.444) (0.366) (0.546) (0.247) (0.369) Nkhonde ‐3.462*** 0.425 ‐14.64*** 0.672* ‐1.534 (1.087) (0.383) (0.475) (0.369) (1.086) 12 Lambya ‐3.123*** 1.066*** ‐15.18*** ‐1.462** ‐1.473** (0.415) (0.391) (0.566) (0.728) (0.574) Sukwa ‐0.580 0.747 ‐14.85*** 0.108 ‐15.68*** (0.760) (0.840) (0.806) (0.732) (0.656) Senga ‐2.005*** 20.13*** 0.702** 0.274 ‐1.791*** (0.248) (1.092) (0.318) (0.242) (0.284) Nyanja ‐5.029*** ‐0.203 0.271 ‐0.327 ‐2.212*** (0.748) (0.300) (0.293) (0.276) (0.394) Malawian Only [does not iden fy with any group] ‐1.874 ‐0.204 0.710 ‐15.14*** ‐16.29*** (1.143) (1.141) (1.239) (0.550) (0.722) Other ‐3.942*** 0.584 ‐0.896* ‐1.228** ‐1.277*** (0.495) (0.494) (0.468) (0.533) (0.415) DK/RA ‐1.803** ‐15.53*** 0.681 ‐15.42*** ‐0.0833 (0.805) (0.703) (1.192) (0.630) (1.111) Sufficient Income 0.0726 0.00565 ‐0.0933 0.173 ‐0.0736 (0.130) (0.123) (0.145) (0.138) (0.170) Nega ve assessment of subsidy program 0.0249 ‐0.0856 0.0952 ‐0.110 ‐0.258 (0.192) (0.0970) (0.158) (0.169) (0.188) Constant 0.127 ‐0.975*** ‐2.013*** ‐1.103*** ‐1.618*** (0.344) (0.357) (0.329) (0.288) (0.463) Observa ons 6,267 6,267 6,267 6,267 6,267 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 13 LOCAL BALLOT VARIABLES LOCAL: MCP LOCAL: PP LOCAL: UDF LOCAL: Other LOCAL: R.A. Age 0.00552 ‐0.00391 ‐0.00121 ‐0.00531*
* 0.00994**
* (0.00353) (0.00274) (0.00295) (0.00263) (0.00314) Female ‐0.0959 ‐0.0264 ‐0.0176 ‐0.165* 0.488*** (0.136) (0.0839) (0.130) (0.100) (0.123) Educa on 0.0906** 0.103** 0.0888* 0.0944** ‐0.193*** (0.0441) (0.0443) (0.0484) (0.0449) (0.0690) Lomwe ‐3.984*** ‐1.584*** ‐0.483 ‐0.633** ‐1.561*** (0.339) (0.271) (0.305) (0.262) (0.205) Yao ‐2.583*** ‐0.183 2.643*** 0.254 0.0316 (0.351) (0.243) (0.286) (0.236) (0.216) Ngoni ‐2.031*** ‐0.612** ‐0.509 ‐0.616 ‐1.197*** (0.343) (0.290) (0.378) (0.422) (0.339) Tumbuka ‐1.999*** 1.188*** ‐1.227*** 1.246*** ‐0.333 (0.279) (0.222) (0.432) (0.280) (0.253) Mang'anja ‐5.113*** ‐1.166*** ‐0.933*** ‐1.539*** ‐2.058*** (0.605) (0.321) (0.355) (0.434) (0.328) Sena ‐4.758*** ‐0.505 ‐1.241*** ‐1.108*** ‐2.000*** (0.313) (0.350) (0.382) (0.315) (0.295) Tonga ‐2.454*** 1.547*** ‐1.377** 1.631*** ‐0.611** (0.454) (0.467) (0.680) (0.363) (0.272) Nkhonde ‐2.308*** 0.751 ‐0.376 1.330** 0.210 (0.872) (0.566) (1.050) (0.531) (0.613) 14 Lambya ‐2.606*** 1.983*** ‐15.15*** ‐0.733 ‐0.455 (0.496) (0.561) (0.558) (0.568) (0.483) Sukwa ‐0.914 1.213** ‐14.59*** ‐14.89*** ‐0.227 (1.104) (0.539) (0.811) (0.832) (0.704) Senga ‐2.169*** 0.182 25.26*** 0.282 ‐1.519*** (0.230) (0.239) (1.070) (0.267) (0.256) Nyanja ‐5.176*** ‐0.584 ‐0.189 ‐0.777 ‐1.529*** (0.888) (0.423) (0.265) (0.657) (0.372) Malawian Only [does not iden fy with any group] ‐0.764 1.629 ‐13.94*** 1.387 0.157 (1.397) (1.244) (1.008) (1.450) (1.338) Other ‐5.288*** 0.677 ‐1.593*** ‐0.967 ‐1.268*** (1.057) (0.557) (0.606) (0.646) (0.333) DK/RA ‐1.818** ‐15.26*** 0.626 ‐15.38*** ‐0.771 (0.780) (0.663) (1.167) (0.648) (1.148) Sufficient Income 0.0528 0.109 0.0141 ‐0.120 0.0723 (0.179) (0.121) (0.138) (0.127) (0.115) Nega ve assessment of subsidy program ‐0.0720 ‐0.133 0.170 0.0669 ‐0.304** (0.175) (0.0936) (0.145) (0.136) (0.138) Constant 0.460 ‐0.911*** ‐2.036*** ‐1.352*** ‐0.299 (0.314) (0.312) (0.328) (0.302) (0.366) Observa ons 6,267 6,267 6,267 6,267 6,267 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 15 Villages The LGPI‐Malawi dataset is a stra fied mul ‐stage probability sample in which primary sampling units (PSUs) are the enumera on areas of the latest popula on census. The sta s cal agency of Malawi does not maintain boundary‐maps of villages within Tradi onal Authori es. Villages are defined and redefined on the basis of the authority of their Chief and may easily split or re‐congregate as circumstances and opportuni es allow. For instance, armed with the knowledge that government subsidies for fer lizers were to be handed out as a fixed amount per village, many villages decided that it was preferable to split formally into mul ple en es in order to maximize the level of government assistance per capita. It is not clear whether villages returned to their original state once the distribu on of fer lizers was complete. Such fluidity at the village level presented implementa on challenges: the popula on size of sampled villages was not known ex­ante , forcing the research team to devise a sampling design targe ng 50 respondents around fixed sampling points within a given EA, and to then select households through a quasi‐random walk procedure. In fact, it was necessary to confirm the name of the village to which sampled households actually belong to with respondents and community leaders. In some cases, households located in one EA belonged to the periphery of a village whose center and leadership is located in a neighboring EA. This process revealed that 8107 LGPI respondents map to 270 villages. Thus, villages do not cons tute a formal sampling unit at the design stage, a feature of the research that allows us both to es mate models for complex stra fied mul stage sampling designs and at the same me incorporate village‐level variables in the same models, something that would not be possible had we been able to make villages secondary or lower‐level sampling units. Although village‐level elec ons returns are not available, we can nonetheless rely on reported votes in the LGPI to ascertain the leading party in each village. The key assump on is that the sample of households within EAs is random and that non‐response to these items is either random or small enough that it does not bias our forecast of the leading party in the village. 16 Figure 1. Distribution of leading parties in villages, by sampled Traditional Authority These calcula ons reveal a great deal of varia on of local poli cal condi ons. The DDP lead the presiden al ballot in every village in 10 sampled TAs of our project, while UDF was hegemonic only in Jalassi, whereas the MCP and the PP competed with the DPP in dis nct TAs. The strength of the DPP is clearly revealed by its absence in only two TAs (Jalassi and Tambala). 17 Figure 2. Dominant parties in the respondent’s locality, coded 0 if the respondent’s reported vote is consistent with individual model of voting behavior, and coded 1 if forecast and reported votes differ. Party code: 1=DPP; 2=MCP; 3=PP, 4=UDF. What are the factors that pull voters towards community­level preferences?
At the me of wri ng, we are s ll exploi ng interview data with village and local leaders that will allow us develop a more detailed village‐level dataset that will help us clarify how the variability of village‐level socio‐poli cal ins tu ons influence the decision‐making process of voters. In Table 3, we present a first cut of our efforts, using two flavors of mul variate models of village‐level effects. We present logit regressions for complex sampling data (including post‐stra fica on weight), es mated for the sub‐popula on of respondents who did not vote for the Party that our individual choice model predicted. Models 1a, 2a, and 3a use the simplest set of controls that dis nguish between rural and non‐rural communi es, the la tude of the village (since Malawi has been historically divided between a rela vely richer north dominated by patrilineal land arrangements, and a poorer southern region where matrilineal arrangements are more prevalent. We control for matrilineal tenure, because geography alone , while important, does determinis cally explain land tenure across the 18 271 villages that are covered in this study. Models 1b, 2b, and 3b add a number of village level controls that focus on ethnic dynamics in the villages and well as the presence of poten ally important social and poli cal players in the community: wealthy people, Civil‐society or religious organiza ons, and well as poli cal par es. Given the defini on of our dependent variable, posi ve coefficients denote a greater propensity to vote along with the village, whereas nega ve coefficients suggest that the respondents voted as predicted by their demographic and SES traits. We detect evidence that “vo ng with the village” is more likely to occur in matrilineal areas, though not in the case of the presiden al ballot. This discrepancy may be explained by the unusual dynamics of the latest elec ons in which a woman incumbent (Joyce Banda) was on the ballot and whose Lomwe ethnic group is dominant in Southeast Malawi. Ethnic Lomwe voters who were conflicted were less likely to follow co‐villagers who were not co‐ethnic with the incumbent president, which suggests that the People’s Party was indeed able to a ract Lomwe votes regardless of the type of community where Ms. Banda’s resided. For these voters, ethnic loyalty trumped loyalty to the village. The results in Models 1b, 2b, and 3b suggest rather complex within‐village poli cal dynamics. Or empirical results suggest that poli cal cleavages within local communi es are highly con ngent on ethnic (as)symmetry between voters and Chiefs. Voters who we iden fy as conflicted were less likely to “vote with the village” when they were themselves co‐ethnic with the village head, which highlights the vulnerability of poli cal outsiders within villages. Poli cal minori es in their village were very reluctant to vote differently from fellow villagers when they are not themselves co‐ethnic with their Chief. By contrast, those who are were far more willing to vote differently from the majority of fellow villagers, a behavior that is consistent with the norm that villages Chiefs should maintain poli cal neutrality and not meddle in electoral poli cs. Our findings are thus more nuanced and contextual. This norm seem to hold when voters and their Chief are co‐ethnic, but when they are not, it is the Chief’s preference that seems to carry the day. 19 Table 3: Village­level correlates of the decision to vote like the village 1a VARIABLES Vote with Vote with Vote with Vote with Vote with Vote with village: village: village: village: village: village: prez prez parl parl local local Rural ‐0.257 ‐0.390 0.244 0.214 ‐0.0861 0.404 (0.233) (0.401) (0.416) (0.391) (0.259) (0.362) la tude ‐0.112 ‐0.214* ‐0.334** ‐0.338** ‐0.0861 ‐0.179* (0.121) (0.114) (0.137) (0.150) (0.101) (0.0933) matrilineal 0.185 0.0330 0.757** 1.066** 0.718** 0.863** (0.255) (0.237) (0.316) (0.410) (0.311) (0.370) village_overall_ethniciza on 0.0628 ‐1.408 ‐0.322 (1.882) (2.175) (1.710) ‐2.449*** ‐2.101** ‐1.857** Lomwe Pres) (resp.co‐ethnic with 1b 2a 2b 3a 3b (0.778) (0.742) (0.806) Respondent co‐ethnic with MP ‐0.255 ‐0.154 ‐0.0819 (0.150) (0.248) (0.145) ‐1.223*** ‐1.059*** ‐1.198*** Respondent village‐head co‐ethnic with (0.312) (0.353) (0.340) born_in_this‐village ‐0.119 ‐1.017 ‐1.042 (0.845) (0.784) (0.768) wealthy_in_village 0.0533 ‐0.0752 0.349* (0.182) (0.184) (0.173) par es_in_village 0.124 0.388* ‐0.00500 (0.172) (0.196) (0.159) cso or religious organiza ons in village ‐0.0461 ‐0.263 0.00827 20 (0.149) (0.190) (0.139) Constant ‐2.497 ‐2.805 ‐7.306*** ‐5.557* ‐3.291** ‐3.864** (1.522) (2.018) (2.231) (2.918) (1.438) (1.685) Observa ons 6,193 5,745 6,157 5,588 6,154 5,612 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 21 Preliminary conclusions Our early analysis of recent survey data collected in Malawi suggests that the long‐standing debate between individual a ributes and social interac ons remains highly relevant in the context of a young, s ll mostly rural democracy. Whereas the extant literature on vo ng behavior in Africa focuses on ethnic cleavages and the importance of hierarchies within ethnic groups, we have iden fied instead a rich spectrum of vo ng behaviors that does not fit these models well. We find that half the voters cast their ballots based on factors emphasized in the individual vo ng literature. Among them, 14% ended up not vo ng like fellow villagers for President, 26% for parliament, and 11% for local councillors, which demonstrates that villages are not poli cally homogenous. As for the other half of “conflicted” voters who are the focus of this paper, we find that 22%, 12% and 14% of them voted like most fellow villagers on their presiden al, parliamentary and local ballots respec vely. We do deny the poli cal relevance of ethnicity, but we find strong preliminary evidence that the impact of ethnicity is mediated by the specific ways in which the ethnicity of Chiefs and villagers interact. Again, we could not detect such effects sta s cally if Malawian villages were ethnically homogenous. In the next round of revision of this paper, we will further explore whether and how much village‐level ins tu ons mediate the complex pa erns of vo ng behavior that we observe in our sample. 22