is huge—of an estimated 17 and 28 percentage points (compared to a sample average of 38 percent reporting vote buying). These district fixed effects are the most robust correlates of vote buying across all specifications, as can be seen from the results across all columns in Table 1.

However, column (2) of Table 1 shows that the variable measuring clan domination in municipal politics, or lack thereof, is opposite in sign to that suggested by congressional district fixed effects. Greater inter-clan competition, or lack of a single clan being entrenched in municipal politics across term limits, is associated with 9 percentage points lower reported vote buying. This coefficient is not as robustly significant as those for the district fixed effects. The correlations between vote buying and the domination of political clans are difficult to interpret because of obvious concerns of reverse causality—vote buying practices may enable some political clans to thwart competition. In other cases, however, vote buying may enable new candidates to launch a challenge to a political clan. The correlation of vote buying with these political characteristics may be idiosyncratically different across municipalities.

Another, more standard measure of political competition—the margin of victory—for the years for which data is available, exhibits a negative correlation with vote buying (column 3). That is, in municipalities where margins of victory are on-average greater across elections, perhaps representing lower competitive pressures, vote buying is reported to be lower. It is difficult to interpret this correlation, however. Vote buying may be mechanistically linked to margins of victory. Where political competition involves greater vote buying, margins of victory may be lower because challengers are able to buy votes. Furthermore, the quality of data here is suspect, with a large number of missing values (for 5 out of 30 municipalities for the most recent election of 2007 before the survey). Missing electoral data may not be unrelated to underlying political characteristics of municipalities.<sup>26</sup> Greater poverty has been widely hypothesized as facilitating vote buying (Stokes, 2005), especially in interaction with electoral competition (Weitz-Shapiro, 2012). Small area estimates of poverty are available from the National Statistics Office in the Philippines. These estimates combine information from nationally representative household surveys, with information from the census, to generate what the poverty literature considers to be some of the most reliable estimates at lower levels of disaggregation (Elbers et al, 2003).

There is little robust and significant correlation of poverty incidence with vote buying (columns 4-7). Although the coefficient point estimate in most specifications suggests that greater poverty could be associated with greater vote buying, the estimate is not typically statistically significant. At the very least, this casts doubt on any poverty-based alternate explanation for the correlation between vote buying and health services.<sup>27</sup> There are no robust patterns in the data to show that greater competition (measured through (lower) margins of victory, or as (lack of) entrenchment of clans) and higher poverty together explain greater vote buying. One possibility for why poverty and its interaction with available measures of electoral competition do not show-up significant here is because of the highly disaggregated nature of the sample, relatively small municipalities within one province in the Philippines. Poverty

> 26 Another measure of electoral competition was also included in various specifications—the number of candidates competing for mayoral office—but this was typically insignificant, in the majority of specifications. 27 In the main results presentation in Section 4, the paper uses various specifications and measures of poverty to establish that the correlation of interest—between vote buying and health services—is not driven by poverty.

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