with greater community radio access. Households are less likely to report incomes in the lowest income bracket (less than 30,000 CFA) in villages with access to more community radios, but the relationship is only marginally significant in the bivariate specification and not at all significant in the multivariate.<sup>15</sup> According to the multivariate regressions, homes in villages with greater radio access are more likely to have brick walls, but _less_ likely to have cement floors and (not quite significantly) less likely to have five or more rooms. In the bivariate regressions, none of these is related to the number of radio stations. Again, the estimated community radio coefficients are robust, and their magnitude practically invariant, to controlling for these income and wealth variables.

Among the many proxies for village wealth, such as the availability of various facilities and infrastructure—private primary schools, secondary schools, paved roads, potable water sources, literacy center, and health center—only the presence of a secondary school is positively associated with village community radio access.

While donors targeted more remote and rural communes, within communes some villages are more remote and smaller than others, potentially leading to less community radio access and different attitudes towards clientelist politicians. Smaller and more remote villages could be more likely to have fewer accessible radio signals and particular attitudes towards clientelism. The results in Tables 4 and 5 indicate that, in fact, there is no significant correlation between measures of village size and remoteness and their access to community radio signals. The survey has information on village distance from urban centers and to a train or bus stop. The most recent census in Benin, from 2002, has information on village population for nearly all of the villages in the sample. There is no significant correlation between radio access and these measures of size and remoteness. Distance to the nearest urban center is marginally significant, but this is because of a single outlying village that reports a distance that is 50 percent higher than the next most remote village in the sample. Once this outlier is dropped, there is no significant correlation of distance with radio access.

Village ethnic, religious and linguistic characteristics, similarly inferred from the household data, could also influence community radio access and different attitudes towards clientelist politicians. The analysis uses controls for the four largest ethnic groups in the sample and the two religions (Catholic and Islam). There are significantly fewer Yoruba in areas with more community radio according to both the multivariate or bivariate specifications. Controlling for all other correlated, there are also fewer Yoa/Lokpa. It is also possible to compare villages linguistically, looking first at the probability that any two of the village households in the sample speak the same language at home; and, second, at whether the most common language among the sample households in a village is different from the most common language among all the households surveyed in the commune in which that village resides. These linguistic variables are also uncorrelated with radio access.

# **5. Results:  Radio access and citizen support for clientelism**

To examine radio’s influence on a range of outcomes, including political attitudes, we surveyed 20 randomly selected households in each of 210 villages across northern Benin in March

> 15 There are no census or statistically representative data of incomes and poverty rates at the village-level in Benin.  The survey offers one proxy for village income, which could be correlated with both radio and bed net access.   Sampled households were given a set of different income brackets and selected one to which their household belonged.  From a sample of 20 households in each village, we calculated the village-level variable of the share of respondents that reported belonging to the lowest income bracket.

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