These effects, however, are entirely conditional on access to radio. The third column reports results from interacting the radio access variable with the gender of the respondent and the number of children in the household. Female respondents with no access to radio are no more likely to know about ORS treatment; nor are households with children. However, among respondents in which the household respondent is female and the household has the median number of children (two), an increase in the number of community radio stations from zero to the median (two) leads to a 4.4 percentage point increase in the fraction of respondents who respond correctly to the ORS question; 48 percent of all respondents answered this question correctly.

Another survey question, which is likely correlated with household knowledge of good health practices, relates to awareness of the rates of child mortality. Greater knowledge of child mortality rates may be especially correlated with health messages related to malaria and the efficacy of bed-nets, given that this disease is one of the leading causes of death among children before they reach their fifth birthday. Respondents were asked to give a ball-park estimate of child mortality rates in Benin—around how many among any 100 children born in Benin would not survive beyond the age of five. Only 15 percent of respondents correctly answered with the right range (based on national statistics). The last column in Table 5 shows that village radio access has a significant positive effect on correctly identifying the range of child mortality rates in Benin. These results are consistent with media effects on household knowledge of health practices and outcomes, which would account for the estimated reduced-form effect of media access on household private investment in anti-malaria bed nets.

# **Robustness**

The results in Table 4 are robust to a large number of other specifications. First, the estimates are based on household observations. They are clustered and therefore not assumed to have independently-distributed errors at the village level. However, since bed net distribution could be focused on villages, and radio access varies by village, the village could be the more appropriate unit of observation.

Table 6 reports the results of estimating equation (1) at the village level. The survey includes information on village level characteristics that might affect the availability of bed nets, in addition to radio access: the distance of the village to the nearest urban center or to the nearest bus or train stop; the number of new potable water sources in the village and whether the village has a paved road; the number of functional private schools; whether the village has access to a literacy center of health/maternity center; the level of education of the village chief. All of these are controlled for. The village population comes from census data. Unfortunately, the census has no income data at the village level. We therefore average village responses to the income and housing quality questions and control for these averages. Finally, in a linguistically diverse country, linguistic heterogeneity could affect access to bed nets. We control for two variables, again based on household responses to the survey: whether the main village language and the main commune language are the same; and the probability that any two households in the village sample speak the same language.

The estimates in Table 6 reinforce the results presented in Table 4: radio access increases both the willingness of households to pay for bed nets and the diversion of potentially free bed nets into the paid market. As before, access to community radio has no significant effect on the total number of bed nets and a negative, insignificant effect on the number of free bed nets reported by households. In contrast, again as in the earlier estimates, radio access leads households to acquire a significantly larger number of paid government bed nets.

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