question in two ways. The first approach is based on testing whether the coefficients on the education variables of interest estimated over the subsample of women with no education are different from those estimated over the subsample of women with some education.<sup>22</sup> Although there is some ambiguity, the test statistics (Table A7) do not permit us to reject the hypothesis that the coefficients are the same across the subsamples (the hypothesis can be rejected only for spousal education in the case of child immunizations). Second, following Davidson and MacKinnon (1993), we also explore a more direct approach to test for the appropriateness of an alternative specification with a rival set of conditioning variables. The test asks whether there is any statistically significant evidence of departure from the null hypothesis in the direction of an alternative hypothesis. The results provide evidence in favor of the alternative specification in the case of pregnancy control, but not for the other health care choices (Table A8). In summary, the specification tests are inconclusive. They suggest that the rival specification of the relevant education variable may be more appropriate for some education variables, or in explaining some choices. There is, however, no basis for unambiguously favoring one specification over the other.

# **6. Summary and Conclusion**

This paper has focused on the role of intrahousehold education externalities in health care choices. Its central premise is that health service use is determined not solely by an individual’s own education, but rather by some notion of _effective education_ , which incorporates the educational attainment of other household members. The paper sets out a general framework for representing education externalities and proposes a number of specific hypotheses concerning the way in which the education of different household members impacts on health care choices. These hypotheses were tested on data from Mozambique, focusing on maternity services and child immunizations. We can draw five major conclusions from the analysis.

First, while own/maternal education seems to be the education variable of primary importance for the health care choices under consideration, the education of other household members does have a significant and sometimes large effect. Importantly, it is not only the education of the spouse that matters, but also the education of other individuals residing in the household. Indeed, the marginal effect of education is greater for the nonspouse household member with the highest level of education than for the spouse. These findings appear robust to the how the education variable is specified. Second, the analysis suggests that while the education of the person (nonspouse) in the household with the highest-level education is important, the level of education of additional household members does not have an impact on health care choices. Third, the data provide no evidence of a gender difference in education externalities. In other words, the impact of the education of nonspouse household members on health care decisions seems to be the same regardless of whether they are men or women. Fourth, we examine the merits of two alternative representations of the education externality. In the original representation, education is measured as the highest grade completed. In the alternative specification, the educational attainment of other household members is measured as the deviation from

> 22 This is done by testing restrictions in a model estimated over both subsamples, but including a set of independent variables constructed by interacting all the original variables (including the constant) with a subsample dummy variable.

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