The macro-level effect of religiosity on health

An issue that has not yet been explored in the religiosity-health literature is the macro-level effect of religiosity on health-the effect of the religiosity of a society on the absolute health of the population of that society as a whole. We address this issue using two panel datasets: The first is a time-series cross-sectional panel dataset for 17 countries from 1925 to 2000. The second is a cross-sectionally dominated panel dataset of up to 92 countries for the period 1981-2016. Our main findings are as follows: first, religiosity has a significant negative causal effect on health at the macro level; second, a substantial part of this effect can be attributed to an indirect effect via public health expenditures; and third, changes in population health do not cause significant changes in societal religiosity.

Theory and explanation in demography: The case of low fertility in Europe

In the 50th anniversary edition of Population Studies, John Hobcraft commented that demographers spend too little time trying to explain the phenomena they measure and describe. A quarter of a century on, this paper looks at the state of theory and explanation in contemporary demography. I ask how demographers have approached the task of explanation since Hobcraft's comment, grounding the discussion in the mainstream literature on low fertility in Europe. Using selected examples, I critically review macro- and micro-level approaches to explanation, highlighting some of the philosophical problems that each encounters. I argue that different conceptions of what demography is, and the explanatory language fertility researchers use, lead to differences in explanatory strategies that are rarely explicitly recognized. I also consider how critical theories challenge demographers to think in new ways. Despite the increasing attention paid to theory and explanation, I conclude that more engagement with the philosophy of social sciences is needed before fertility researchers can legitimately claim their studies do as much to explain and understand as to quantify and describe.