Broadening the Ethnographic Atlas: Religion and Climate
There is a long tradition of research investigating the relationship between geography/climate and economic outcomes (geographical determinism). More recently, this theory has been revised and the new research argues that the effect of geography on economic development might be indirect via institutions: geography affects institutions and institutions affect economic development. Our research shows that geography, and in particular the local climate, affects religious institutions and religious beliefs. Religious institutions then affect both secular institutions and economic development directly. Our research has focused on Mediterranean regions and the Christian faith, but we believe the same mechanisms apply more broadly. The goal of this project is to extend the analysis of this mechanism to the rest of the world.
The Ethnographic Atlas is a dataset created by the anthropologist George Peter Murdock, and then extended by Patrick Gray. It contains information on all ethnic groups in the planet, historically. Although it contains detailed information regarding the culture of these societies, it only contains limited information regarding religious beliefs. Our goal is to extend the information in the atlas by adding information on whether each particular ethnicity has a ritual or a ceremony to ask the Divine for intervention by changing the weather, e.g., whether they pray for rain. We have information on hundreds of ethnicities, but we would want to extend to the remaining ethnicities.
In addition to the religious information we would need to add more detail climate information regarding each ethnicity. In particular, we would to recover information on rain and temperature with very precise geographical location. When we have such information we would need to create several indexes that can be used to test our particular hypothesis.
Requisite Skills and Qualifications:
The main goal for the RA would be to create the new dataset, both the religious and the climate variables. The RA would also use the preliminary data already collected and write code to clean the data and generate new variables. Finally, the RA would also create tables, graphs and maps with the dataset.