Spatial Inference on Oil and Economic Development
A four-year research project funded by the Research Council of Norway.
This project studies how oil and gas activity affects economic, social, and demographic outcomes, across space and time. The project is funded by The Research Council of Norway. Our team consists of researchers within economics, political science, and geography from top universities in the U.S., the U.K., Denmark, Finland, and Sweden.
Oil and gas revenues amount to between two and five percent of the world’s total income. This project uses unique geolocalized data to explore how these revenues systematically affect economic and social development not only close to, but also further away from the extraction sites.
Over the last decade, several extensive geolocalized data sets on variables such as local income, health, ethnicity, infrastructure, population density, civil conflict, and wars have become publicly available. Some of these data come from satellite images, others from large surveys. We will couple these data with detailed oil and natural gas field data to estimate, for example, how changes in the oil income of an oil field or an oil region spreads across space and time.
In a next step, we might then study how the oil induced income changes affect local social and economic conditions, as well as local and global geopolitical relations.
The project, thus, has two main purposes. The first is to study the direct, local effects of oil activity. The second is to learn more about how local economic shocks, more generally, travel across space and time.
One might think that higher income is always for the better, but existing research suggests it is sometimes the opposite. For example, if the income is unevenly distributed so as to increase inequality, this may increase the general level of conflict in society. Whether overall social welfare increases or decreases may then depend on factors such as the political system, social cohesion versus fractionalization, and conflict history.
This project will contribute to broaden our knowledge about the spatial relationship between local income shocks and social welfare.