Spatial and Cultural Autocorrelation in International Datasets

Positive autocorrelation implies that proximate observations take on similar values. “Proximate” can be defined in many different dimensions. In a cross-section of nations, it can be defined using physical distance, cultural similarity, ecological similarity, or using frequency and intensity of interaction, such as trade relationships or enemy and ally relationships. Autocorrelation of regression residuals presents well-known problems in least-squares estimation, but autocorrelation also provides useful information for exploratory data analysis and model specification. The paper shows that autocorrelation is widespread in international datasets. The paper demonstrates the usefulness of autocorrelation in uncovering stylized facts about international relations, and in specifying a least-squares model.