Gravity modeling in social science: the case of the commuting phenomenon in Greece

Abstract

This article empirically examines the utility of the gravity modeling in regard to its explanatory resolution, to its power against linearity, and to its geographical scale (intercity vs. interregional). For this purpose, the analysis is performed towards three directions; the first regards the model structure and examines how the number of explanatory variables (drafted from a pool of available predictors) affects the model determination, the second examines the model type, comparing the same predictor configurations entered to gravity multivariate linear regression models, and the third examines the changes induced corresponding interregional and intercity gravity models due to the effect of geographical scale. The analysis shows that the gravity modeling is generally effective in the study of systems of spatio-economic interaction, where the use of its standard expression appears a safe and simple choice. However, this model may also attain many effective extended expressions, and thus, it can be functional in higher complexity demand. Overall, this paper sheds some light to the interregional commuting for the case of Greece and highlights the utility of gravity model in the fields of Econophysics and of economic modeling.

Commuting Pattern Recognition Using a Systematic Cluster Framework

“…Subsequently, Varga [3] proposed a further generalization for the original radiation model-flow and jump model (FJM); test results showed that the FJM can offer an improved description for commuting data. Despite some limitations of the previous models [4][5][6][7][8][9], these models are widely used due to the advantages in approaching the mobility laws [6]. Some studies try to investigate the commuting pattern considering the stop-making behavior or land use properties.…”