Gravity and Spatial Structure: The Case of Interstate Migration in Mexico*

Abstract

The estimation of gravity models of internal (aggregate) place‐to‐place migration is plagued with endogeneity (omitted‐variable) biases if the unobserved effects of spatial structure are not accounted for. To address this econometric problem, this paper presents a more general specification of the gravity model, which allows for (bilateral) parameter heterogeneity across individual migration paths—along with (unilateral) origin‐ and destination‐specific effects. The resultant “three‐way fixed‐effects” (3FE) model is applied for an analysis of interstate migration in Mexico based on cross‐sectional data. To overcome parameter‐dimensionality problems (due to limited or incomplete information), the 3FE model is estimated using the Generalized Maximum Entropy (GME) estimator. The empirical implications of this new modeling strategy are illustrated by contrasting the 3FE‐GME estimates with those for the traditional and two‐way fixed‐effects (2FE) models. The former are far more plausible and intuitively interpretable than their traditional and 2FE counterparts, with parameter estimates changing in expected directions. The (average) effect of the migrant stock is markedly smaller than usually estimated, providing a more realistic measure of network‐induced migration. Migration outflows from centrally located origins have significantly steeper distance decay. Path‐specific distance effects exhibit directional asymmetries and spatial similarities.

Internal migration in a developing country: A panel data analysis of Ecuador (1982–2010)

“…As explanatory variables, we include basic gravity factors – the population of origin and destination and the distance between them – approximating the costs associated with migration (Peeters ). The distance variable can be measured in kilometres and expressed in logarithms ( L Dist ), as in Mayda (), or in terms of time ( L Time ), which is closer to the economic concept of the cost of moving.…”

Gravity Models of Interregional Migration in Indonesia

“…A popular proxy to measure the network effects of migration is the migrant stock. The migrant stock is defined as the accumulated number of previous in-migrants to the destination who have migrated from a particular region of origin (Beine, Bertoli, and Moraga 2014;Fan 2005;Greenwood 1969aGreenwood , 1975Peeters 2012).…”

Spatial Interaction

“…Care is certainly required when the models are deployed in situations with added complexity. For example, regional migration within Mexico is clearly influenced by proximity to the US border (Peeters, 2012). These techniques have been deployed on some massive regional movements such as interregional movement and migration in China (Shen and Wang, 2012).…”