Distributional dynamics of patenting across states in Mexico: A spatial Markov chain approach

Resumen

This investigation aims to analyze the distributional dynamics of patenting across Mexican states. Our main results suggest, by means of implementing a spatially conditioned Markov chain framework, the regional context is relevant to understand the evolution of the state patenting patterns of distribution over time and across space in Mexico. In this regard, additional evidence suggests top-innovators states interacting with neighboring states sharing similar levels of regional patenting may benefit from positive spatial externalities, while those states positioned in lower levels of the patenting distribution would experience difficulties in accessing top-innovators’ technological knowledge that may impede their upward transition to higher classes within the patenting distribution.