Abstract

This paper presents a methodological procedure to evaluate the influence of spatial proximity on evolution of cities to detect regional differences in their spatiotemporal dynamics. The six-step method based on a set of statistical methods can be computed with a new R package: estdaR. The first step consists of the usual characterization of the cross-sectional distribution of the urban areas by means of nonparametric estimations of density functions for a set of significant years. In the second and third steps, the growth process is modeled as a first-order stationary Markov chain to evaluate the effect of global and local spatial autocorrelation on the transition probabilities with a set of indices based on the spatial version of the standard Markov chain. The fourth, fifth, and sixth steps perform in-depth analysis to detect the existence and interaction of spatial regimes in the movement direction and ranking mobility of urban distribution. We apply this novel strategy for the period 1930-2002 to analyze the entire Chilean urban system-not only the Central Zone, in which most of the population and economic activities are concentrated, but also other urban zones in the country.