Analysis of the spatial genetic structure within continuous populations in their natural habitat can reveal acting evolutionary processes. Spatial autocorrelation statistics are often used for this purpose, but their relationships with population genetics models have not been thoroughly established. Moreover, it has been argued that the dependency of these statistics on variation in mutation rates among loci strongly limits their interest for inferential purposes. In the context of an isolation by distance process, we describe relationships between a descriptor of the spatial genetic structure used in empirical studies, Moran’s I statistic and population genetics parameters. In particular, we point out that, when Moran’s I statistic is used to describe correlation in allele frequencies at the individual level, it provides an estimator of Wright’s coefficient of relationship. We also show that the latter parameter, as a descriptor of genetic structure, is not influenced by selfing rate or ploidy level. Under specific finite population models, numerical simulations show that values of Moran’s I statistic can be predicted from analytical theory. These simulations are also used to estimate the time taken to approach a structure at equilibrium. Finally, we discuss the conditions under which spatial autocorrelation statistics are little influenced by variation in mutation rates, so that they could be used to estimate gene dispersal parameters.