The STARMA (space-time autoregressive moving average) model class was introduced in the mid-1970s as a spatio-temporal extension to the ARMA time series model class. To enhance the model’s ability in dealing with spatial dependence and heterogeneity of observations, the article extends...

The contention of this paper is that many social science research problems are too “wicked” to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is...

A series of recent papers have introduced some explorative methods based on Ripley’s K-function (Ripley in J R Stat Soc B 39(2):172–212, <CitationRef CitationID="CR43">1977</CitationRef>) analyzing the micro-geographical patterns of firms. Often the spatial heterogeneity of an area is handled by referring to a case–control design, in...</citationref>

Agricultural productivity is characterized by location patterns, represented by the so-called spatial effects, namely, spatial heterogeneity and spatial dependence. This paper analyzes the spatial effects which exert influence on agricultural land productivity at three points in time – 1991,...

This study try to identify the â-convergence process among regions in East Java using cross-section data of 30 regions for period 1983-2001, taking into account the presence of spatial heterogeneity and spatial dependence. Detection of spatial regimes using G-I* statistics on regional per...

This paper explores the implications that spatial effects can hold for the application of measures of sigma-convergence. The bias of a common indicator of convergence is examined for a family of spatial process models including: [a] spatial lag, [b] spatial error, and [c] spatial moving average....

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory....

Como no Brasil existem grandes heterogeneidades com relação à renda per capita, buscou-se estudar importantes aspectos determinantes da formação dessa renda nos diversos municípios. Com base em dados de 5.425 municípios, foram empregadas técnicas de análise exploratória de dados...

When analyzing economic aspects at regional levels, the spatial dimension of the data plays a crucial role. This is the case as spatial data and models are often characterized by two spatial effects, namely spatial dependence and spatial heterogeneity. The field of spatial econometrics is a...