Add to ORKGThe aim of this paper is to evaluate the spatial and hierarchical models for data generating processes with spatial heterogeneity and spatial dependence at the higher level. The simulation for the m-SAR and HSAR models was used to discuss the consequences of spatial misspecification. We noticed that the misspecification of spatial homogeneity or heterogeneity in both models affects i.a. the estimated parameter for spatial interactions at the individual level. Applying a m-SAR model for spatially heterogeneous processes causes the overestimation of the spatial interaction parameter
In this study, I investigate the necessary condition for consistency of the maximum likelihood estim...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
In this paper, the problem of combining information from different data sources is considered. We f...
The aim of this paper is to evaluate the spatial and hierarchical models for data generating process...
Hierarchical models have a long history in empirical applications; recognition of the fact that many...
Spatial regression models provide the opportunity to analyse spatial data and spatial processes. Yet...
In this simulation study, regressions specified with autocorrelation effects are compared against th...
In this paper I will give a brief and general overview of the characteristics of spatial data, why i...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
This article aims at testing the possibilities of applying hierarchical spatial autoregressive model...
In multilevel modelling, interest in modeling the nested structure of hierarchical data has been acc...
Spatial econometric methods aim at taking into account the two special characteristics o...
This study focus on models with spatially varying coefficients using simulations. As shown by Sarri...
This paper develops a methodology for extending multilevel modelling to incorporate spatial interact...
In this study, I investigate the necessary condition for consistency of the maximum likelihood estim...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
In this paper, the problem of combining information from different data sources is considered. We f...
The aim of this paper is to evaluate the spatial and hierarchical models for data generating process...
Hierarchical models have a long history in empirical applications; recognition of the fact that many...
Spatial regression models provide the opportunity to analyse spatial data and spatial processes. Yet...
In this simulation study, regressions specified with autocorrelation effects are compared against th...
In this paper I will give a brief and general overview of the characteristics of spatial data, why i...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
We evaluate by means of Monte Carlo simulations the W-based spatial autoregressive model and the str...
This article aims at testing the possibilities of applying hierarchical spatial autoregressive model...
In multilevel modelling, interest in modeling the nested structure of hierarchical data has been acc...
Spatial econometric methods aim at taking into account the two special characteristics o...
This study focus on models with spatially varying coefficients using simulations. As shown by Sarri...
This paper develops a methodology for extending multilevel modelling to incorporate spatial interact...
In this study, I investigate the necessary condition for consistency of the maximum likelihood estim...
We examine a higher-order spatial autoregressive model with stochastic, but exogenous, spatial weigh...
In this paper, the problem of combining information from different data sources is considered. We f...