scholarly journals Simultaneous consideration of spatial heterogeneity and spatial autocorrelation in European innovation: a spatial econometric approach based on the MGWR-SAR estimation

2021 ◽  
Author(s):  
Andrea Furková
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Autocorrelation ◽  
Spatial Econometric ◽  
Econometric Approach

scholarly journals Local voting in Russia: a spatial-econometric approach

2021 ◽  
Author(s):  
E.M. Korneeva
Keyword(s):  
Spatial Autocorrelation ◽  
Local Level ◽  
Political Regime ◽  
Spatial Econometric ◽  
Parliamentary Elections ◽  
Political Processes ◽  
Spatial Differences ◽  
Spatial Interdependence ◽  
Econometric Approach

The article presents theoretical and methodological foundations for the application of the spatial-econometric approach in electoral processes. The analysis based on spatial-econometric approach that underlies an assumption about interdependence of processes occurring in adjacent objects. Theoretical framework of research is devoted to social-political assumptions that allow to explore the existence of interdependence of political processes occurring in neighboring objects. Empirical research is accomplished on local constituencies data from all parliamentary elections that took place in Russia in 1995–2016. The research involves addressing the concept of spatial autocorrelations – Moran, Geary and Getis – Ord indices. The research focuses on issue about the degree of spatial differences between regional and local voting. The results of research demonstrate that there is a high spatial interdependence in local voting in Russia. A comparative analysis of spatial autocorrelation on local and regional levels demonstrates that the municipal districts are most prone to spatial interdependence. This finding allows to trace a hidden tendences on local level of elections. Such differences between local and regional spatial autocorrelation identify that regional political regime can be an obstacle on the way of restraining the territorial distribution of local communities with similar electoral behavior. Finally, the research proves that the role of place is significant in Russian electoral space.

The peer effect of training on farmers' pesticides application: a spatial econometric approach

2020 ◽  
Vol 12 (3) ◽  
pp. 481-505
Author(s):  
Li Zhou ◽  
Fan Zhang ◽  
Shudong Zhou ◽  
Calum G. Turvey
Keyword(s):  
Peer Effects ◽  
Spillover Effects ◽  
Technical Training ◽  
Pesticide Use ◽  
Spatial Econometric ◽  
Agricultural Technologies ◽  
Content Type ◽  
Spatial Econometric Models ◽  
Estimated Parameters ◽  
Econometric Approach

PurposeThe purpose of this paper is to examine the relationships of technical training and the peer effects of technical training with farmers' pesticide use behaviors.Design/methodology/approachThis study uses survey data from 300 peanut growers in Zoucheng County, Shandong, China, in 2016 and employs spatial econometric models to examine the relationships of technical training and the peer effects of technical training with farmers' pesticide use behaviors.FindingsThis paper reveals that important peer effects can be channeled through technical training and that these peer effects are sufficiently significant to encourage neighboring farmers to reduce the amount of pesticide use, to transform the structure of pesticide use, and to increase the usage amount of low-toxicity, low-residue pesticide use per hectare. The estimated parameters for the peer effects from technical training are significantly larger than those from technical training alone, which suggests that the technical training of neighboring farmers plays a greater role than technical training for farmers individually.Originality/valueThe research finds that technical training within smaller, localized, groups can induce previously unobservable spillover effects, and this provides a scientific, theoretical and empirical justification for agricultural technology extension that can lead to a rapid, effective transformation of applying new agricultural technologies in an environmentally sensitive and economically sustainable manner.

scholarly journals Variability of spatial patterns of autocorrelation and heterogeneity embedded in precipitation

2018 ◽  
Vol 50 (1) ◽  
pp. 215-230
Author(s):  
Dedi Liu ◽  
Qin Zhao ◽  
Shenglian Guo ◽  
Pan Liu ◽  
Lihua Xiong ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Autocorrelation ◽  
Spatial Patterns ◽  
Spatial Interpolation ◽  
Kendall Test ◽  
Test Methods ◽  
Distributed Hydrological Model ◽  
Interpolation Methods ◽  
Increasing Trend ◽  
Spatial Interpolation Methods

Abstract Spatial interpolation of precipitation data is an essential input for hydrological modelling. At present, the most frequently used spatial interpolation methods for precipitation are based on the assumption of stationary in spatial autocorrelation and spatial heterogeneity. As climate change is altering the precipitation, stationary in spatial autocorrelation and spatial heterogeneity should be first analysed before spatial interpolation methods are applied. This study aims to propose a framework to understand the spatial patterns of autocorrelation and heterogeneity embedded in precipitation using Moran's I, Getis–Ord test, and semivariogram. Variations in autocorrelation and heterogeneity are analysed by the Mann–Kendall test. The indexes and test methods are applied to the 7-day precipitation series which are corresponding to the annual maximum 7-day flood volume (P-AM7FV) upstream of the Changjiang river basin. The spatial autocorrelation of the P-AM7FV showed a statistically significant increasing trend over the whole study area. Spatial interpolation schemes for precipitation may lead to better estimation and lower error for the spatial distribution of the areal precipitation. However, owing to the changing summer monsoons, random variation in the spatial heterogeneity analysis shows a significant increasing trend, which reduces the reliability of the distributed hydrological model with the input of local or microscales.

A Biparametric Approach to Spatial Autocorrelation

1979 ◽  
Vol 11 (1) ◽  
pp. 51-58 ◽  
Author(s):  
A S Brandsma ◽  
R H Ketellapper
Keyword(s):  
Maximum Likelihood ◽  
Spatial Autocorrelation ◽  
Likelihood Ratio Test ◽  
Econometric Models ◽  
Ratio Test ◽  
Spatial Econometric ◽  
Maximum Likelihood Approach ◽  
Spatial Econometric Models ◽  
Likelihood Approach ◽  
Error Terms

In spatial econometric models, autocorrelation among error terms is usually incorporated by means of the so-called contiguity matrix W, determining the interdependence between the spatial observations on the dependent variable. In this paper, the analysis is generalized by introducing two contiguity matrices, related to two autocorrelation parameters. This may be useful when dealing with variables representing flows between regions, where both the origin and the destination regions have a different impact on the autocorrelation scheme. It is shown analytically and illustrated empirically that the presence of such autocorrelation can be tested with the likelihood-ratio test, whereas the parameters can be estimated by the maximum-likelihood approach.

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