Spatial econometrics for misaligned data

Author(s):  
Guillaume Allaire Pouliot
2021 ◽  
Vol 13 (12) ◽  
pp. 6930
Author(s):  
Shinsuke Kyoi

This study evaluates people’s preferences regarding the proximity of their residence to agricultural urban green infrastructure (UGI), such as agricultural land and satoyama, and discusses the availability of these types of land as UGI. UGI is vital for reducing the negative environmental impacts of urban areas, as these impacts are too large to ignore. In this study, we conducted an online survey and a choice experiment to investigate people’s perceptions regarding the proximity of their residence to agricultural UGI (AUGI). The respondents of the choice experiment were 802 inhabitants of Ishikawa Prefecture, Japan, which has rich agricultural resources. To examine explicitly the spatial autocorrelation of people’s preferences, in this study, we used the spatial econometrics method. The main empirical findings are that people prefer agricultural land far away from their residence—more than 1000 m, not within 1000 m—which reflects the not-in-my-backyard phenomenon. Meanwhile, people’s preferences regarding proximity to satoyama are complicated and their preferences are positively spatially autocorrelated. The results indicate that policymakers and urban planners should manage and provide AUGI far away from residential areas; otherwise, they must address people’s avoidance of neighboring AUGI.


Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1276
Author(s):  
Roger Bivand ◽  
Giovanni Millo ◽  
Gianfranco Piras

The software for spatial econometrics available in the R system for statistical computing is reviewed. The methods are illustrated in a historical perspective, highlighting the main lines of development and employing historically relevant datasets in the examples. Estimators and tests for spatial cross-sectional and panel models based either on maximum likelihood or on generalized moments methods are presented. The paper is concluded reviewing some current active lines of research in spatial econometric software methods.


2015 ◽  
Vol 5 (2) ◽  
pp. 19-36
Author(s):  
Anis Kacem

Tunisia has signed a free trade agreement with the European Union in 1996, which provides for the reduction of tariff barriers between Tunisia and the EU. In this article, we aim to know and test whether the similarity of the institutional framework has to stimulate international trade between Tunisia and the European Union. In this context, we built a variable called “Institutional distance” to valid the institutional dimension of international trade, near borders effects reported in the literature. To this end, a gravity model was used initially (Tunisia and 21 European countries). Secondly, the estimate shows the existence of spatial autocorrelation. The latter has been corrected using spatial econometrics. The results show that the geographical distance remains more important than the institutions in this type of agreement between north and south shores of the Mediterranean.


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