The main objective of this study is to evaluate the impact of maritime transportation instability on international trade instability based on wavelet smoothing and spatial panel data econometric method during the period 1990-2012. The results showed that the spatial effects have an impact on international trade instability. So that a sudden 100 percent increase in international trade in the nei...

societies have paid attention to safety. this study examines the relationship between socio-economic factors and crime, emphasizing on immigration. due to the locational aspect of the data, spatial econometric techniques are used. the model has been specified in the form of spatial durbin panel data model (sdpdm). the specified model has been estimated for 30 provinces of iran in 2006-11 by con...

Regression analysis with geographic information needs to take into consideration the inherent spatial autocorrelation and heterogeneity of the data. Due to such spatial effects, it is found that local regression such as the geographically weighted regression (GWR) tends to capture the relationships better. In addition, in panel data analysis, the variable coefficient panel regression can borrow...

background: using spatial analysis tools to determine the spatial patterns of china province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. methods: the global moran’s i index is used to examine whether the spatial autocorrelation exists in selected regions and moran’s i s...

oil sector is the most effective sector in these countries. oil is the most important product that world industries use as the cheapest energy. the price of oil depends on the world’s supply and demand and many economic, political and geographical variables. this is the reason why the price of oil has fluctuations. the fluctuations in oil price lead to fluctuate in the oil revenues of the membe...

Due to criticisms of potential identification issues within spatial panel data models, this study contributes to the literature by comparing forecasts of provincelevel carbon dioxide emissions against empirical reality using dynamic, spatial panel data models with and without fixed effects. From a policy standpoint, understanding how to predict emissions is important for designing climate chang...

We investigate farmers’ decision to engage in organic production. Our objective is to identify the key factors that promote or hinder the update of organic farming. In particular, we focus on neighborhood factors and the spatial allocation of organic land parcels. A rich spatial panel data of all agricultural parcels is compiled and the information on land use, soil quality, biodiversity, local...

This paper studies the convergence of per-capita GDP across European regions over a fairly long period. Most of the works in the field are based on either cross-sectional or fixed-effects estimates. We propose the estimation of convergence in per-capita GDP across European regions by making use of panel-data models extended to include spatial error autocorrelation (Anselin, 1988; Elhorst, 2003)...