the purpose of this study is to determine spatial dependency pattern of systematic risk of dry land wheat production in iran, using spatial autoregressive models. to this end, spatial weighted contiguity matrix was constructed based on the delaunay triangularization method, and correlation coefficient among these neighbors were estimated using spatial autoregressive models. in addition, the rol...

introduction: under the principles of international law, no state has the right to use or permit the use of its territory in such a manner as to cause damage to the environment of other states. spatial econometrics provides a powerful tool to assess the influence of the pollution of neighboring countries on a country's pollution level. spatial spillover effects play a significant role in a...

This paper is concerned with modelling and estimating panel data autoregressive spatial processes in the framework of minimum distance methods. A contiguity matrix based on distance between points relates observations spatially. The model is estimated in two stages. First, the cross-section parameters are consistently estimated by maximum likelihood, and a consistent asymptotic covariance matri...

We examine violent conflict's spillover effects on food insecurity in Uganda, Ethiopia, and Malawi. Using a contiguity matrix weighted the distance between housing units data from Living Standard Measurement Survey, we find statistically significant effect of conflict security Ethiopia Uganda. Statistically indirect were negative within Malawi positive Ethiopia. Direct conflicts other covariate...

let and be a sequence with non-negative entries. if , denote by the infimum of those satisfying the following inequality: whenever . the purpose of this paper is to give an upper bound for the norm of operator t on weighted sequence spaces d(w,p) and lp(w) and also e(w,?). we considered this problem for certain matrix operators such as norlund, weighted mean, ceasaro and copson matrices. th...

An Euclidean graph associated with a molecule is defined by a weighted graph with adjacency matrix M = [dij], where for ij, dij is the Euclidean distance between the nuclei i and j. In this matrix dii can be taken as zero if all the nuclei are equivalent. Otherwise, one may introduce different weights for distinct nuclei. Balaban introduced some monster graphs and then Randic computed complexit...