This paper attempts to describe the graphical behavior of the distributed lag model in an infinite coordinate space. The "mega distributed lag model" (MDL) is a mathematical framework that can examine the simultaneous interrelationships between all involved variables. The multidimensional...

In this article I provide a (selective) review of the recent econometric literature on networks. I start with a discussion of developments in the econometrics of group interactions. I subsequently provide a description of statistical and econometric models for network formation and approaches...

Random graph generation is an important tool for studying large complex networks. Despite abundance of random graph models, constructing models with application-driven constraints is poorly understood. In order to advance state-of-the-art in this area, we focus on random graphs without short...

Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Design/methodology/approach: Network modeling by combining Petri and Bayesian network. Findings: Modeling with...

This paper studies inference on fixed effects in a linear regression model estimated from network data. We derive bounds on the variance of the fixed-effect estimator that uncover the importance of the smallest non-zero eigenvalue of the (normalized) Laplacian of the network and of the degree...

The article deals with neighborhood ties to European Union countries in terms of graph theory. It is determined the minimum distance between states and the consequences, in terms of minimum distance, of leaving the European Union by one country or another.

In this paper, we propose to employ the framework of graph-transformational swarms for the modeling of dynamic logistic networks with decentralized processing and control. The members of a graph-transformational swarm act and interact in a common environment graph with massive parallelism of...