Semi-parametric spatial autoregressive models in freight generation modeling

Krisztin, T. ORCID: (2018). Semi-parametric spatial autoregressive models in freight generation modeling. Transportation Research Part E: Logistics and Transportation Review 114 121-143. 10.1016/j.tre.2018.03.003.

[thumbnail of 1-s2.0-S1366554517309602-main.pdf]
1-s2.0-S1366554517309602-main.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview
Project: GLOBIOM


This paper proposes for the purposes of freight generation a spatial autoregressive model framework, combined with non-linear semi-parametric techniques. We demonstrate the capabilities of the model in a series of Monte Carlo studies. Moreover, evidence is provided for non-linearities in freight generation, through an applied analysis of European NUTS-2 regions. We provide evidence for significant spatial dependence and for significant non-linearities related to employment rates in manufacturing and infrastructure capabilities in regions. The non-linear impacts are the most significant in the agricultural freight generation sector.

Item Type: Article
Uncontrolled Keywords: Non-linear spatial autoregressive models; Genetic algorithms; Semi-parametric modeling; Freight generation
Research Programs: Ecosystems Services and Management (ESM)
Depositing User: Luke Kirwan
Date Deposited: 18 Apr 2018 06:01
Last Modified: 27 Aug 2021 17:30

Actions (login required)

View Item View Item