Estimating Inter-Regional Freight Demand in China Based on the Input–Output Model

Wenjie Li, Chun Luo, Yiwei He, Yu Wan and Hongbo Du ()
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Wenjie Li: National Inland Waterway Regulation Engineering Research Center, Chongqing Jiaotong University, Chongqing 400074, China
Chun Luo: Key Laboratory of Ministry of Education for Hydraulic and Waterway Transport Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Yiwei He: Key Laboratory of Ministry of Education for Hydraulic and Waterway Transport Engineering, Chongqing Jiaotong University, Chongqing 400074, China
Yu Wan: National Inland Waterway Regulation Engineering Research Center, Chongqing Jiaotong University, Chongqing 400074, China
Hongbo Du: National Inland Waterway Regulation Engineering Research Center, Chongqing Jiaotong University, Chongqing 400074, China

Sustainability, 2023, vol. 15, issue 12, 1-16

Abstract: The inter-regional freight volume is a crucial factor for transportation infrastructure planning and investment decision-making. However, existing studies on freight volume estimation have mainly focused on the total freight volume within a specific region, without taking freight flow into consideration. In this research, a gravity model was employed to estimate the inter-regional trade coefficient matrix based on the input–output tables of the 31 provinces in China in 2017. The inter-regional freight volume was then determined by converting the value flow into freight flow. To determine the model parameters, we used information from 2017 and subsequently validated the results using dates from 2012 to 2020. We also studied the impact of industrial structure change on freight volume by simulating dates from the aforementioned model in 2017. The results indicated that the model can effectively simulate inter-regional freight volume while taking into account the influence of industrial restructuring.

Keywords: inter-regional freight demand; input–output tables; GDP; industry structure (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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