Measuring causal effects of disasters and consequent relief activity on truckload markets

Shraddha Rana, Jarrod Goentzel and Chris Caplice

Transportation Research Part E: Logistics and Transportation Review, 2025, vol. 201, issue C

Abstract: During disasters the demand for transportation increases to distribute relief supplies, but the capacity decrease due to damaged infrastructure and competition for limited assets, leading to higher procurement prices. With the increase in frequency of natural disasters and resulting economic losses, we are motivated to study the historical impact to prepare for the future. We contribute to the disaster modeling, management, and transportation planning literature by measuring the causal effects of disasters on a critical system’s performance, i.e., truckload transportation procurement prices. This research quantifies the magnitude, geographical extent, timing, and duration of the causal effects of disaster (Hurricane Harvey and Hurricane Irma) conditions and consequent relief activity by the Federal Emergency Management Agency (FEMA) on the procurement prices using a difference-in-differences methodology. We find that long-haul truckloads inbound to nodes near the hurricane’s paths experienced the largest statistically significant increase in prices during the hurricane periods. Additionally, FEMA’s relief activity added to the impact of the hurricanes on prices with a larger magnitude, but did not cause an effect outside of the hurricane areas. Notably, the causal increase in prices were both localized and short-lived. We further identify that increase in competition for transportation is a more significant driving factor, for increase in prices, compared to damaged infrastructure. We provide valuable insights for shippers to formulate their emergency transportation decisions, motivate alternate procurement practices to reduce externalities while ensuring timely and economical delivery of relief supplies, and finally discuss future extensions to the modeling approach.

Keywords: Causal inference; Difference-in-differences; Disaster impact; Disaster relief distribution; Truckload market (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.tre.2025.104271

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