Comparing the Economic Impact of Natural Disasters Generated by Different Input–Output Models: An Application to the 2007 Chehalis River Flood (WA)

Abstract

Due to the concentration of assets in disaster-prone zones, changes in risk landscape and in the intensity of natural events, property losses have increased considerably in recent decades. While measuring these stock damages is common practice in the literature, the assessment of economic ripple effects due to business interruption is still limited and available estimates tend to vary significantly across models. This article focuses on the most popular single-region input-output models for disaster impact evaluation. It starts with the traditional Leontief model and then compares its assumptions and results with more complex methodologies (rebalancing algorithms, the sequential interindustry model, the dynamic inoperability input-output model, and its inventory counterpart). While the estimated losses vary across models, all the figures are based on the same event, the 2007 Chehalis River flood that impacted three rural counties in Washington State. Given that the large majority of floods take place in rural areas, this article gives the practitioner a thorough review of how future events can be assessed and guidance on model selection.

Tracking an atmospheric river in a warmer climate: from water vapor to economic impacts

“…Then the net loss in local production is calculated using the Inv-DIIM. The total physical damages for Lewis, Thurston and Grays Harbor combined were estimated at USD 678 million with business disruption losses of USD 51 million (Table 3, "Base" rows), most of which was in Lewis County (Avelino and Dall'erba, 2016). While reported loss estimates are difficult to obtain, the Department of Commerce estimated that losses for the states of Washington and Oregon combined for this flooding event were approximately USD 1 billion, so our estimates for the three counties seem reasonable.…”

“…These indirect economic losses are estimated from the 2008 inputoutput tables extracted from IMPLAN at a 16-sector aggregation level (Avelino and Dall'erba, 2016). In addition to production losses, the combination of HAZUS and input-output techniques allows us to quantify how local final demand decreases as a result of the employees suffering from labor income losses due to temporary closure of their workplace.…”

“…The total economic im-pact in the three affected counties and the rest of Washington is then estimated using the Inventory-Dynamic Inoperability Input-Output Model (Inv-DIIM) proposed by Barker and Santos (2010). In relation to other available input-output models, the Inv-DIIM offers a dynamic view of inoperability and recovery processes in addition to accounting for available inventories that can alleviate disruptions in the region (Avelino and Dall'erba, 2016). The inventory data for the DIIM are based on the December 2007 inventory-to-sales ratio for manufacturing reported by the Federal Reserve Bank of St. Louis in 2016.…”

Evaluation of the moisture sources in two extreme landfalling atmospheric river events using an Eulerian WRF tracers tool

“…1a-d). Locally known as the "Great Coastal Gale of 2007", this event primarily impacted the western state of Washington, and the associated flooding resulted in approximately USD 680 million direct losses from three severely impacted counties in the state (Avelino and Dall'erba, 2016;Dominguez et al, 2017) and 11 fatalities (NOAA, 2008). Formed from the remnants of the two typhoons Hagibis and Mitag, the event produced hurricane force winds (Crout et al, 2008).…”

Advances in Spatial Risk Analysis

“…The articles of Hu, Li, Guo, van Gelder, and Shi (), Avelino and Dall'ebra (), Ouyang, Tian, Wang, Hong, and Mao (), and Trakas () examine spatial impact assessment in interconnected systems. Hu et al.…”