Storm Surge to Demand Surge: Exploratory Study of Hurricanes, Labor Wages, and Material Prices

Olsen, Anna H.

doi:10.1061/(asce)nh.1527-6996.0000111

Cited by 26 publications

(15 citation statements)

References 3 publications

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“…Thus, the production capacity can be adapted to the change in demand, and the impact on material prices is less pronounced. This finding is supported by work conducted by Olsen and Porter () and AIR (). Olsen and Porter, for example, show that correlation between wind speed, as a proxy for damage, and material prices is low.…”

Section: Hypotheses Developmentsupporting

confidence: 80%

“…However, the model results are not verified for other catastrophes. By contrast, Olsen and Porter () use a series of multilevel regressions to predict the cost changes of constructed baskets of repairs representing the total repair costs, material and labor components caused by Atlantic hurricanes. The model is based on data for nine hurricane seasons and 52 cities on the Atlantic and Gulf coasts.…”

Section: Hypotheses Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Insured Loss Inflation: How Natural Catastrophes Affect Reconstruction Costs

Döhrmann¹,

Gürtler²,

Hibbeln³

2016

J of Risk & Insurance

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. In the aftermath of a natural catastrophe, there is increased demand for skilled reconstruction labor, which leads to significant increases in reconstruction labor wages and hence insured losses. Such inflation effects are known as "Demand Surge" effects. It is important for insurance companies to properly account for these effects when calculating insurance premiums and determining economic capital. We propose an approach to quantifying the Demand Surge effect and present an econometric model for the effect that is based on 191 catastrophe events in the United States. Our model explains more than 75% of the variance of the Demand Surge effect and is thus able to identify the key drivers of the phenomenon. Terms of use: Documents inJEL classification: G22, J23, J31, Q54, R23

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Section: Hypotheses Developmentsupporting

confidence: 80%

Section: Hypotheses Developmentmentioning

confidence: 99%

Insured Loss Inflation: How Natural Catastrophes Affect Reconstruction Costs

Döhrmann¹,

Gürtler²,

Hibbeln³

2016

J of Risk & Insurance

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“…Another critical decision made by most insurers was to adopt a project management method to manage their clients’ earthquake repairs, using appointed contractors as opposed to providing cash payment. As increased building costs, or demand surge, is often a prominent feature in post-disaster environments (Olsen and Porter 2013), insurers elected this option in order to control building costs and reduce losses for themselves. In Christchurch, insurers set up their own project management offices (PMOs) through a credited contractor.…”

Section: Post-earthquake Decisionsmentioning

confidence: 99%

“…There is a need to respond quickly, using or building on existing skills, capacity and arrangements (Johnson and Olshansky 2013). The urgency to replace lost built facilities within a short timeframe often generates a surge in demand for materials and labor, resulting in higher repair or rebuild costs (Chang et al 2012, Olsen and Porter 2013).…”

Section: Introductionmentioning

confidence: 99%

An Organizational Capability Framework for Earthquake Recovery

Chang‐Richards

Wilkinson

Seville³

et al. 2017

Earthquake Spectra

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Engineering and construction capability affects the cost and pace of post-disaster recovery. An organizational capability framework for effective earthquake recovery was developed after studying longitudinally 15 engineering and construction organizations following the 2010/11 earthquakes in Christchurch, New Zealand. The longitudinal case studies, conducted from 2012 to 2015, revealed insights regarding the multitude of decisions that affected demands for engineering and construction post-earthquake, and thus the capability of organizations to meet demands. The framework presents five major challenges faced by organizations operating in an earthquake recovery environment and three core organizational capabilities required to address these challenges: disaster recovery know-how, organizational adaptive capacity to meet changing demands, and collective support among organizations. The findings offer real experience to help engineering and construction industries anticipate capability challenges and prepare for them as a business, as a sector, and as a partner with government agencies in a disaster management context.

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“…Moreover, following large-scale disasters, regional construction capacity is constrained due to excessive new demand for reconstruction. Labor shortages following disasters not only delay housing reconstruction but also result in a demand-surge of labor prices (Olsen & Porter, 2013). On the other hand, the availability of capital resources is influenced by the socioeconomic status of households and determines if homeowners have the financial capacity to purchase construction resources necessary for housing reconstruction.…”

Section: Introductionmentioning

confidence: 99%

How Construction and Capital Resource Availability Drive Regional Post-disaster Housing Reconstruction

Pradhan¹,

Arneson²

EPiC Series in Built Environment

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Natural hazards cause damages to the U.S. residential housing stock every year, and reconstruction of damaged housing is essential for the long-term community resilience. Post-disaster housing reconstruction in the U.S. is a market-driven process, influenced by the availability of construction and capital resources. Previous case studies have illustrated that housing reconstruction outcomes are uneven across different disaster-affected regions of the U.S. and may be attributable to varying availability of regional construction and capital resources. However, there is a lack of quantitative studies exploring the relationships between resourcing factors and housing reconstruction outcomes across varying geographical regions of the U.S. Using Ordinary Least Squares (OLS) regression and Geographically Weighted Regression (GWR), this study aims to: (1) quantify the relationships between pre-disaster construction and capital resource availability and post-disaster housing reconstruction outcomes at a regional scale; and (2) explore spatially varying relationships between resourcing factors and reconstruction outcomes. The Northeast census region of the U.S. is used as a case study for this research, due to unprecedented levels of residential housing disaster damages from 2011-2012. Results from the case study highlighted significant relationships between resource availability and reconstruction outcomes, and the relationships varied across the study region.

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Storm Surge to Demand Surge: Exploratory Study of Hurricanes, Labor Wages, and Material Prices

Cited by 26 publications

References 3 publications

Insured Loss Inflation: How Natural Catastrophes Affect Reconstruction Costs

Insured Loss Inflation: How Natural Catastrophes Affect Reconstruction Costs

An Organizational Capability Framework for Earthquake Recovery

How Construction and Capital Resource Availability Drive Regional Post-disaster Housing Reconstruction

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