Construction Research Congress 2020
Quantifying Relationship between Pre-Disaster Construction Market Conditions and Post-Disaster Construction Labor Wage Fluctuations in the Gulf Coast Construction Industry
Publication: Construction Research Congress 2020: Project Management and Controls, Materials, and Contracts
ABSTRACT
The United States is one of the top five countries in the world prone to natural hazards. Natural hazards could have a significant impact on the construction industry. In a large-scale disaster, labor cost fluctuation is known to be an important driving factor in the construction cost increases. Labor cost fluctuation could increase the reconstruction cost by 20 to 50 percent after a large-scale disaster. Although the effect of disaster’s scale on construction cost has been determined in the literature, the role of construction market conditions on the post-disaster construction labor wage fluctuations has not been studied. The objective of this study is to quantify the relationship between pre-disaster construction market conditions and post-disaster construction labor wage fluctuations in the construction industry considering time dependency, using panel data models. Four commonly used construction market indicators are used within panel data models to explore this relationship. Historical county-level data of 532 counties impacted by weather-related disasters (flood, tornado, and storm) from 2014 to 2017 are collected to conduct the analysis. This study showed that there is a significant relationship between the construction employment level, construction contribution, and average weekly wage with post-disaster construction labor wage fluctuations. The results indicated that both, construction contribution, and average weekly wage have a negative effect on the labor wage increase after a natural disaster. This study helps construction companies, property owners, regulators, insurers, and cost engineers to have a better understanding of post-disaster construction cost variations aftermath of a natural disaster.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Ahmadi, N., & Shahandashti, S. M. (2018a). “Role of Predisaster Construction Market Conditions in Influencing Postdisaster Demand Surge.” Natural Hazards Review, 19(3), 04018010.
Ahmadi, N., & Shahandashti, S. M. (2018b). “Assessing the Vulnerability of Building Exterior Construction’s Labor Wages to Weather-Related Disasters in the United States.” In Construction Research Congress, 594-603.
Ashuri, B., Shahandashti, S. M., & Lu, J. (2012a). “Is the information available from historical time series data on economic, energy, and construction market variables useful to explain variations in ENR construction cost index?.” In Construction Research Congress 2012: Construction Challenges in a Flat World, 457-464.
Ashuri, B., Shahandashti, S. M., & Lu, J. (2012b). “Empirical tests for identifying leading indicators of ENR construction cost index.” Construction Management and Economics, 30(11), 917-927.
Astoul, A., Filliter, C., Mason, E., Rau-Chaplin, A., Shridhar, K., Varghese, B., & Varshney, N. (2013). “Developing and testing the automated post-event earthquake loss estimation and visualization (APE-ELEV) technique.” Bulletin of Earthquake Engineering, 11(6), 1973-2005.
Benson, C. and Twigg, J. with Rossetto, T. (2007), Tools for mainstreaming disaster risk deduction: Guidance notes for development organizations, Switzerland, ProVention Consortium.
Bureau of Labor Statistic. (2016). “QCEW Location Quotient Details.” The United States Department of Labor, Bureau of Labor Statistic, https://data.bls.gov/cew/doc/info/location_quotients.htm (Jul. 22, 2019).
Chang-Richards, Y. & Wilkinson, S. & Seville, E. & Brunsdon, D. (2017).” Effects of a major disaster on skills shortages in the construction industry Lessons learned from New Zealand.” Engineering, Construction and Architectural Management, Vol. 24 Iss 1, 2 – 20.
Cutter, S. L., & Emrich, C. (2005). “Are natural hazards and disaster losses in the US increasing?.” EOS, Transactions American Geophysical Union, 86(41), 381-389.
Döhrmann, D., Gürtler, M., Hibbeln, M. (2013). “An econometric analysis of the demand surge effect.”.
EQECAT (2005), North Atlantic Hurricane Model, EQECAT, Oakland.
FEMA. (2017). “Texas Hurricane Harvey (DR-4332).” The department of Homeland Security, Federal Emergency Management Agency, https://www.fema.gov/disaster/4332 (May. 5, 2019).
FEMA. (2016). “Louisiana Severe Storms and Flooding (DR-4277).” The department of Homeland Security, Federal Emergency Management Agency, https://www.fema.gov/disaster/4277 (May. 2, 2019).
FEMA. (2015). “Texas Severe Storms, Tornadoes, Straight-line Winds, and Flooding (DR-4223).” The department of Homeland Security, Federal Emergency Management Agency, https://www.fema.gov/disaster/4223 (May. 2, 2019).
FEMA. (2014). “Florida Severe Storms, Tornadoes, Straight-line Winds, and Flooding (DR-4177).” The department of Homeland Security, Federal Emergency Management Agency, https://www.fema.gov/disaster/4177 (May. 5, 2019).
Fenner, A. E., Razkenari, M., Hakim, H., and Kibert, C. J. (2017). “A Review of Prefabrication Benefits for Sustainable and Resilient Coastal Areas.” In Proceedings of the 6th International Network of Tropical Architecture Conference, Tropical Storms as a Setting for Adaptive Development and Architecture, Gainesville, FL, USA, 316-327.
Forder, J. (2014), Macroeconomics and the Phillips curve myth,Oxford, UK: Oxford University Press.
Friedman, M. (1968). “The role of monetary policy.” Am. Econ. Rev., 68 (1), 1–17.
Galbusera, L., & Giannopoulos, G. (2018). “On input-output economic models in disaster impact assessment.” International journal of disaster risk reduction, 30, 186-198.
Grogan, T., & Angelo, W. J. (2005). “Katrina keeps inflation roaring.” Eng. News-Rec, 255, 12-66.
Guha-Sapir, D., Vos, F., Below, R., & Ponserre, S. (2012), Annual disaster statistical review 2011: the numbers and trends, Centre for Research on the Epidemiology of Disasters (CRED).
Hallegatte, S. P. (2008). “An Adaptive Regional Input-Output Model and its Application to the Assessment of the Economic Cost of Katrina.” Society for Risk Analysis.
Hsiao, C., Mountain, D. C., & Illman, K. H. (1995). “Bayesian integration of end-use metering and conditional-demand analysis.” Journal of Business & Economic Statistics, 13(3), 315-326.
Hsiao, C. (2007). “Panel data analysis—advantages and challenges.” Test, 16(1), 1-22.
Jayaraj, A (2006), Post disaster reconstruction experience in Andhra Pradesh, in India, In: IF Research Group (Ed.): International Conference on Post-Disaster Reconstruction – Meeting Stakeholder Interests, 17-19 May 2006, Florence, Italy, The IF Research Group, Universite the Montreal.
Kunreuther, H. and Michel-Kerjan, E. (2009), At War with the Weather: Managing Large-Scale Risks in a New Era of Catastrophes, MIT Press, Cambridge.
Mueller, V. A., & Osgood, D. E. (2009). “Long-term impacts of droughts on labor markets in developing countries: evidence from Brazil.” The Journal of Development Studies, 45(10), 1651-1662.
Mueller, V., & Quisumbing, A. (2010), Short and long-term effects of the 1998 Bangladesh flood on rural wages (No. 956), International Food Policy Research Institute (IFPRI).
Olsen, A. H., Porter, K.A. (2011a), On the Contribution of Reconstruction Labor Wages and Material Prices to Demand Surge, Report No. SESM-11-1, Dept. of Civil, Environmental, and Architectural Engineering, Univ. of Colorado at Boulder, Boulder, CO.
Olsen, A. H., Porter, K.A. (2011b). “What We Know about Demand Surge: Brief Summary.” ASCE Journal of Natural Hazards Rev., 12(2), 62–71.
Olsen, A. H., Porter, K.A. (2013). “Storm surge to demand surge: exploratory study of hurricanes, labor wages, and material prices.” ASCE Journal of Natural Hazards Review.
Owen, D. & Dumashie, D. (2007), Built environment professional`s contribution to major disaster management, FIG Working Week – Strategic integration of surveying services, Organized by International Federation of Surveyors, 13-17 May 2007, Hong KongHong Kong.
Smith, S. K., & McCarty, C. (2009). “Fleeing the storm (s): An examination of evacuation behavior during Florida’s 2004 hurricane season.” Demography, 46(1), 127-145.
United Nations Development Programme, Bureau for Crisis Prevention, & Recovery. (2004), Reducing Disaster Risk: A Challenge for Development-a Global Report, United Nations.
Wooldridge, J. M. (2015), Introductory econometrics: A modern approach, Nelson Education.
Information & Authors
Information
Published In
Construction Research Congress 2020: Project Management and Controls, Materials, and Contracts
Pages: 812 - 822
Editors: David Grau, Ph.D., Arizona State University, Pingbo Tang, Ph.D., Arizona State University, and Mounir El Asmar, Ph.D., Arizona State University
ISBN (Online): 978-0-7844-8288-9
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Nov 9, 2020
Published in print: Nov 9, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.