Browsing by Author "Arneson, Erin, advisor"

Now showing 1 - 3 of 3

Open Access
Effects of weather-related disasters on U.S. highway, street and bridge construction sector labor markets
(Colorado State University. Libraries, 2021) Shrestha, Sudip, author; Arneson, Erin, advisor; Harper, Christofer, committee member; Alves Pena, Anita, committee member
The U.S. has been experiencing the increasing effects of disasters, both in frequency and economic losses. Disaster damages to U.S. transportation infrastructure systems cause hundreds of millions in direct and indirect economic losses annually. Hundreds of miles of highways, streets and bridges are damaged every year due to severe storm events and are particularly vulnerable to flood damage. The urgency to repair and reconstruct these road networks after disasters creates a sudden demand shock for construction industry services and labor. The term demand shock is used throughout this thesis to indicate changes in the demand for labor due to exogenous factors like weather-related disasters. The researcher hypothesizes that the rapid increase in construction labor demand after disasters influences labor wages within the highway, street, and bridge construction sector (NAICS 237310) labor market. Specifically, this study proposes to answer the following research questions: RQ1: How does post-disaster labor demand shock affect the highway, street, and bridge sector? RQ2: How do State-level socioeconomic conditions influence post-disaster labor demand shock? RQ3: How can the highway, street and bridge sector anticipate post-disaster labor demand shock? This research provides the quantitative assessments of how post-disaster demand for construction services can influence labor market wages in the highway, street and bridge construction sector. Results indicate labor costs spike after disasters, information that could help local and state governments to plan for post-disaster reconstruction project costs. This research can also help contractors bidding on roads and bridge reconstruction projects to include more accurate costs for labor wages. The study of labor demand helps in assessing the current status of labor market and its capacity in supporting the post-disaster reconstruction.
Embargo
Marshall Fire's impact on Colorado housing market
(Colorado State University. Libraries, 2024) Sharma, Rukuma, author; Arneson, Erin, advisor; Valdes-Vasquez, Rodolfo, advisor; Bhattarai, Niroj, committee member
The devastation caused by wildfires not only results in the loss of human lives and property but also significantly impacts the residential housing real estate market in the United States. With the rise in urban and suburban wildfires and brushfires, as well as increased human settlement across the Wildlife Urban Interface (WUI) zone, it is imperative to analyze how wildfires in less rural areas impact the housing market. While previous studies have explored the impact of disasters on the housing market, only a few studies have focused specifically on how wildfires affect the residential housing market in the United States. Out of those, there are only limited studies about wildfires in suburban and urban communities. This research focuses on examining the aftermath of the Marshall Fire, a brushfire that occurred in a suburban region near Boulder, Colorado, in December 2021, causing damage to over 1,000 residential homes. The study investigates the impact of the Marshall Fire on the residential housing market in Colorado, aiming to achieve two primary objectives: 1) determine the extent and timing of changes in housing values following the Marshall Fire, and 2) assess how geographical proximity to the fire zone affected housing values. The study collects secondary data on the monthly housing values for Marshall Fire-affected zip codes and surrounding areas in Colorado from Zillow. Data from before and after the wildfire was analyzed to identify the extent of the impact of the Marshall Fire on home values. Results indicate a significant increase in median housing values in the fire-affected region. Housing values spiked two months post-fire, remained inflated for six months post-fire, and gradually returned to pre-fire trends after six months. Before the Marshall Fire, housing values in fire-affected zip codes consistently lagged behind surrounding and other Colorado zip codes for 14 months. Statistical tests, including paired t-tests and repeated measures ANOVA tests, indicate that the changes in housing values pre-fire and post-fire are statistically significant. The geographic proximity of a home to the Marshall Fire also played a statistically significant role in housing value changes. This surge in housing values could be attributed to supply and demand dynamics in the real estate market. The research contributes valuable insights into the effects of suburban fires on the residential housing market, aiding stakeholders in making informed decisions for the future. The study's findings offer valuable guidance for homebuyers, sellers, and the general public in predicting housing market trends in the event of similar incidents, facilitating informed decision-making.
Open Access
Modeling post-disaster permanent housing reconstruction outcomes in the U.S. using resourcing factors
(Colorado State University. Libraries, 2020) Pradhan, Srijesh, author; Arneson, Erin, advisor; Vasquez, Rodolfo Valdes, advisor; Mahmoud, Hussam N., committee member
The residential housing stock in the U.S. is vulnerable to the rising frequency of weather-related hazards, exemplified by economic losses and social disruptions caused by recent billion-dollar events. Reconstruction of damaged residential housing is essential for the swift recovery and long-term resilience of communities. However, recovery is often delayed, and the outcomes are not uniform across disaster-affected regions of the U.S. which may be attributable to unequal access to reconstruction resources. Permanent housing reconstruction in the U.S. adopts a market-driven resourcing approach which is dependent on the availability of construction and capital resources. The availability of construction resources is determined by the capacity of the regional construction market to supply labor and material resources while the availability of capital resources is determined by the socioeconomic characteristics of households and the availability of federal grants for home repairs. Under a market-driven model, the socioeconomic characteristics of households, construction industry, and the federal government constitute three core resourcing forces, composed of various resourcing factors, that influence the availability and accessibility of capital and construction resources. Although the availability of resources is crucial for reconstruction, very few studies have quantitatively examined the influence of resourcing factors on residential reconstruction outcomes at a regional scale. As geographic regions of the U.S. vary in their socioeconomic conditions and construction capacity to supply resources, the influence of resourcing factors on reconstruction outcomes may also show regional variation. However, very few studies have explored the spatially varying influence of resourcing factors on reconstruction outcomes across disaster-affected regions. Using both aspatial and spatial statistical approaches, this study performs a quantitative analysis of post-disaster permanent housing reconstruction outcomes from the lens of resource availability and accessibility. Using Ordinary Least Square regression (OLS) and Geographically Weighted Regression (GWR) models, this study seeks to: (1) quantify the global relationships between socioeconomic, construction industry, and federal government resourcing factors and post-disaster permanent housing reconstruction outcomes at a regional scale in the U.S.; and (2) explore the spatially varying local relationships between resourcing factors and reconstruction outcomes. Over 600 counties hit by federally declared weather-related hazards, with substantial residential losses, between 2007-2015 are analyzed to establish the global relationships between resourcing factors and reconstruction outcomes. The Northeast Census Region of the U.S., hit by catastrophic weather-related hazards between 2011-2012 with unprecedented residential losses, is used as a case study region to explore the spatial heterogeneity in the relationships between resourcing factors and reconstruction outcomes. Findings from the OLS model reveal that availability of construction and capital resources, measured through socioeconomic and construction industry resourcing factors, significantly influence reconstruction outcomes in disaster-hit counties across the U.S. Findings from the case study of the Northeast Census Region, analyzed through the GWR model, reveal that the relationships between resourcing factors and reconstruction outcomes showed regional variation as a result of region-specific resourcing context. The findings of this study will help emergency planners, policymakers, contractors, homeowners, and reconstruction stakeholders in resource planning, policymaking, and decision-making through the identification of critical resourcing bottlenecks and their spatially varying influence across geographical boundaries.