Browsing by Author "Zahran, Sammy, committee member"

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Open Access
Addressing the religious free-rider problem via religious consumption signaling and religious capital accumulation
(Colorado State University. Libraries, 2012) Simpson, Jason J., author; Bernasek, Alexandra, advisor; Zahran, Sammy, committee member; Dickinson, Greg, committee member
The aim of this paper is to investigate and illustrate the religious free-rider problem within church congregations while investigating religious consumption signaling patterns and the ability, or lack thereof, to form religious capital. From an institutional perspective, this paper will address stigma-screening processes via three economic models in an effort to understand and evaluate the overall effectiveness of institutional responses towards free-riding members. In addition, this paper will explore incentives behind perverse consumption signaling as a method of communicating membership, as well as the overall impact of restricting religious capital accumulation for both members and free-riders alike.
Open Access
An analysis of housing values and national flood insurance reform under the Biggert-Waters Act of 2012
(Colorado State University. Libraries, 2015) Villar, Daniel Clark, author; Goemans, Christopher, advisor; Suter, Jordan, committee member; Zahran, Sammy, committee member
Previous research has shown that both flood risk and insurance premiums are capitalized in housing values. This paper examines the effect of National Flood Insurance Program reform implemented by the Biggert Waters Act of 2012 and the Homeowners Flood Insurance Affordability Act of 2014 on housing values over a three-and-a-half year time period. It is hypothesized that the effects of increasing flood insurance rates through the elimination of established subsidies was capitalized in home values resulting in a loss of value in areas where subsidies are maintained. The paper presents a hedonic price difference-in-difference OLS model which is then tested for flexibility to the policy period and robustness to the treatment group. The evidence indicates that (1) housing values trend differently for areas with subsidies than areas without and (2) that this effect is correlated with flood insurance reform periods and robust to the definition of the treatment group. I conclude that the Biggert-Waters Act had a negative impact on median home values for areas with subsidized policies.
Open Access
Elderly migration and natural disasters in the United States from 1960 to 2010
(Colorado State University. Libraries, 2015) Boyne, John R., author; Lacy, Michael, advisor; Peek, Lori, advisor; Zahran, Sammy, committee member
The United States is a rapidly aging society. As a larger proportion of the population enters into the retirement years, it is likely that a larger portion of the nation's migrants will be elderly. Over the last four decades, natural disasters have also been increasing in frequency and scale across the United States. This thesis draws together two different data sets in order to test the relationship between the two variables, elderly migration and natural disaster loss. The purpose of this thesis is to examine whether migration patterns among the elderly are influenced by natural disaster risk across the country. After a brief introduction, the thesis offers a review of the literature regarding elderly migration in the United States and an exploration of the particular vulnerabilities that the elderly face before, during, and after natural disasters. Then, the thesis reviews the relationship between migration and natural disasters, specifically focusing on climate change, economic development, and amenities. Natural disaster data ranged from 1960 to 2000 and elderly migration data ranged from 1970 to 2010. A fixed effects panel regression model was used to measure the effect natural disaster damage on elderly migration patterns at the county level. The previous decade's disaster damage data was measured against the following decade's elderly migration patterns. The analysis showed statistical significance between several of the variables but little substantive effect between natural disaster damage and elderly migration across the United States measuring across multiple variables of natural disaster data including per capita damage, number of events experienced and number of extreme events experienced. As the elderly continue to comprise a larger proportion of the population and as migration rates continue to rise among this age group, an understanding of the unique relationship between this age group and the risk of natural disasters will help at-risk communities more effectively prepare for extreme events. Although there are limitations to this project, the research contributes to the emerging research field of elderly migration and natural disaster vulnerability.
Open Access
Essays on local economic development and social capital
(Colorado State University. Libraries, 2024) Poerbonegoro, Anna Farina, author; Weiler, Stephan, advisor; Alves Pena, Anita, advisor; Zahran, Sammy, committee member; Suter, Jordan, committee member
Creative Sector activities and social capital are interconnected in the same spectrum of local economic development, even though is not always immediately apparent. The two are related in that social capital is a product of, and simultaneously a determinant for, the Creative Sector. The three essays in this dissertation address each component separately. The first two essays examine the Creative Sector, and the third focuses on social capital. Motivated by the increasing role of the role of Creative Sector as growth driver and the economic base approach, in Chapter 1 titled Role of Creative Initiatives in Economic Performance: Case Study on Colorado's Creative Districts and Main Street Communities I examine the influence of Colorado's place-based initiative / policy on economic performance. Two dependent variables are chosen to represent performance, namely Business Establishments and Net Job Creation. In addition, sectoral employment (the Creative Sector and NAICS sector 71 (Arts, Entertainment and Recreation) and employment in sectors outside of the two) are examined as a supplement; for the placed-based policy, Creative District Certification program and the Main Street Communities program are selected, along with a set of control variables and a set of interaction terms that signify co-existence of the two policies in any particular county. The data used in estimation is a panel dataset for Colorado's 64 counties in a ten-year period (2010 – 2019). Results indicate that both place-based initiatives affect business establishments but not their birth rates, but each influence is opposite direction; co-location of the two is also playing a role, which is positive in Urban areas but negative in Rural areas. Job creation is positively influenced by the MS Communities program in the Rural region but not by Creative District certification program. Creative Sector employment is slightly negatively influenced by the initiatives; in contrast, they do not influence employment in either Sector 71 or Other Sectors. The results suggest that the two initiatives are beneficial, but each for different types of counties. Chapter 2, titled Sectoral Employment Spillover in Colorado, focuses on spatial spillover effects of employment in two leading industrial sectors – namely the Arts, Recreation and Entertainment (NAICS 71 or Sector 71) and the Creative Sectors – on employment in Other Sectors in Colorado, based on the Economic Base Theory. The analysis is performed using county-level Quarterly Census of Employment and Wages (QCEW) data. The study aims at answering the question of whether sectoral employment in one county affects that in a neighboring county (in other words, whether spatial correlation exists). Moreover, the analysis also examines how sectoral employment (Creative Sector and Sector 71) in one county influences employment in sectors outside the two, in different counties; this is the employment spillover question. Two variations of model specifications are tested, examined spatially and non-spatially, using lagged variables in one model and lagged log variables in another. The result suggests that overall, the two sectoral employments do influence Other Employment, but the spatial spillover is not detected. More specifically, the Creative Sector is negatively associated with the next period's employment in Other Sectors in both models. However, the significance of Sector 71 employment's relationship with employment in Other Sectors depends on how it is modeled. Social Capital is discussed in Chapter 3, County Level Social Capital in Colorado. While social capital is acknowledged as being a fuzzy concept, it embeds both demand and supply side within itself. While the demand side typically addresses how social capital affects other dimensions in economics, Chapter 3 here focuses on the supply side, by inquiring how social capital at county level in Colorado is affected by various socio-economic aspects. The discussion covers various standpoints of social capital contexts and definitions that are indicative of the fuzziness of the concept itself. Empirically, I employ a quantitative measure of social capital in the form of an index portraying civic participation (developed by Rupasingha et al. (2006)). A short panel regression was performed using a series of explanatory variables (physical infrastructure, poverty, unemployment, personal and regional incomes, education, and an economic recession). The results indicate that poverty and economic shock have the tendency to reduce social capital in Colorado in the form of civic engagement particularly in Urban regions, while larger pool of the unemployed in the society indicates a positive relationship with civic participation. Physical infrastructure, proxied by new housing permits, is negatively associated with civic participation in all three regions.
Open Access
Essays on the economics of natural disasters
(Colorado State University. Libraries, 2020) Hu, Yuchen, author; Cutler, Harvey, advisor; Zahran, Sammy, committee member; Mushinski, David, committee member; van de Lindt, John, committee member
Natural hazards occur frequently, and the costs associated with these events are well into the billions of dollars. The rising frequency and costs from natural disasters require a comprehensive understanding of its impacts on the economic system and mitigation strategies for local communities that can minimize these losses. The purpose of Chapter 1 is to demonstrate a linkage between civil engineering and economic models to accomplish these objectives. To do this, I build a spatial computable general equilibrium model (SCGE) for Shelby County in Tennessee that requires an extensive data set dependent upon eight different data sources. I then develop advanced methods that integrate simulation models from engineering and economics. Civil engineers have created a range of simulation models that estimates the impact of a hypothetical earthquake on damages to buildings, utilities, and transportation network. These damages are integrated into the SCGE model to simulate a range of economic outcomes. I find that the SCGE model is more advanced in capturing the adjustment behaviors of businesses and households to external shocks compared to previous attempts. I also find that to better estimate the economic impacts, we need to simulate the model with the three types of physical damages jointly and not individually. Chapter 2 investigates a hidden layer of the impact of natural disasters, which is the spillover effect due to disaster-induced migration on the receiving areas' labor markets. Using the difference in difference approach, I empirically compare the hourly wage rates in areas that received the evacuees from Hurricane Katrina to areas that didn't. I find that in the export-oriented industry, the inflow of migrants due to Katrina slightly reduces the hourly wage rates for both the low and the high-skilled workers. However, in the localized industries where the inflow of the migrants also increased the demand for local goods and services, the inflow of evacuees raises the hourly wage rates the high-skilled workers and imposes no significant impacts for the low-skilled workers. These results are consistent with previous literature in that immigrants did impact the local labor markets but at a small magnitude. Chapter 3 proposes the setup of a Rainy-Day Fund (RDF) through tax increase/hikes for local governments in preparing for external shocks in the future. To minimize the costs of tax hikes to the economy and achieve the target amount of RDF, I use the SCGE model developed in Chapter 1 to solve for an optimal path of tax hikes over time. The process starts with an endogenized cost function measured by the foregone output that could be produced had there been no changes in the tax system. Built on the profit and utility maximization in response to changes in taxes, the cost function expands the theoretical setup of Barro (1979) and Ghosh (1995) by allowing any factors that influence the output to enter the optimization process. Moreover, the cost function in any period depends on not only the tax rates in that period but also the tax rates in previous periods, since any changes to the tax rates previously can influence the current economy through changes in investment and capital. I find that the optimal trajectory of the tax hikes tends to be rising in time. The rate of the increase depends on the magnitude of labor supply elasticity to real wages, and the interest of the regional planners to include economic outcomes beyond the planning horizon.
Open Access
Fragility approach for performance-based design in fluid-structure interaction problems, Part I: Wind and wind turbines, Part II: Waves and elevated coastal structures
(Colorado State University. Libraries, 2016) Do, Trung Quang, author; van de Lindt, John W., advisor; Heyliger, Paul R., committee member; Mahmoud, Hussam N., committee member; Zahran, Sammy, committee member
This dissertation focuses on a methodology for performance-based design using fragilities in fluid-structures interaction problems. Two types of fluid-structure interaction problems are investigated in this dissertation: Part I: wind-structure interaction (for wind turbine tower-base fatigue), and Part II: wave-structure interaction (for elevated coastal structures subjected to shear and uplift loading). The first problem type focuses on performance-based design of a wind turbine tower base connection subjected to wind loading using a fatigue limit state. A finite element model for wind turbines is subjected to nonlinear wind loading in the time domain. The relative motion of the actual wind speed and velocity of the moving blades in the along-wind direction creates force nonlinearity for the applied wind load, and hence, necessitates a fluid-structure interaction model. Then, a model for fatigue assessment including crack propagation was developed for the tower base connection. The inclusion of crack propagation is expected to extend the service life of the tower compared to conventional fatigue life analysis using the characteristic S-N approach. By varying the tower thickness, diameter, and considering predefined levels of crack propagation, fragility curves based on a fatigue life limit state are developed for the application of performance-based design. The desired fatigue life of a wind turbine tower for different wind sites can be obtained based on the fragilities. Finally, an illustrative example of performance-based design for a typical 5-MW wind turbine throughout Colorado is used as an illustrative example in this study. The second type of problem focuses on development of a performance-based design methodology for elevated coastal structures such as bridges and buildings. Initial numerical results are compared to existing data from a large-scale bridge section test and a full-scale transverse wood wall tested previously at the O.H. Hinsdale Wave Research Laboratory at Oregon State University. These validations provide the foundation for developing a method of wave generation for interaction with bridge and building models. By introducing fragility modeling, a variety of design options can be considered consisting of either raising the elevation of the bridge or strengthening the structure itself in order to obtain the desired probability of failure for a specified of hurricane surge and wave intensity.
Open Access
From revolutions to realities: an empirical investigation of the Arab Spring's consequences
(Colorado State University. Libraries, 2023) Muktad, Abdalla, author; Miller, Ray, advisor; Tavani, Daniele, committee member; Zahran, Sammy, committee member; Çavdar, Gamze, committee member
With the irrevocable change in the Arab world over the last decade, fully understanding the economic and political impact of the Arab Spring is paramount for policymakers. This dissertation consists of three empirical essays on the Arab Spring which attempt to capture causal relationships between Arab Spring and some political and economic factors. Exogenous shocks such as the experiences of revolution are treated as natural experiments which minimize problems of endogeneity and selection. Therefore, these essays are analyzed based on the synthetic control method and synthetic difference-in-differences. The first essay concerns the impact of the Arab Spring on economic growth, corruption and democracy. I focused on Tunisia and Libya as a case study of Arab Spring countries using the synthetic control method (SCM). I found that there was a negative impact of the Arab Spring on economic growth after 2010 for both Tunisia and Libya. On the other hand, the results suggested that although there was a substantial increase in democracy after the Arab Spring for both Tunisia and Libya, democracy sharply decreased in 2015 in Libya due to armed conflict. Surprisingly, the results showed that there was a substantial increase in corruption in both Libya and Tunisia after the Arab Spring. In the second essay, I estimated the Arab Spring's impact on foreign aid by using the synthetic difference-in-difference method. I examine whether the Arab Spring affects the distribution of foreign aid. I argue that the conflict may respond differently to different types of aid because of the objectives and aid-giving motives. The results indicate that, following the Arab Spring, there was a general increase in total foreign aid to affected countries, with exceptions for certain donors and a stronger increase for "non-traditional Western allies," with the United States being the largest contributor. Also, the findings suggest that, following the Arab Spring, various donors increased foreign aid to affected nations, particularly in government and civil society support, as well as humanitarian aid, with the United States focusing on government and civil society aid in Tunisia, Libya, and Syria, European countries emphasizing government and civil society aid in Libya and Tunisia, and Multilateral aid generally increasing, except for government and civil society aid in Yemen. In the third essay, I studied the spillover effect of the Arab Spring by investigating its influence on nearby countries concerning economic growth, bilateral trade, and foreign direct investment. I aimed to address how proximity to Arab Spring countries impacts the economic growth, bilateral trade, and foreign direct investment of neighboring economies. The results found that countries located within 2000 kilometers of Arab Spring nations experienced a significant negative impact on both real GDP and net inflow of foreign direct investment (FDI). However, the negative effects on bilateral trade were not statistically significant, suggesting that engaging in trade with Arab Spring countries did not necessarily harm the economic growth of neighboring countries.
Open Access
Impacts of flooding on the rice production of Bangladesh: a panel data study
(Colorado State University. Libraries, 2019) Hassan, S. M. Kamrul, author; Kling, Robert, advisor; Zahran, Sammy, committee member; Bayhem, Jude, committee member
This paper attempts to measure the impact of flooding on rice production in Bangladesh by using two versions of econometric model, namely a total production model and a yield model. The production model uses tons of production as the dependent variable while the yield model uses the log of yield which has been defined as tons per acre. The findings from the production model suggest the vulnerability of the boro variety of rice, as it appears to have meaningful coefficients with flood damage indicator variables. The spatial dimensions of vulnerability become apparent as some districts appear to have more damaging impacts on several varieties of rice even while the national level estimates do not reveal the fact. But with both negative and positive flooding effects, the overall trend of rice production signifies the resilience and development achieved in this sector. The yield model uses similar variables to the production model, but normalizes them and drops some control due to the presence of multicollinearity. But while this second model has theoretically appealing attributes, the findings are not meaningful or significant as only one of the concerned variables gives the expected effects signs. This puts a caution in the transformation of the variables used in panel data regression.
Open Access
Integrated decision-making for urban raw water supply in developing countries
(Colorado State University. Libraries, 2011) Soentoro, Edy Anto, author; Grigg, Neil S., advisor; Fontane, Darrell G., committee member; Vlachos, Evan C., committee member; Zahran, Sammy, committee member
Rapid urbanization and development are causing severe problems of raw water extraction and related environmental and social impacts in developing countries. This study demonstrated that an integrated approach to decision making could help solve these problems. A case study of raw water management in the region of Jabotabek, Indonesia, which is in and around Jakarta, exhibited social and environmental problems including land-subsidence. The integrated approach was applied in a simulated planning process for raw water development, to include consideration of the economic, environmental and social demands, the hydrological system, and the institutional systems that exist in particular areas. Simulation and optimization techniques (Supply_sim model) were used to determine the planned water allocation for a series of demand clusters for a suite of alternatives and development strategies. A multi-criteria decision analysis (MCDA) based on a decision support system (DSS) was used as an Integrated Decision-Making model to analyze the important and related aspects as one integrated system and to find the best set of decision options. The overall result of the study showed that the integrated approach could improve the decision process to solve the problem. However, its success ultimately depends on the political will of the government to apply the approach. The government needs to improve coordination among the institutions related to raw water supply development and to carry out a transparent decision-making process. Regulations on land-use planning, groundwater abstraction and water pollution control should be applied strictly and aimed to maintain raw water sources. The study also showed that a decision process tool such as the DSS within an integrated framework of decision making could help decision makers to reach consensus and gain stakeholder participation, accountability and commitment to the decision being made. In dealing with complex raw water problems in large cities, the study also showed that planning systems could help decision makers to think systematically to improve the decision results.
Open Access
Integration of graphical, physics-based, and machine learning methods for assessment of impact and recovery of the built environment from wind hazards
(Colorado State University. Libraries, 2019) Pilkington, Stephanie F., author; Mahmoud, Hussam, advisor; Ellingwood, Bruce, committee member; van de Lindt, John, committee member; Zahran, Sammy, committee member; McAllister, Therese, committee member; Hamideh, Sara, committee member
The interaction between a natural hazard and a community has the potential to result in a natural disaster with substantial socio-economic losses. In order to minimize disaster impacts, researchers have been improving building codes and exploring further concepts of community resilience. Community resilience refers to a community's ability to absorb a hazard (minimize impacts) and "bounce back" afterwards (quick recovery time). Therefore, the two main components in modeling resilience are: the initial impact and subsequent recovery time. With respect to a community's building stock, this entails the building damage state sustained and how long it takes to repair and reoccupy that building. In modeling these concepts, probabilistic and physics-based methods have been the traditional approach. With advancements in artificial intelligence and machine learning, as well as data availability, it may be possible to model impact and recovery differently. Most current methods are highly constrained by their topic area, for example a damage state focuses on structural loading and resistance, while social vulnerability independently focus on certain social demographics. These models currently perform independently and are then aggregated together, but with the complex connectivity available through machine learning, structural and social characteristics may be combined simultaneously in one network model. The popularity of machine learning predictive modeling across multiple different applications has risen due to the benefit of modeling complex networks and perhaps identifying critical variables that were previously unknown, or the mechanism behind how these variables interacted within the predictive problem being modeled. The research presented herein outlines a method of using artificial neural networks to model building damage and recovery times. The incorporation of graph theory to analyze the resulting models also provides insight into the "black box" of artificial intelligence and the interaction of socio-technical parameters within the concept of community resilience. The subsequent neural network models are then verified through hindcasting the 2011 Joplin tornado for individual building damage and the time it took to repair and reoccupy each building. The results of this research show viability for using these methods to model damage, but more research work may be needed to model recovery at the same level of accuracy as damage. It is therefore recommended that artificial neural networks be primarily used for problems where the variables are well known but their interactions are not as easily understood or modeled. The graphical analysis also reveals an importance of social parameters across all points in the resilience process, while the structural components remain mostly important in determining the initial impact. Final importance factors are determined for each of the variables evaluated herein. It is suggested moving forward, that modeling approaches consider integrating how a community interacts with its infrastructure, since the human components are what make a natural hazard a disaster, and tracing artificial neural network connections may provide a starting point for such integration into current traditional modeling approaches.
Open Access
Longitudinal and geographic analysis of the relationship between natural disasters and crime in the United States
(Colorado State University. Libraries, 2012) Prelog, Andrew J., author; O'Connor Shelley, Tara, advisor; Peek, Lori, advisor; Hogan, Michael, committee member; Zahran, Sammy, committee member
Natural disasters and crime are ubiquitous in the United States. The public generally views the social disorder associated with disaster events as criminogenic--that is, disasters somehow foster opportunistic criminal behavior. Scientific investigation into the relationship between disaster and crime is more nuanced--and at times has produced contradictory and inconsistent findings. This dissertation research explores the relationship between disaster and crime in the continental United States to investigate the question of whether disasters of different magnitudes and/or types differentially affect crime rates. I employ three sociological theories to inform the analyses. First, sociology of disaster researchers, using the therapeutic community hypothesis, have long asserted that disasters reduce criminal activity both during and after the event. Second, criminologists using social disorganization theory assert that disaster may increase the likelihood and occurrence of crime. Third, researchers using routine activity theory suggest that disaster may increase or decrease criminal activity, depending on how a disaster restructures formal and informal mechanisms of social control, and criminal opportunity. To investigate this question, I use geographic and longitudinal analyses of 14 years of county-level data on socio-demographic predictors of crime, crime rates, and disaster impacts. I statistically model 11 different categories of crime and impacts from 12 different disaster types using geographic information systems, hierarchical linear modeling, and geographically weighted regression. In general, findings indicate that higher crime rates are associated with larger disaster magnitudes. The effect is not consistent for all categories of crime investigated in this research. Findings also indicate that certain types of disasters have a differential effect on crime outcomes, independent of disaster magnitude. This research and results represent the first county-level geographic and longitudinal analysis of disaster and crime for the United States.
Open Access
Making ends meet in a social context: grandparent childcare during the 2008 recession, debt of the poor and financial innovation, and relative poverty's effect on election outcomes
(Colorado State University. Libraries, 2018) Roberts, Michael, author; Pena, Anita, advisor; Weiler, Stephan, committee member; Zahran, Sammy, committee member; Kroll, Stephan, committee member; Pressman, Steven, committee member
The chapters illustrate dynamics of the choices of individuals and households when facing income and time constraints in the recent United States. In the first chapter, grandparent childcare provision is studied from the supply side with a focus on the effect of the 2008 recession. Findings suggest differing effects for lower income respondents, and female respondents. In the second essay, I test a structural consumption model building on Brown (2007) and extending into recent periods using newly available data. Results suggest that Minskian effects are present in consumption in the U.S. Lastly, I test a new relative poverty measure against the more traditional form and study its relation to electoral outcomes from 2000-2016. Results suggest that state-level relative poverty decreases the likelihood of Republican victories. All of these aspects investigate the relationship between the social and the economic in the modern U.S.
Open Access
Quantification of performance, damage, and risk to light wood frame buildings subjected to tornadoes and expansive soils
(Colorado State University. Libraries, 2017) Maloney, Timothy D., author; Mahmoud, Hussam N., advisor; Ellingwood, Bruce R., advisor; van de Lindt, John W., committee member; Zahran, Sammy, committee member
Each year, damage to infrastructure caused by the uncorrelated hazards of tornadoes and expansive soils is on the order of billions of dollars. The monetary losses caused by each hazard alone are reason for concern. For tornados, however, the impact can be devastating and extend beyond monetary loss. Furthermore, the presence of expansive soils can exacerbate life-safety concerns during a tornado by limiting construction of underground shelters such as basements. It is not uncommon for communities to be crippled by damage to critical infrastructure such as businesses, homes, utility networks, and emergency facilities. This destruction can limit a community's ability to support its population in the short-term which can lead to significant outmigration that may be difficulty to recover from. The ability of a community to plan for and recover from such hazards is referred to as community resilience. The major goal of this research is to contribute to the development of a set of standards and guidelines for resilient community design. Specifically, this study aims to link the performance of individual building components to building system performance, so that the effect of implementing a change in standard construction techniques (i.e. recommending that homes be constructed with hurricane clips) can be quantified. The work herein focuses on light wood frame residential buildings constructed with methods typical in the American heartland. The research approach taken herein was to develop detailed finite element (FE) models to capture building system performance and individual building component behavior under expansive soil and tornado loading. The level of detail used in the FE models allows the interaction between building components to be captured to a higher degree than previously possible. Knowledge of the demand on building components gained from the FE analysis was then applied to perform statistical analysis to quantify the performance of several building archetypes chosen to represent the residential building portfolio in a typical community located in the US heartland. The performance of the typical archetypes was then analyzed to identify deficient building components and compared to target resilience performance levels provided by research partners at the University of Oklahoma. The effect of implementing various improved construction techniques was then examined in an effort to meet the resilience performance targets. This study revealed that, typically, light wood frame residential construction that is common in tornado prone areas of the U.S. is not sufficient to meet the resiliency goals considered in this study. This is unsurprising considering the historical lack of consideration given to tornado hazards in U.S. design codes and standards. Similarly, it was found that typical masonry block basement wall construction was insufficient to withstand loading from expansive soils without sustaining damage. This is also not surprising because many people in expansive soil prone areas choose to forgo constructing basements due to the likelihood of damage. The study also revealed, however, that resilience target performance levels can be achieved using existing construction techniques. This suggests that resilient community design is a goal that is already within reach at the current state of the art.
Open Access
Resilience of healthcare and education networks and their interactions following major earthquakes
(Colorado State University. Libraries, 2021) Hassan, Emad Mohamed Shafik, author; Mahmoud, Hussam N., advisor; Ellingwood, Bruce R., committee member; van de Lindt, John W., committee member; Zahran, Sammy, committee member; McCabe, Steven, committee member; Cerato, Amy, committee member
Healthcare and education systems have been identified by various national and international organizations as the main pillars of communities' stability. Ensuring the continuation of vital community services such as healthcare and education is critical for minimizing social losses after extreme events. A shortage of healthcare services could have catastrophic short-term and long-term effects on a community including an increase in morbidity and mortality, as well as population outmigration. Moreover, a shortage or lack of facilities for K-12 education, including elementary, middle, and high schools could impact a wide range of the community's population and could lead to impact population outmigration. Despite their importance to communities, there are a lack of comprehensive models that can be used to quantify recovery of functionalities of healthcare systems and schools following natural disasters. In addition to capturing the recovery of functionality, understanding the correlation between these main social services institutions is critical to determining the welfare of communities following natural disasters. Although hospitals and schools are key indicators of the stability of community social services, no studies to date have been conducted to determine the level of interdependence between hospitals and schools and their collective influence on their recoveries following extreme events. In this study, comprehensive frameworks are devised for estimating the losses, functionality, and recovery of healthcare and educational services following earthquakes. Success trees and semi-Markov stochastic models coupled with dynamic optimization are used to develop socio-technical models that describe functionalities and restorations of the facilities providing these services, by integrating the physical infrastructure, the supplies, and the people who operate and use these facilities. New frameworks are proposed to simulate processes such as patient demand on hospitals, hospitals' interaction, student enrollment, and school administration as well as different decisions and mitigation strategies applied by hospitals and schools while considering the disturbance imposed by earthquake events on these processes. The complex interaction between healthcare and education networks is captured using a new agent-based model which has been developed in the context of the communities' physical, social, and economic sectors that affect overall recovery. This model is employed to simulate the functional processes within each facility while optimizing their recovery trajectories after earthquake occurrence. The results highlight significant interdependencies between hospitals and schools, including direct and indirect relationships, suggesting the need for collective coupling of their recovery to achieve full functionality of either of the two systems following natural disasters. Recognizing this high level of interdependence, a social services stability index is then established which can be used by policymakers and community leaders to quantify the impact of healthcare and educational services on community resilience and social services stability.
Open Access
Suicide mortality, economics and subgroup segregation
(Colorado State University. Libraries, 2020) Briggs, Thomas, author; Pena, Anita Alves, advisor; Bernasek, Alexandra, advisor; Zahran, Sammy, committee member; Canetto, Silvia, committee member
In the United States, suicide is typically theorized as an individual act, and as symptom of a mental disorder. However, evidence shows that those who die of suicide (e.g., by sex, race) varies depending on cultural, social and economic factors. Research on the contexts of suicide has been marked by several limitations, including a tendency to analyze social and economic factors separately, and also a disregard for the combined role of sex and ethnicity in the relationship between social and economic factors and suicide. This study compares current statistics with past research and offers a different methodology in the estimation and model construction of the socioeconomic determinants of suicide. By examining the association between social and economic indicators and suicide among African descent men and women, as compared to European descent men and women in the United States, this study isolates the impact of business cycle fluctuations (as indicated by the unemployment rate) on socioeconomic flows in marital, educational and age groups. The first chapter compares previous research on suicide mortality conducted in Ruhm, (2000) over business cycles by exploiting socioeconomic data from 2005-2012. Using detailed suicide mortality data, I observe that previous trends in state level suicide determination via the unemployment rate, hold over this time period. My research also expands upon Ruhm (2000) by accounting for race and gender specific socioeconomic means and suicide rates, I determine that the strong correlation between the unemployment rate and the suicide rate, only holds for whites, in particular white males. The association is insignificant for every other demographic at the state level. I also estimated the association at the county level. In a comparison of the regions, county level aggregates found significance for each subgroup. A significant and negative association was found for blacks and significant and positive for whites. These results suggest that the detrimental effects of unemployment (alone) only affects whites, although the mechanism that increases suicide for blacks could be through other socioeconomic variables that are themselves impacted by the unemployment rate. The findings imply that the modeling technique used in previous research is not sufficient to obtain the appropriate results for every demographic subgroup or subregion. The second chapter studies the impact of socioeconomic status variables such as marital status, educational attainment, income level and inequality on the suicide count as well as regional controls on gun ownership and level of unemployment insurance. This section employs a zero-inflated negative binomial model, with modification for panel data. Results indicated that unemployment was significantly positive only for white males. Marriage has a significant and negative impact on every demographic subgroup with the exception of black females. The impact of inequality on black males and females was much more positive and significant by magnitude than that for white males and females. These findings suggest inequality as a significant factor on suicide during economic downturns, especially for blacks. Furthermore, these results suggest that business cycle fluctuations impact the black suicide rate through inequality thus, not through unemployment directly. The third chapter addresses economic frustration as a reason for the notable increase in suicide rates, particularly amongst poor whites. It is argued that the externalization of economic frustration by poor whites once led to homicide of blacks. Through changing social norms and penal consequences current economic and social frustration is internalized and leads to increased morbidity and suicide mortality in whites. I refer to the past perspective of one of the most influential black leaders, W.E.B. Dubois. I also provide a history of economic violence and analyze current phenomena using the philosophies of Dubois and add further evidence of the current state of affairs offered by Jonathan Metzl. Together these chapters suggest an alternative reasoning for increased suicide mortality in the U.S. As demonstrated, the current etiology does not universally account for the socioeconomic determinants of suicide mortality in the United States by subgroup or subregion. Furthermore, there has been s substantial disregard for the cultural changes in America that may account for rising suicide mortality in America, such as racial/ethnic saturation and the internalization of economic frustration in economic analysis.
Open Access
The role of urbanization in resilience of communities under flood risk
(Colorado State University. Libraries, 2021) Hemmati, Mona, author; Mahmoud, Hussam N., advisor; Ellingwood, Bruce R., advisor; Crooks, Andrew T., committee member; Zahran, Sammy, committee member
Flood risk is on the rise worldwide due to climate change and urbanization. Although urbanization has a significant role in placing the lives and livelihoods of people at flood risk, it has received less attention in comparison to climate change. Urbanization is expected to increase in the future; based on a report by the United Nations, 68% of the world population is expected to live in urban areas by 2050 compared to 50% in 2020. Perceptions of economic opportunity, accessibility to recreational facilities, and agricultural development have made floodplains and coastal areas desirable places to live. The nature of the risk brought about by urbanization in flood-prone areas must be thoroughly understood to develop effective policies for mitigating risk in rapidly growing flood-prone communities. This dissertation aims at understanding the effect of urbanization on future flood risk and how policymakers can integrate nonstructural flood mitigation measures, in terms of urban planning policies and socioeconomic incentives, in their urban development plans to help future communities move toward resilience. We begin by conducting a comprehensive literature review of how current studies have tackled the impact of urbanization on hazard and exposure components of flood risk through alternative policies. Since urban development plans are among the most influential factors in shaping the growth of a community over time, we evaluate these studies through the lens of how effective these policies have been in controlling the flood consequences. In this first step, we also identify some of the gaps and challenges in current flood risk mitigation planning and suggest a path forward, which will be considered in the upcoming sections of this dissertation. Next, we introduce a new approach to assess the effect of urbanization on future flood risk. The objectives of this step are to: (1) establish a framework for flood risk assessment to account for the impact of urbanization on flood risk; (2) develop a spatial model for simulating the growth of a community over time, considering geographical, physical, social, and economic factors associated with urbanization; and (3) evaluate the role of land-use policies and socioeconomic incentives, such as acquisition, zoning, and taxation in mitigating flood consequences. We believe that this methodology could be used to assist city planners and stakeholders in examining tradeoffs between costs and benefits of future land development, considering uncertainties in flood hazards, the performance of the built environment, and population and economic growth. Finally, we demonstrate how changes in human behavior affect urbanization and flood risk. To do so, we show how human behavior impacts urbanization by modeling the principal agents and their interactions that lead to changes in the urban expansion of a community over time. We evaluate how the risk perception of households affects their decision as to where to locate. Then, we investigate the driving factors and incentives in human decision-making on locational choices and how these incentives can be adopted by local authorities and policymakers as nonstructural flood mitigation measures to shape urbanization and to achieve resilient and sustainable development of urban communities.
Open Access
Three essays in cultivating regional growth: brownfields and charter schools
(Colorado State University. Libraries, 2023) Trouw, Michael Frans, author; Weiler, Stephan, advisor; Pena, Anita Alves, committee member; Zahran, Sammy, committee member; Lopes, Tobin, committee member
This dissertation is comprised of three chapters focused on two important factors in cultivating regional growth. The first factor considered in chapter one is potential barriers to contaminated land reuse. As cities and towns grow, over time the stock of land within an area can be impacted by prior land use. A property which currently has a contamination issue from prior use which must be remedied before the land may be used in the future, whether for production or settlement, is called a brownfield. In this chapter we employ a survey of real estate professionals, and find developers require an additional risk premium on top of their normal rate of return on investment to incentivize them to invest in a brownfield. Importantly, this risk premium is found to be in excess of cleanup costs. Informed by the results of the survey analysis, a theoretical framework is used to explore the implications of this risk premium. We show this risk premium generated by information asymmetries potentially leads to inefficiency in the market for real estate and can perpetuate a cycle of underdevelopment due to a first mover problem. The redevelopment of this land is important, as these brownfield properties are typically located in the urban core of cities and towns and if not remediated can leave potentially productive swaths of land fenced off while expansion occurs in a sprawling manner on the fringes. The second factor in cultivating regional growth considered in chapters two and three of this dissertation is the role of educational alternatives. Specifically, I focus on the determinants of charter school formation and growth. Education quality and availability has been shown to be important in determining economic growth and migration patterns. Specifically, a strong education system can be viewed as an amenity to households and firms debating moving to a particular locale. Charter schools are publicly funded, privately run institutions crafted first as a pilot program for innovation, and more recently as a substitute or competitor for public schools. While the efficacy of charter schools has been heavily researched and remains controversial, little work has focused on the determinants of demand for the schools themselves. Chapter two builds on a small existing literature to provide light on what factors outside of direct measures of educational quality affect the creation rate of charter schools. Using a panel of core based statistical areas over the period 2006-2015, this analysis finds evidence that the composition of industry within a Core Based Statistical Area is related to the rate at which new charter schools are created, with more technical employment associated with a greater demand for alternative school options. The connection between industry and charter school creation is further explored by measuring the impact of intra-industry entrepreneurship on charter school proliferation, where findings suggest that higher levels of entrepreneurship within an CBSA is correlated with a higher charter school formation rate. Chapter three further explores the connection between charter schools and their interconnectivity with the broader economy. Posed as a method of returning education to the private market, charter schools are considered to be more exposed to market conditions, potentially more nimble to changing conditions and methodologies, but also potentially functioning in a more volatile market where school closings can occur more easily. This chapter uses the impact of the 2007 financial crisis to determine if charter schools were impacted differently than public schools. Using a nationally representative sample and aggregating to the Core Based Statistical Area, I find both traditional public and charter schools experienced small decreases in revenue but were largely sheltered from recessionary forces due to Federal intervention. Using a difference-in-differences approach I find that charter schools experienced both an increased rate of openings and an increase in the stock during the Great Recession. I attribute this effect to the decreased opportunity cost of charter school entrepreneurship. However, areas most affected by the Great Recession experienced a decrease in the stock of charter schools, as the challenges associated with opening a new school likely increased and lowered the viability relative to education entrepreneur's next best venture.
Open Access
Three essays on connections between personal life and economic outcomes
(Colorado State University. Libraries, 2018) Curley, Christina, author; Bernasek, Alexandra, advisor; Zahran, Sammy, committee member; Mushinski, David, committee member; Canetto, Silvia Sara, committee member
The theme of this collection is the intersection of individuals' personal lives and economic lives. Personal traits may be influenced by gender, life events, and socioeconomic class. Personal traits can affect productivity and therefore are important in determining what happens in the labor market. In other words, what happens at work and what happens at home are not entirely separate. The first essay explores how sexual orientation and sexual experiences are related to individual income. Previous literature indicates that gay, lesbian, and bisexual (LGB) individuals experience an income differential when compared with heterosexuals. Recent data indicate that self-identification as an LGB individual and/or same-sex sexual behavior are still correlated with a lower income, however, not all of the results are statistically significant. In addition, there is a statistically significant negative income differential of 32% for men who report having had a same sex partner at some point, but identify as straight/heterosexual. The second essay analyzes parental divorce and how this may affect children later in life. Previous literature indicates that a multitude of issues exist for children whose parents divorced. The impact of parental divorce on children's income later in life is tested. Results from the Panel Study of Income Dynamics (PSID) indicate that negative income effects from parental divorce persist for young men, however, young women and older age groups do not experience negative impacts on income. The third essay investigates a relationship between student loan debt and probability of marriage. Using the Baccalaureate and Beyond Survey 2008-2012, and with gender differences in mind, the impact of student loan repayment burden on the probability of marriage occurring in the four years following graduation is tested. Results indicate that increased payment-to-income ratio on student loan debt is negatively related to the probability of getting married for women who indicate a delay in marriage due to education debt.
Open Access
Three essays on corruption in the Middle East and North Africa
(Colorado State University. Libraries, 2022) Kirsanli, Fatih, author; Vasudevan, Ramaa, advisor; Tavani, Daniele, committee member; Zahran, Sammy, committee member; Dossani, Asad, committee member
This dissertation focuses on the corruption phenomenon at the macro level in the Middle East and North Africa (MENA) after the Arab uprisings regarding its impacts on economic growth and income inequality. The first chapter investigates the relationship between corruption and economic growth. The results show that after the Arab Spring, corruption lowers economic growth. After clustering the MENA countries into three categories -- severe, moderate, and light -- according to the magnitude of the Arab protests and their outcomes, the results are obscure due to the low number of observations. Although the results are not significant in sub-sample regressions, they are robust for the entire data set with alternative corruption indexes. Furthermore, the findings verify that the natural resource curse is a valid argument. Lastly, the Chow test confirms that 2011, the year when the Arab protests started, constitutes a structural break. The second chapter examines the impact of corruption on income inequality. The findings concludes that there is no significant relationship between corruption and inequality for the entire data set. Then, the MENA region is categorized into three sub-regions as in the first chapter to test whether results constitute intra-regional heterogeneity. The robust results reveal a negative and significant relationship between the Arab Spring and inequality in severely affected countries. Nevertheless, the results are insignificant for moderately and lightly affected countries. The third chapter analyzes the heterogeneous findings of the previous chapters. In the first part, crony capitalism, democratization of corruption and rentier state models are discussed to explain the political-institutional characterization of severely, moderately and lightly affected countries. In the second part, severely affected countries are further examined on how corruption income inequality nexus rotates in terms of magnitude and sign and still significant after the Arab Spring. The political economy analysis helps to provide country and group-specific policy recommendations.
Open Access
Three essays on globalization of trade and structures of economic growth and (under) development: comparative analysis of advanced and emerging nations
(Colorado State University. Libraries, 2020) Ganguly, Arpan, author; Braunstein, Elissa, advisor; Vasudevan, Ramaa, advisor; Tavani, Daniele, committee member; Zahran, Sammy, committee member; Stevis, Dimitris, committee member
With the rise of neoliberal perspectives on economic policy and development in the 1980s came a new phase of globalization in the world economy. Quantitative increases in trade and financial flows, coupled with qualitative changes in corporate strategy and governance have been elemental to this process. Globalization of trade and production has integrated developed and underdeveloped regions of the world in a process of capitalist expansion and accumulation, one that has at times delivered bouts of growth in some countries, but little in terms of economic development or improvements in employment in others. This dissertation seeks to understand linkages between the globalization of trade and structures of development and under-development. Chapter 1 empirically evaluates the impact of trade and globalization on the quality of employment, particularly wage inequality by skill type and the functional distribution of income. This paper argues that rather than changes in relative prices, the link between trade and wage inequality is better explained by the mechanism of skill-intensity reversals. This is evident in trade's negative impact on less-skilled labor's skill intensity in production. Particularly for emerging nations, gains from external integration based on exploiting resource or skill-based differences in comparative advantage seems to have become transitory over time. Chapter 2 models the multifaceted impacts of trade and globalization on economic growth, using principal component analysis to differentiate among groups of countries based on how global capital interacts with domestic macroeconomic structures. This paper ties together a wide range of structuralist growth models to provide a unified narrative on regimes of globalization and growth. Chapter 3 evaluates the impact of trade globalization on economic development through its impact on structural change. This paper groups the analysis of regional differences in structural change in the development literature into three broad categories. Data on sectoral composition of value-added trade, output and employment is used to emphasize these regional dynamics, highlighting how internal and external constraints on the industrial sector lie at the heart of these challenges.