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- All Subjects: Spatial data infrastructures
- Creators: Rey, Sergio
- Resource Type: Text
Description
After a relative period of growth (2000-06), the U.S. economy experienced a sharp decline (2007-09) from which it is yet to recover. One of the primary factors that contributed to this decline was the sub-prime mortgage crisis, which triggered a significant increase in residential foreclosures and a slump in housing values nationwide. Most studies examining this crisis have explained the high rate of foreclosures by associating it with socio-economic characteristics of the people affected and their financial decisions with respect to home mortgages. Though these studies were successful in identifying the section of the population facing foreclosures, they were mostly silent about region-wide factors that contributed to the crisis. This resulted in the absence of studies that could identify indicators of resiliency and robustness in urban areas that are affected by economic perturbations but had different outcomes. This study addresses this shortcoming by incorporating three concepts. First, it situates the foreclosure crisis in the broader regional economy by considering the concept of regional economic resiliency. Second, it includes the concept of housing submarkets, capturing the role of housing market dynamics in contributing to market performance. Third, the notion of urban growth pattern is included in an urban sprawl index to examine whether factors related to sprawl could partly explain the variation in foreclosures. These, along with other important socio-economic and housing characteristics, are used in this study to better understand the variation in impacts of the current foreclosure crisis. This study is carried out for all urban counties in the U.S. between 2000 and 2009. The associations between foreclosure rates and different variables are established using spatial regression models. Based on these models, this dissertation argues that counties with higher degree of employment diversity, encouragement for small business enterprises, and with less dependence on housing related industries, experienced fewer foreclosures. In addition, this thesis concludes that the spatial location of foreclosed properties is a function of location of origination of sub-prime mortgages and not the spatial location of the properties per se. Also importantly, the study found that the counties with high number of dissimilar housing submarkets experienced more foreclosures.
ContributorsRay, Indro (Author) / Guhathakurta, Subhrajit (Thesis advisor) / Rey, Sergio (Committee member) / Phillips, Rhonda (Committee member) / Arizona State University (Publisher)
Created2012
Description
A major challenge in health-related policy and program evaluation research is attributing underlying causal relationships where complicated processes may exist in natural or quasi-experimental settings. Spatial interaction and heterogeneity between units at individual or group levels can violate both components of the Stable-Unit-Treatment-Value-Assumption (SUTVA) that are core to the counterfactual framework, making treatment effects difficult to assess. New approaches are needed in health studies to develop spatially dynamic causal modeling methods to both derive insights from data that are sensitive to spatial differences and dependencies, and also be able to rely on a more robust, dynamic technical infrastructure needed for decision-making. To address this gap with a focus on causal applications theoretically, methodologically and technologically, I (1) develop a theoretical spatial framework (within single-level panel econometric methodology) that extends existing theories and methods of causal inference, which tend to ignore spatial dynamics; (2) demonstrate how this spatial framework can be applied in empirical research; and (3) implement a new spatial infrastructure framework that integrates and manages the required data for health systems evaluation.
The new spatially explicit counterfactual framework considers how spatial effects impact treatment choice, treatment variation, and treatment effects. To illustrate this new methodological framework, I first replicate a classic quasi-experimental study that evaluates the effect of drinking age policy on mortality in the United States from 1970 to 1984, and further extend it with a spatial perspective. In another example, I evaluate food access dynamics in Chicago from 2007 to 2014 by implementing advanced spatial analytics that better account for the complex patterns of food access, and quasi-experimental research design to distill the impact of the Great Recession on the foodscape. Inference interpretation is sensitive to both research design framing and underlying processes that drive geographically distributed relationships. Finally, I advance a new Spatial Data Science Infrastructure to integrate and manage data in dynamic, open environments for public health systems research and decision- making. I demonstrate an infrastructure prototype in a final case study, developed in collaboration with health department officials and community organizations.
The new spatially explicit counterfactual framework considers how spatial effects impact treatment choice, treatment variation, and treatment effects. To illustrate this new methodological framework, I first replicate a classic quasi-experimental study that evaluates the effect of drinking age policy on mortality in the United States from 1970 to 1984, and further extend it with a spatial perspective. In another example, I evaluate food access dynamics in Chicago from 2007 to 2014 by implementing advanced spatial analytics that better account for the complex patterns of food access, and quasi-experimental research design to distill the impact of the Great Recession on the foodscape. Inference interpretation is sensitive to both research design framing and underlying processes that drive geographically distributed relationships. Finally, I advance a new Spatial Data Science Infrastructure to integrate and manage data in dynamic, open environments for public health systems research and decision- making. I demonstrate an infrastructure prototype in a final case study, developed in collaboration with health department officials and community organizations.
ContributorsKolak, Marynia Aniela (Author) / Anselin, Luc (Thesis advisor) / Rey, Sergio (Committee member) / Koschinsky, Julia (Committee member) / Maciejewski, Ross (Committee member) / Arizona State University (Publisher)
Created2017