An official website of the United States government
Abstract Multiscale geographically weighted regression (MGWR) extends geographically weighted regression (GWR) by allowing process heterogeneity to be modeled at different spatial scales. While MGWR improves parameter estimates compared to GWR, the relationship between spatial scale and correlations within and among covariates—specifically spatial autocorrelation and collinearity—has not been systematically explored. This study investigates these relationships through controlled simulation experiments. Results indicate that spatial autocorrelation and collinearity affect specific model components rather than the entire model. Their impacts are cumulative but remain minimal unless they become very strong. MGWR effectively mitigates local multicollinearity issues by applying varying bandwidths across parameter surfaces. However, high levels of spatial autocorrelation and collinearity can lead to bandwidth underestimation for global processes, potentially producing false local effects. Additionally, strong collinearity may cause bandwidths to be overestimated for some processes, which helps mitigate collinearity but may obscure local effects. These findings suggest that while MGWR offers greater robustness against multicollinearity compared to GWR, bandwidth estimates should be interpreted with caution, as they can be influenced by strong spatial autocorrelation and collinearity. These results have important implications for empirical applications of MGWR.
more »
« less
The spatial and temporal dynamics of voter preference determinants in four U.S. presidential elections (2008–2020)
Abstract Political and social processes that shape people's voting preferences might be linked to geographical location, varying from place to place, and operating at local, regional, and national scales. Here, we use a local modeling technique, multiscale geographically weighted regression (MGWR), to examine spatial and temporal variations in the influences of county‐level socio‐economic factors on voter preference during the 2008–2020 U.S. presidential elections. We argue that the local intercept in the MGWR model is an indicator of the effect of spatial context on voter preference and not only can this be separated from the effect of other socio‐economic factors, but it needs to be in order to prevent misspecification bias in the indicators of these other factors. We also identify strong and consistent divisions across the country in how context shapes election results.
more »
« less
- Award ID(s):
- 2117455
- PAR ID:
- 10375577
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Transactions in GIS
- Volume:
- 26
- Issue:
- 3
- ISSN:
- 1361-1682
- Page Range / eLocation ID:
- p. 1609-1628
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
We consider the electoral bribery problem in computational social choice. In this context, extensive studies have been carried out to analyze the computational vulnerability of various voting (or election) rules. However, essentially all prior studies assume a deterministic model where each voter has an associated threshold value, which is used as follows. A voter will take a bribe and vote according to the attacker's (i.e., briber's) preference when the amount of the bribe is above the threshold, and a voter will not take a bribe when the amount of the bribe is not above the threshold (in this case, the voter will vote according to its own preference, rather than the attacker's). In this paper, we initiate the study of a more realistic model where each voter is associated with a willingness function, rather than a fixed threshold value. The willingness function characterizes the likelihood a bribed voter would vote according to the attacker's preference; we call this bribe-effect uncertainty. We characterize the computational complexity of the electoral bribery problem in this new model. In particular, we discover a dichotomy result: a certain mathematical property of the willingness function dictates whether or not the computational hardness can serve as a deterrence to bribery attackers.more » « less
-
The role of climate factors on transmission of mosquito-borne infections within urban landscapes must be considered in the context of the pronounced spatial heterogeneity of such environments. Socio-demographic and environmental variation challenge control efforts for emergent arboviruses transmitted via the urban mosquitoAedes aegypti. We address at high resolution, the spatial heterogeneity of dengue transmission risk in the megacity of Delhi, India, as a function of both temperature and the carrying-capacity of the human environment for the mosquito. Based on previous results predicting maximum mosquitoes per human for different socio-economic typologies, and on remote sensing temperature data, we produce a map of the reproductive number of dengue at a resolution of 250m by 250m. We focus on dengue risk hotspots during inter-epidemic periods, places where chains of transmission can persist for longer. We assess the resulting high-resolution risk map of dengue with reported cases for three consecutive boreal winters. We find that both temperature and vector carrying-capacity per human co-vary in space because of their respective dependence on population density. The synergistic action of these two factors results in larger variation of dengue’s reproductive number than when considered separately, with poor and dense locations experiencing the warmest conditions and becoming the most likely reservoirs off-season. The location of observed winter cases is accurately predicted for different risk threshold criteria. Results underscore the inequity of risk across a complex urban landscape, whereby individuals in dense poor neighborhoods face the compounded effect of higher temperatures and mosquito carrying capacity. Targeting chains of transmission in inter-epidemic periods at these locations should be a priority of control efforts. A better mapping is needed of the interplay between climate factors that are dominant determinants of the seasonality of vector-borne infections and the socio-economic conditions behind unequal exposure.more » « less
-
Abstract Biodiversity conservation efforts have been criticized for generating inequitable socio‐economic outcomes. These equity challenges are largely analyzed as place‐based problems affecting local communities directly impacted by conservation programs. The conservation of migratory species extends this problem geographically since people in one place may benefit while those in another bear the costs of conservation. Thespatial subsidiesapproach offers an effective tool for analyzing such relationships between places connected by migratory species. Designed to quantify ecosystem services provided and received in specific locations across a migratory species’ range—and the disparities between them—the spatial subsidies approach highlights three axes of inequity: between indigenous and settler colonial societies, between urban and rural populations, and between the Global North and Global South. Recognizing these relationships is critical to achieving two mutually reinforcing policy goals: avoiding inequitable conservation outcomes in efforts to conserve migratory species, and ensuring effective long‐term conservation of migratory species. In demonstrating how the spatial subsidies approach enables the identification and quantification of inequities involving three migratory species (northern pintail ducks, monarch butterflies, and Mexican free‐tailed bats), we argue that a spatial subsidies approach could apply to migratory species conservation efforts worldwide under the context of “payments for ecosystem services.”more » « less
-
Abstract We study the consequences of unequal parenting on children’s long-term outcomes. Our analysis reveals that parenting style exerts a distinct influence on children’s development, separate from socio-economic factors such as education and race. We contend that parenting styles adapt to the evolving environment in which children are raised. Although correlated with socio-economic family characteristics, this factor demonstrates an independent impact. Recognizing how parents respond to economic shifts is crucial for deriving policy implications. Supporting this perspective, our findings indicate that parenting choices exhibit systematic variation across countries and local communities with varying formal and informal institutions. Therefore, a critical next step in addressing inequality in early-childhood outcomes involves examining how parents will modify their own behaviours in response to potential policy changes.more » « less
