Spatial Econometrics and GIS YouTube Playlist

Burkey, Mark L.

doi:10.18335/region.v5i3.254

Cited by 11 publications

(6 citation statements)

References 6 publications

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“…In the final step, we performed spatial regressions between the MSME combinations and the 16 explanatory variables. Our approach to empirically estimating the spatial interaction between planned settlements and MSMEs adopts the analytical methods developed by Anselin [45], and later on by Burkey [46].…”

Section: Discussionmentioning

confidence: 99%

“…The spatial autocorrelation analyses estimated whether MSMEs were distributed randomly across neighborhoods or whether there is an underlying spatial pattern that exhibit certain degrees of clustering [45][46][47][48]. Such spatial clustering was assessed through a Moran's I test, as shown in the equation below, adopted from related studies [47][48][49]:…”

Section: Discussionmentioning

confidence: 99%

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Spatial Interactions between Planned Settlements and Small Businesses: Evidence from the Jakarta Metropolitan Area, Indonesia

Widita,

Lechner

2024

Land

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Rapid urban growth is reshaping cities and promoting economic development in low and middle-income countries throughout Southeast Asia, with the prevalence of Micro-, Small-, and Medium-sized Enterprises (MSME) emerging as a crucial factor. This study explores the complex relationship between MSMEs and planned settlements within the Jakarta Metropolitan Area (JMA), Indonesia. Utilizing official government data and extensive GIS sources analyzed using a Spatial Lag Model, the research assessed the spatial interactions between MSMEs and sixteen variables, revealing the statistical significance of eight of these variables. Notably, the study identified a negative correlation between the prevalence of planned settlements and the number of MSMEs, indicating that areas with a higher proportion of planned settlement land use tend to have fewer MSMEs. Emphasizing the importance of land use and built environment policies, the findings underscore MSMEs’ preference for locations with a greater share of commercial land uses. Moreover, the research highlights the localized nature of MSMEs, suggesting a tendency to cluster in specific areas. As Indonesia and other Global South countries experience rapid urbanization and potential increases in planned settlements, the study underscores the need for policymakers to develop strategies that foster a synergistic relationship between planned settlement development and MSME growth to support sustainable urban development.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Spatial Interactions between Planned Settlements and Small Businesses: Evidence from the Jakarta Metropolitan Area, Indonesia

Widita,

Lechner

2024

Land

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“…The collinearity of the fitted models was examined using variance inflation factors. The final multivariable SEM, SLX, and SDEM models were derived separately and compared using the likelihood ratio and Lagrange multiplier tests ( 52 ). We only presented the results from the final SEM model because it has a significantly better fit than the SDEM and SLX models (all comparisons had p -values<0.05) as well as the largest R-squared value and smallest AIC value.…”

Section: Methodsmentioning

confidence: 99%

Association of multi-criteria derived air toxics hazard score with lung cancer incidence in a major metropolitan area

Zhu

McWilliams

McKeon

et al. 2023

Front. Public Health

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BackgroundLung cancer remains a major health problem world-wide. Environmental exposure to lung cancer carcinogens can affect lung cancer incidence. We investigated the association between lung cancer incidence and an air toxics hazard score of environmental carcinogen exposures derived previously under the exposome concept.MethodsLung cancer cases diagnosed in Philadelphia and the surrounding counties between 2008 and 2017 were identified from the Pennsylvania Cancer Registry. Age-adjusted incidence rates at the ZIP code level were calculated based on the residential address at diagnosis. The air toxics hazard score, an aggregate measure for lung cancer carcinogen exposures, was derived using the criteria of toxicity, persistence, and occurrence. Areas with high incidence or hazard score were identified. Spatial autoregressive models were fitted to evaluate the association, with and without adjusting for confounders. Stratified analysis by smoking prevalence was performed to examine potential interactions.ResultsWe observed significantly higher age-adjusted incidence rates in ZIP codes that had higher air toxics hazard score values after controlling for demographic variables, smoking prevalence, and proximity to major highways. Analyzes stratified by smoking prevalence suggested that exposure to environmental lung carcinogens had a larger effect on cancer incidence in locations with higher smoking prevalence.ConclusionThe positive association between the multi-criteria derived air toxics hazard score and lung cancer incidence provides the initial evidence to validate the hazard score as an aggregate measure of carcinogenic exposures in the environment. The hazard score can be used to supplement the existing risk factors in identifying high risk individuals. Communities with higher incidence/hazard score may benefit from greater awareness of lung cancer risk factors and targeted screening programs.

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“…For the spatially lagged explanatory variables [ 45 ] or the spatial cross-regressive model (S.L.X. ), the response variable depends on own-location covariates (

) plus the same factors averaged by the neighboring regions (

).…”

Section: Methodsmentioning

confidence: 99%

The Impact of Meso-Level Factors on SARS-CoV-2 Vaccine Early Hesitancy in the United States

Kaliba

Andrews

2023

IJERPH

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The extant literature on the U.S. SARS-CoV-2 virus indicates that the vaccination campaign was lagging, insufficient, and uncoordinated. This study uses the spatial model to identify the drivers of vaccine hesitancy (in the middle of the pandemic), one of the critical steps in creating impactful and effective interventions to influence behavioral changes now and in the future. The applied technique accounted for observed and unobserved homogeneity and heterogeneity among counties. The results indicated that political and religious beliefs, quantified by Cook’s political bipartisan index and the percentage of the population affiliated with the main Christian groups, were the main drivers of the SARS-CoV-2 vaccine hesitancy. The past vaccination experience and other variables determining the demand and supply of vaccines were also crucial in influencing hesitancy. The results imply that vaccination campaigns require engaging community leaders at all levels rather than depending on politicians alone and eliminating barriers to the supply and demand of vaccines at all levels. Coordination among religious and community leaders would build a practical institutional arrangement to facilitate (rather than frustrate) the vaccination drives.

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Spatial Econometrics and GIS YouTube Playlist

Cited by 11 publications

References 6 publications

Spatial Interactions between Planned Settlements and Small Businesses: Evidence from the Jakarta Metropolitan Area, Indonesia

Spatial Interactions between Planned Settlements and Small Businesses: Evidence from the Jakarta Metropolitan Area, Indonesia

Association of multi-criteria derived air toxics hazard score with lung cancer incidence in a major metropolitan area

The Impact of Meso-Level Factors on SARS-CoV-2 Vaccine Early Hesitancy in the United States

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