The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach

Partridge, Mark D.; Rickman, Dan S.; Ali, Kamar; Olfert, M. Rose

doi:10.3368/le.84.2.241

Cited by 120 publications

(139 citation statements)

References 39 publications

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“…Although there may be measurement error bias when using straight-line distance rather than travel time, Apparicio et al (2008) show that Cartesian distances-i.e., Euclidean and Manhattan distances-are strongly correlated with more accurate travel time distances. Moreover, Partridge et al (2008) argue that such measurement error would bias the distance regression coefficient toward zero, suggesting that the actual effect of distance would be stronger than reported. Also, with the relatively well-developed road systems in the countries under consideration, the measurement error is expected to be small.…”

Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 89%

“…First, we measure distance from the geographical centroid of the municipality to the centroid of the nearest urban municipality. If a municipality is located close to a major urban center, it may benefit from urban spillovers as well as Bborrowed size^effects (Partridge et al 2008;Meijers and Burger 2015). If a municipality is classified as urban, the distance to the nearest urban municipality is zero for this municipality.…”

Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 99%

“…If a municipality is classified as urban, the distance to the nearest urban municipality is zero for this municipality. Following Partridge et al (2008), it can be expected that there is an incremental distance penalty for access to more populous higher-level urban areas. Specifically, remoteness from a larger city would carry an added penalty, but this penalty is only incrementally greater than the already existing distance penalty.…”

Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 99%

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Urbanization and start-up rates in different geographies: Belgium, the Netherlands, and Sweden

Hans

Koster

2017

Small Bus Econ

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This study addresses the mediating role of settlement patterns in the relationship between urbanization and start-up activity. Places do not operate in a vacuum and to understand the effect of Bown^density on start-up patterns, we need to account for the urban spillovers or borrowed size that they may experience from other places nearby. The results can explain the empirical ambiguity in the relationship between urbanization and start-up patterns: the relationship between urbanization and start-up rates becomes more similar between countries when controlling for countryspecific settlement patterns by including a spatially lagged urbanization variable and variables measuring the distance to urban centers. Accounting for the relative location of places and relevant sorting effects, we find that Bown^density has a consistently negative effect on start-up activity. Yet, access to other places has a generally positive effect. This implies that nearby regions profit from the advantages offered by urban environments without having to deal with the costs involved.

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Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 89%

Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 99%

Section: Measuring the Mediating Effects Of Settlement Patternsmentioning

confidence: 99%

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Urbanization and start-up rates in different geographies: Belgium, the Netherlands, and Sweden

Hans

Koster

2017

Small Bus Econ

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“…Evidence in support to this link between amenities and high-tech employment is reported by Partridge et al (2008). We therefore include a variable that measures bilateral differences in natural amenities using the natural amenity index for each state provided by the Economic Research Service of the United States Department of Agriculture.…”

Section: Htmentioning

confidence: 99%

Business cycle dynamics across the US states

Magrini

Gerolimetto

Duran

2013

The B.E. Journal of Macroeconomics

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Abstract:The analysis of synchronization among regional or national business cycles has recently been attracting a growing interest within the economic literature. Far less attention has instead been devoted to a closely related issue: given a certain level of synchronization, some economies might be systematically ahead of others along the swings of the business cycle. We analyze this issue within a system of economies and show that leading (or lagging behind) is a feature that does not occur at random across the economies. In addition, we investigate the economic drivers that could explain this behavior. To do so, we employ data for 48 conterminous US states between 1990 and 2009.

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“…Nilai bandwidth yang optimal menunjukkan seberapa banyak pengamatan yang berpengaruh signifikan dalam pembentukan model GWR [11] . Ada beberapa metode yang digunakan untuk memilih bandwidth optimum, salah satunya adalah Cross Validation (CV) [9] : …”

Section: Pemilihan Bandwidthunclassified

Pemodelan Data Kemiskinan Di Provinsi Sumatera Barat Dengan Metode Geographically Weighted Regression (Gwr)

Maggri¹,

Ispriyanti²

2013

Medstat

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Counting the number of poor have often been modeled as a function of a global regression, which meant that the regression coefficient value applied to all geographic regions. Though this assumption was not always valid because of the differences in geographic locations most likely causing the spatial heterogeneity. In case of spatial heterogeneity, the regression parameters would vary spatially, so if the global regression model was applied, would produce an average value of those regression parameters which vary spatially. This study uses the method Geographically Weighted Regression (GWR) to analyze data that contains spatial heterogeneity. In GWR model estimation, the model parameters are obtained by using the Weighted Least Square (WLS) which gives a different weighting in each location. This study discusses the factors that influence the level of poverty in the province of West Sumatra. Suitability test of the model results shows that there is no influence of spatial factors on the level of poverty in the province of West Sumatra. The results shows that there are four variables that are assumed to affect the level of poverty in the province of West Sumatra, they are the variable of floor space, the facility to defecate, ability to pay the cost of health center / clinic and education levels of household head. The four variables have a similar effect in every city and county.

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The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach

Cited by 120 publications

References 39 publications

Urbanization and start-up rates in different geographies: Belgium, the Netherlands, and Sweden

Urbanization and start-up rates in different geographies: Belgium, the Netherlands, and Sweden

Business cycle dynamics across the US states

Pemodelan Data Kemiskinan Di Provinsi Sumatera Barat Dengan Metode Geographically Weighted Regression (Gwr)

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