Effects of Scale in Spatial Interaction Models

Arbia, Giuseppe; Petrarca, Francesca

doi:10.1007/978-3-319-30196-9_5

Cited by 7 publications

(7 citation statements)

References 8 publications

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“…This work can be extended in several ways. First, one may explicitly take into account the geographic dimension in trade and migration data by using spatial-econometric techniques in gravity regressions [ 47 ]. Indeed, the absence of serial autocorrelation in trade and migration data (as documented by Wooldridge-Drukker tests) does not exclude the presence of autocorrelation at the spatial level (either in the dependent variable or in the disturbances).…”

Section: Discussionmentioning

confidence: 99%

Does Human Migration Affect International Trade? A Complex-Network Perspective

Fagiolo

Mastrorillo

2014

PLoS ONE

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This paper explores the relationships between international human migration and merchandise trade using a complex-network approach. We firstly compare the topological structure of worldwide networks of human migration and bilateral trade over the period 1960–2000. Next, we ask whether pairs of countries that are more central in the migration network trade more. We show that: (i) the networks of international migration and trade are strongly correlated, and such correlation can be mostly explained by country economic/demographic size and geographical distance; (ii) centrality in the international-migration network boosts bilateral trade; (iii) intensive forms of country centrality are more trade enhancing than their extensive counterparts. Our findings suggest that bilateral trade between any two countries is not only affected by the presence of migrants from either countries, but also by their relative embeddedness in the complex web of corridors making up the network of international human migration.

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Section: Discussionmentioning

confidence: 99%

Does Human Migration Affect International Trade? A Complex-Network Perspective

Fagiolo

Mastrorillo

2014

PLoS ONE

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“…The MAUP effects have also been studied in OLS regressions [ 9 , 11 , 22 , 27 ], logit models [ 28 ], Poisson regression [ 29 ], spatial interaction models [ 30 ], spatial econometrics models [ 31 ], forecasts in regional economy [ 32 ], and spatial autocorrelation statistics, such as the Moran’s coefficient, Geary’s Ratio, and G-Statistic [ 28 , 33 , 34 ]. Other authors have studied the MAUP effects in more sophisticated methods, such as the factorial analysis [ 35 ], spatial interpolation [ 36 ], image classification [ 37 ], location and allocation models [ 38 ], and discrete selection models [ 39 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Also, in the field of spatial econometrics, although it is a controversial issue, it is recommended the use of an exogenous weights matrix such as the first-order spatial contiguity matrix [ 48 – 50 ]. The rook matrix has been also used in four of the most important computational experiments on the effects of the MAUP [ 20 , 30 , 31 , 33 ]. However, according to [ 51 ], in grouping through averages, the variance of the aggregated variable decreases faster as the average number of neighbors increases.…”

Section: Maup Effectsmentioning

confidence: 99%

S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem

2018

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This work presents a nonparametric statistical test, S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge, S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP.

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“…The most often cited measures of α vary between 1.5 and 2 [38] and range from 1.0 to 2.2 [20]. The value is often set to 1 [3,9] and 2 [39,40]. The population potential model is a type of gravity model borrowed by geographers from the physical sciences (e.g., Newton's laws of gravitation) [5,41].…”

Section: Urban Population Potential Modelingmentioning

confidence: 99%

A Novel Method for Simulating Urban Population Potential Based on Urban Patches: A Case Study in Jiangsu Province, China

et al. 2015

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Urban population potential is a good measure of urban spatial interactions. However, previous studies often assigned population data to the administrative point of the government or the centroid of the region, such as the county, ward or village. In these cases, two problems exist: (1) the zone centroid problem and (2) the scale problem. To better deal with these problems, we proposed a novel method for simulating the urban population potential based on urban patches using Jiangsu Province as the study area. This study conducted research on a classification scheme based on area for urban patches and developed an urban population potential model on the basis of a potential model. The spatial simulation of the urban population potential at various urban scales and the comprehensive urban population potential of Jiangsu were determined. The spatial pattern is "southern Jiangsu high and north-central Jiangsu low", which is consistent with the "pole-axis" spatial system. This study also compared the simulations of the new method and a traditional method. Results revealed that the method based on urban patches was superior in simulating real spatial patterns of the urban population potential. Further improvements should focus on actual conditions, such as passable expressway entrances and exits and railway stations, and OPEN ACCESSSustainability 2015, 7 3985 high-speed railway data should be employed when simulating the urban population potential across provinces and greater China.

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Effects of Scale in Spatial Interaction Models

Cited by 7 publications

References 8 publications

Does Human Migration Affect International Trade? A Complex-Network Perspective

Does Human Migration Affect International Trade? A Complex-Network Perspective

S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem

A Novel Method for Simulating Urban Population Potential Based on Urban Patches: A Case Study in Jiangsu Province, China

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