The Role of Hierarchical Proximity in Migration and Population Growth: Urban Shadow versus Urban Synergy Effects

Plane, David A.; Henrie, Christopher J.

doi:10.2457/srs.42.109

Cited by 3 publications

(1 citation statement)

References 36 publications

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“…Two particularly fruitful directions would examine how size of metropolitan area and place in the metropolitan hierarchy affect upward mobility. Partridge, Rickman, Ali, and Olfert (, ), Plane (), and Plane and Henrie () offer some creative alternative spatial frameworks for classifying places by size and hierarchical proximity.…”

Section: Conclusion and Implications For Place‐based Policy And Resementioning

confidence: 99%

Intergenerational mobility of low‐income youth in metropolitan and non‐metropolitan America: A spatial analysis

Weber

Fannin

Goetz

2018

Regional Science Policy & Practice

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Average absolute upward mobility is greater for youth in non‐metropolitan counties than in metropolitan counties. What may be more important for upward mobility of low‐income youth, however, is not whether their county is metro or non‐metro but rather how far their county is from metropolitan centres. We test this hypothesis and find support for the conclusion that distance is a significant predictor of upward mobility, that remoteness from central metro counties is associated with higher upward mobility. We also find that the association of other factors with upward mobility differs between metro and non‐metro counties. The shares of single‐mother families and income inequality have a smaller negative association with upward mobility in metro than non‐metro counties. The high school dropout rate, on the other hand, has a much larger negative association with upward mobility in metro than in non‐metro areas, suggesting that the quality of the school system matters more in urban areas. Better spatial job matching and higher social capital, by contrast, are more positively correlated with mobility in non‐metro counties than in metro counties, suggesting that specific place‐based rural policies may have more potential to increase upward mobility in rural areas.

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Section: Conclusion and Implications For Place‐based Policy And Resementioning

confidence: 99%

Intergenerational mobility of low‐income youth in metropolitan and non‐metropolitan America: A spatial analysis

Weber

Fannin

Goetz

2018

Regional Science Policy & Practice

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Moving Up: Migration between Levels of the Settlement Hierarchy in Russia in the 2010s

Mkrtchyan,

Gilmanov

2023

Reg. Res. Russ.

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Moving Up: Migration between Levels of the Settlement Hierarchy in Russia in the 2010s

Mkrtchyan,

Gilmanov

2023

Izvestiâ Rossijskoj akademii nauk. Seriâ geografičeskaâ

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For the first time on Russian data for 2011–2020 the flow of population between 7 levels of the settlement hierarchy is estimated. Levels of the settlement hierarchy are represented by cities of different population sizes and their suburbs, other urban and rural settlements. Indicators of migration icrease (decrease) of the population and indicators of demographic efficiency in the form of matrices are calculated for the hierarchy levels. It is shown that the scale of this flow is affected by changes in the system of migration registration in Russia in the 2010s, namely, the automatic return of migrants to their place of permanent residence after the end of the period of registration at the place of residence. The beneficiaries of the population “vertical migration” are cities with over 250 thous. inhabitants, the biggest winners are the urban agglomerations of Moscow and St. Petersburg. Each next settlement hierarchy level gives the population “up” and receives replenishment from the lower “layers.” In contrast to countries where similar studies were conducted (USA, Canada, the Netherlands, etc.), there is no population flow from top to bottom in Russia, and upward flows have a very high efficiency; it is especially high for Moscow, St. Petersburg, and their suburbs. Despite the population movement between neighboring settlement hierarchy levels, its demographic effect is not as great as in irregular migrations. The research calculations are based on the migrants’ individual depersonalized data, which allow detailing migration flows to individual settlements in Russia. Spatial data referencing was carried out based on 15-digit Rosstat codes unique for each settlement. This made it possible to analyze migration not between administrative units, but between settlements grouped by population size. It was also possible to identify the influence of the features of accounting for migration on the population flow between the selected groups of settlements in the 2010s.

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The Role of Hierarchical Proximity in Migration and Population Growth: Urban Shadow versus Urban Synergy Effects

Cited by 3 publications

References 36 publications

Intergenerational mobility of low‐income youth in metropolitan and non‐metropolitan America: A spatial analysis

Intergenerational mobility of low‐income youth in metropolitan and non‐metropolitan America: A spatial analysis

Moving Up: Migration between Levels of the Settlement Hierarchy in Russia in the 2010s

Moving Up: Migration between Levels of the Settlement Hierarchy in Russia in the 2010s

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