Revealing the structures of internal migration: A distance and a time-space behaviour perspectives

Halás, Marián; Klapka, Pavel

doi:10.1016/j.apgeog.2021.102603

Cited by 10 publications

(6 citation statements)

References 60 publications

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“…Relocation frequency rapidly declines with distance. Putting concrete figures aside, one may conclude that the frequency-distance curves obtained for Russia are similar to those characteristic of Sweden [7], the Czech Republic [27], and Hungary [37]. A distance of 200-300 km, which separates Moscow from regional capitals bordering on the Moscow region or Krasnodar from Rostov-on-Don, is travelled by 6.3 % of Russia's internal migrants.…”

Section: Resultsmentioning

confidence: 92%

“…Overall, the situation in the country is described by the classical curve graph: migration intensity decreases as distance grows. Yet, the curve has a minor peak corresponding to the distance between Prague and Brno, which is about 210 km [27]. In the 1980s, 73 % in the US and 83 % in the UK moved within 50 km.…”

Section: State Of Researchmentioning

confidence: 98%

“…It has been demonstrated for the US that estate owners move longer distances (by 75 %) than renters, albeit this difference is visible only as long as short-distance is concerned and disappears for distances over 50 km [15]. A study into the situation in the Czech Republic [27] demonstrates that an increase in the proportion of estate owners causes the significance of long-distance migration to diminish, as estate owners seem to be particularly attached to their places of residence.…”

Section: State Of Researchmentioning

confidence: 99%

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Migration distances in Russia: a demographic profile of migrants

Karachurina¹,

Владимирович²

2023

Balt. Reg.

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The distance of migration is closely linked to life course events, which are, in turn, marked by age. It serves as a criterion for distinguishing migration from other forms of spatial mobility. This paper aims to calculate the average distance of domestic migrations in Russia between 2011 and 2020, considering various migrant profiles such as sex, age, and type of residential registration. The Euclidean distance between 130,000 geocoded Russian settlements was computed to estimate migration distances. These geospatial data enabled us to obtain estimations of migration distances by weighting the total distance of all migrations based on their respective numbers. The distance of internal migration was similarly estimated, taking into account age, sex, and type of residential registration. The findings revealed that 31.3 % of domestic residential relocations occurred within very short distances not exceeding 50 km, while 43.5 % took place within 100 km of the previous place of residence. Calculating the average migration distance allowed us to identify two peaks: one at the ages of 22—23, present only for men, and another at the ages of 50—70. In all other cases, there were no sex-specific differences in migration distances. Migrants who obtained permanent registration at their new place of residence tended to cover greater distances compared to those registered only temporarily. The shortest relocation distances were associated with the age of 16, which could be attributed to prospective students moving to the nearest town where a vocational school is located.

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Section: Resultsmentioning

confidence: 92%

Section: State Of Researchmentioning

confidence: 98%

Section: State Of Researchmentioning

confidence: 99%

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Migration distances in Russia: a demographic profile of migrants

Karachurina¹,

Владимирович²

2023

Balt. Reg.

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“…Research on internal migration in Slovakia has explored unemployment and wage differentials (Janotka & Gazda, 2010;Michálek & Podolák, 2011;Ondoš and Káčerová, 2015) and regional clusters (Janotka et al, 2013). Relatively few studies have targeted the quantitative assessment of migration motives over the long term (but see Morrison & Clark, 2011;Thomas, 2019;Halás & Klapka, 2021). Most studies on internal migration adopt a costbenefit framework and leave the gap between self-reported motives and actual socioeconomic and sociodemographic developments unanswered.…”

Section: Introductionmentioning

confidence: 99%

Geography of migration motives: Matching migration motives with socioeconomic data

Baláž,

Lichner,

Jeck

2023

Moravian Geographical Reports

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Motives behind internal migration reported by internal migrants often differ from those assumed by standard economic and social theories. This research aims to narrow the gap between the stated motives and those suggested by human capital models. It relates the net migration rates by specific motives to socioeconomic and sociodemographic variables at the LAU 1 level in the period 1997–2021 in Slovakia. This research establishes that most of the stated motives behind internal migration (housing and family) differ from those assumed by human capital theories. This finding is valid for motives stated at the proximal level. The analysis of migration rates and housing supply indicates a substantial concentration of interdistrict migrants in suburban districts of affluent metropolitan regions. This finding resonates with assumptions on the latent importance of employment and income for internal migration.

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“…On the one hand, the rural population migrates more to economically developed regions in many countries, because there are more employment opportunities and a stronger absorptive capacity for surplus rural labor [16][17][18][19]. On the other hand, the willingness to migrate and the number of migrating populations are negatively correlated with the migration distance [20,21]. According to the first law of geography proposed by Tobler [22], neighboring regions have fewer differences in natural environmental characteristics, lifestyles, cultural systems, and types of languages or dialects.…”

Section: Introductionmentioning

confidence: 99%

Spatial Pattern of Farmland Transfer in Liaoning Province, China

et al. 2023

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Farmland transfer (FT) is the key to achieving moderate agricultural scale management in China. Clarifying the spatial pattern of FT is important to improve FT strategies. In this study, the multinomial logit model was used to reveal the spatial pattern of FT in Liaoning Province, Northeast China. On this basis, the reasons for its formation were discussed, and suggestions were proposed. According to the statistical results, 39.7% of the sample peasant households participated in FT. Most of them live far from the regional core area. Regression analysis shows that the FT in Liaoning Province has a significant “core-periphery” spatial pattern. As the spatial distance between the residence and the regional core area (SDRRC) increases, the probability of FT rises for peasant households. Specifically, the odds ratios of farmland transfer out and farmland transfer in rise by 0.9% and 0.6% on average, respectively, for each 1 km increase in SDRRC. Widespread concurrent business and the increase in FT fees due to imperfect urbanization are the main reasons for the formation of the spatial pattern. We suggest that the promotion of FT requires high-quality urbanization in central cities, accelerating urbanization in medium and small cities and counties, implementing differentiated FT subsidy standards, and promoting new agricultural scale management models.

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Revealing the structures of internal migration: A distance and a time-space behaviour perspectives

Cited by 10 publications

References 60 publications

Migration distances in Russia: a demographic profile of migrants

Migration distances in Russia: a demographic profile of migrants

Geography of migration motives: Matching migration motives with socioeconomic data

Spatial Pattern of Farmland Transfer in Liaoning Province, China

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