World experience of economic regulation of migration flows and its application in Ukraine
Why this work is in the frame
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Bibliographic record
Abstract
Anastasiia Simakhova, Doctor in Economics (Dr.oec.) Professor at the Department of Economics of the Faculty of Economics and Business Administration State University “Kyiv Aviation Institute”, Ukraine e-mail: anastasiia.simakhova@npp.kai.edu Viktoriia Derevliuk, Bachelor in Economics (Bc.oec.) Master student at the study programme “International Economics” State University of Trade and Economics, Ukraine e-mail: v.derevliuk_fmtp_1m_25_m_z@knute.edu.ua For citation: Simakhova A., Derevliuk V. (2025) World experience of economic regulation of migration flows and its application in Ukraine. Sociālo Zinātņu Vēstnesis / Social Sciences Bulletin, 41(2): 21–31. https://doi.org/10.59893/szv.2025.2(2) The study investigates global practices in the economic regulation of international migration flows and their applicability to Ukraine’s current migration challenges. With over 281 million international migrants globally and more than 6.3 million Ukrainians displaced due to the Russian military aggression, the issue of migration has become increasingly critical. The paper highlights the need to shift from purely legal-institutional approaches to evidence-based economic modeling that quantifies the macroeconomic effects of migration such as GDP impact, fiscal returns, remittances, and labor market transformation. Using comparative data from the USA, Canada, Germany, the UK, Sweden, and Poland, the research develops a predictive model to assess the economic potential of Ukrainian remigration. It also addresses the lack of a unified economic monitoring system for migration in Ukraine, underscoring the importance of integrating cost-benefit analysis into migration policy planning. The paper concludes that adopting international best practices in economic migration assessment can significantly contribute to Ukraine’s post-war recovery and strategic human capital development. Keywords: migration policy, economic regulation, labor migration, GDP, reintegration, migration, Ukraine. Pasaules pieredze migrācijas plūsmu ekonomiskajā regulēšanā un tās piemērošana Ukrainā Pētījumā tiek analizēta starptautisko migrācijas plūsmu ekonomiskās regulēšanas globālā prakse un tās piemērojamība Ukrainas pašreizējiem migrācijas izaicinājumiem. Ar vairāk nekā 281 miljonu starptautisko migrantu pasaulē un vairāk nekā 6,3 miljoniem ukraiņu, kuri pārvietoti Krievijas militārās agresijas dēļ, migrācijas jautājums ir kļuvis īpaši aktuāls. Rakstā uzsvērta nepieciešamība pāriet no tīri juridiski institucionālām pieejām uz pierādījumos balstītu ekonomisko modelēšanu, kas kvantitatīvi novērtē migrācijas makroekonomisko ietekmi, piemēram, IKP pieaugumu, fiskālos ieguvumus, naudas pārvedumus un darba tirgus pārmaiņas. Izmantojot salīdzinošos datus no ASV, Kanādas, Vācijas, Apvienotās Karalistes, Zviedrijas un Polijas, pētījumā tiek izstrādāts prognozēšanas modelis Ukrainas remigrācijas ekonomiskā potenciāla novērtēšanai. Tāpat tiek aplūkota vienotas ekonomiskās migrācijas uzraudzības sistēmas trūkuma problēma Ukrainā, uzsverot izmaksu–ieguvumu analīzes integrēšanas nozīmi migrācijas politikas plānošanā. Rakstā secināts, ka starptautiskās labākās prakses ieviešana ekonomiskās migrācijas novērtēšanā var būtiski veicināt Ukrainas pēckara atveseļošanos un stratēģisko cilvēkkapitāla attīstību. Atslēgvārdi: migrācijas politika, ekonomiskā regulēšana, darba migrācija, IKP, reintegrācija, migrācija, Ukraina. PDF
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it