International migration by 2030: impact of immigration policies scenarios on growth and employment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose – The aim of this paper is to estimate the dynamic of international migration between the different regions of the world for 2030 and to measure the impact of different kind of migration policies on the economic and social evolution. Design/methodology/approach – The change and migration forecasting are estimated for regions of the world using macroeconomic Cambridge Alphametrics Model. Findings – The crisis and its aggravation thus clearly favour scenarios of immigration policy along the “zero migration” or “constant migration”. These choices of migration policies reinforce the deflationary process resulting in reduced opportunities for renewed growth in industrial areas and are not offset by the dynamism of growth in emerging countries. Paradoxically, the developed countries which are most durably affected by the crisis are also those that have ageing population and are in high need of skilled and unskilled labor. Practical implications – Three options are possible: one going along the depressive process by espousing restrictive immigration policies that remain expensive. The second involves a highly selective immigration policy. Under these conditions the demographic revival already appearing would be reinforced by a rejuvenation of the population brought about by a more open immigration policy. Political and institutional factors play a fundamental role in the emergence of this optimistic assumption and the rise of isolationism in Europe and the ghettoization of suburban areas can hinder the application of such a policy of openness to migration. The third scenario, the mass migration scenario, allows letting go of the growth related constraints and getting out of the deflationist spiral. This pro-active approach could cause public opinions to change in line with public interest. This scenario of mass migration has more of a chance to see the light under a growth hypothesis. However, restrictive policies weaken the prospects of sustainable recovery causing a vicious cycle that can only be broken by pro-active policies or by irresistible shocks. Originality/value – From specific estimations, four immigration regimes have been built that cut across the major regions of the model: the “core skill replacement migration regime” based on selective policies using migration to fill high-skilled labor needs (United Kingdom, West and Northern Europe, Canada, Australia, and USA), “mass immigration and replacement” applies to South Europe, East Asia High Income, and part of West Asia (Gulf countries), “big fast-growing emerging regions of future mass immigration,” notably China, India and “South-South migration” based on forced migration much of it by climate change, which may likely occur in South Asia, part of West Asia, and, most of Africa (without South Africa). Migrations in transit countries (Central America to USA, and East Europe to UK and West Europe) are based on low skilled migrants in labor-intensive sectors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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