Migration, human capital, and growth in a globalized economy
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
This thesis focuses on the implications of past, and hypothetical future movements of people for the prosperity of natives and residents living in the highly developed regions. The first Chapter discusses the welfare impact of migration in the OECD countries by analyzing recent migration flows (net migration between 2000 and 2010), and total stock of migrants in 2010. The importance of different channels, through which migration affects the wellbeing of stayers, is discussed. In the second Chapter, the theoretical framework from the first Chapter is extended to evaluate migration policies in a multi-country general equilibrium model with endogenous migration and trade. In particular, the economic impact of removing visa and trade barriers between the European Union and five major partners (Australia, Canada, Japan, Turkey and the US) is quantified. Additionally, the proposed model gives theoretical evidence about the relations between migration and trade after imposing exogenous shocks to both types of barriers. The third Chapter proposes an innovative modeling technique to identify the global demographic impact of different migration policies in the EU. The model jointly considers peoples’ endogenous decisions about the country of destination, type of visa to apply for, and the duration of stay. In consequence, the proposed framework provides a micro-foundation for multilateral resistance to migration (a complex structure of dependencies between migration choice options). The research question posed in this paper challenges the capacity of the European Union to attract high-skilled immigrants.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 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