Human capital, market imperfections, poverty and migration: evidence from rural Albania
Bibliographic record
Abstract
The most dramatic recent immigration in Europe is the influx of more than 700,000 Albanians, about a quarter of the total Albanian workforce, in the 1990s. The vast majority migrated illegally. This paper analyses the determinants of Albanian migration based on a unique representative survey of rural households. The study confirms that migrants are mostly young, male, and single. Regional variations in migration reflect a combination of cultural and economic factors, including migration costs. However, we find that migrants do not come from the poorest rural households. Moreover, education has a positive, albeit non-linear, effect on the likelihood of migration. Migration is negatively related with household access to alternative income sources and reduced financial constraints but positively related with the presence and household’s access to migration networks. Policy implications are that aid programs and government initiatives to invest in rural infrastructure and rural education may have mixed effects on migration. A key policy target to reduce migration should be the creation of non-farm rural employment and rural households’ access to finance.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".