Are Remittances to Sub-Saharan Africa Altruistic or for Self-Interest? Evidence from Kenya
Bibliographic record
Abstract
International remittances comprise significant financial inflow for many Sub-Saharan African (SSA) countries and provide considerable disposable income for the receiving households. There has, however, been no consensus on the motivation in the part of sending migrants in which explanations are divided between altruism and self-interest. The study employs Autoregressive Distributed Lag (ARDL) model with co-integration approach to investigate whether international remittances to Kenya can be explained by either altruistic or self-interest motive. We process the World Bank annual data from 1970 to 2010 and find that self-interest, not altruism, as the dominant motivation to determine remittances. The analysis also indicates that demand on housing and exchange rates are the two strong drivers of international remittances to Kenya in both short-run and long-run. The Kenyan government is supposed to facilitate savings from remittances through financial institutions to invest more in the small business sector for economic growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".