Migrants as Engines of Financial Globalization: The Case of Global Banking
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
Abstract Does international migration contribute to the spread of global commerce? Recent work demonstrates the relevance of international migration for patterns of investment, focusing on migrants’ role in facilitating investment from their host country to their country of origin. By contrast, we investigate the potential for migrants to attract inward investment into their host country. As customers, migrants shape the composition of the market in the country where they live, such that global networks of migrants can shape investment decisions of co-national firms. Focusing on a single sector, banking, we identify the mechanisms by which international migration attracts foreign investment. First, migrants may prefer home country banks, especially if they are excluded from financial services in their host country. Second, migrants require financial institutions to send remittances to their country of origin. We test these arguments using a global sample of foreign bank ownership data and find that bilateral migrant networks are a predictor of cross-border banking investment. These findings speak to how the composition of markets affects international investment, as well as the reinforcing relationship between two features of globalization: international migration and financial integration.
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 | 0.001 |
| 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