Outward Foreign Direct Investments as a Catalyst of Urban-Regional Income Development? Evidence from the United States
Bibliographic record
Abstract
Challenging populist views of outward foreign direct investments (OFDIs) that suggest they move prosperity abroad, this article builds a model suggesting that OFDIs support urban-regional income levels due to (1) labor; (2) knowledge; and (3) multiplier, spillover, and intermediate input effects. In a panel study of median incomes in US urban regions between 2005 and 2013, we first establish a base model that measures income as a function of local factor endowments (high skill levels, fast-growing and technologically sophisticated industries, and urban scale effects). This base model is highly significant. In the next step, we extend this model by adding our main variables of greenfield inward and outward investment intensity, and finally we integrate other indicators that measure the geographic, industrial, and functional composition of OFDIs. While the results for other investment-related indicators are mixed, the main investment variables are highly significant, thus providing strong support that greenfield OFDIs act as a catalyst of urban-regional income development.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".