National Income Inequality and International Business Expansion
Bibliographic record
Abstract
We examine the extent to which host country income inequality influences multinational enterprises’ (MNE) expansion strategy for foreign production investment, depending on their specific strategic objectives. Applying a transaction cost framework, we predict that national income inequality has an inverted U-shaped relationship with foreign production investment. As inequality increases, MNEs accrue lower transaction costs arising from interactions with various local actors, leading to higher probability of investment. As income inequality increases further, its effect on location attractiveness will become negative, as its attraction effect is increasingly offset by additional monitoring, bargaining, and security costs owing to the more fractious nature of high inequality societies. In addition, we suggest that the impact of income inequality is contingent on investment objectives: The inverted U-shaped relationship is stronger for efficiency-seeking investment but weaker for market-seeking and competence-enhancing investments. We find substantial support for our hypotheses through an analysis of 27 years (1986-2012) of data on Japanese MNEs’ overseas production entries.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".