Do Local Firms Benefit from Foreign Direct Investment? An Analysis of Spillover Effects in Developing Countries
Bibliographic record
Abstract
Developing countries are increasingly recipients of foreign direct investment (FDI). In this regard, governments are attempting to attract FDI due to the expected spillover effects, which relate to benefits in terms of increased productivity of local firms and technology diffusion from multinational enterprises (MNEs) to the domestic economy. However, it is generally not clear whether there are positive or negative spillover effects from FDI to local firms in developing economies. The purpose of this paper is to provide a review of the literature on spillover effects and linkages that arise from FDI in developing countries. Our review suggests that there tends to be negative intra-industry productivity spillover effects (i.e., spillovers between MNEs and local firms in the same industry). This may be explained by the fact that MNEs crowd out local competitors that are not able to compete against MNEs, and by the concept of “absorptive capacity” which implies that local firms may not be able to assimilate and absorb knowledge of MNEs. However, we find evidence for positive inter-industry spillovers through linkages between MNE affiliates and suppliers in different industry sectors which may be attributed to the benefits for MNEs in transferring knowledge and technology to their local suppliers. The study offers suggestions for future research.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 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".