China's Economic Statecraft in Latin America: Evidence from China's Policy Banks
Why this work is in the frame
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Bibliographic record
Abstract
Most scholars and policy makers classify the motivation behind China’s global economic activity as an effort to project soft power or to exercise “extractive diplomacy” by locking up natural resources across the globe. In this paper we argue that China, through its state financial institutions and firms, is also significantly motivated by simply commercial reasons. To shed light on this debate, we examine the extent to which China’s policy banks provide finance to sovereign governments in Latin America. We find that Chinese policy banks now provide more finance to Isatin American governments each year than do the World Bank and Inter-American Development Bank (IDB). Indeed, the large loan size, high interest rates and focus on industry and infrastructure of Chinese finance has less in common with these international financial institutions (IFIs) and more in common with the private sovereign bond market. In this way, Chinese finance appears primarily commercial in nature. Chinese banks offer slightly lower interest rates than the private market, but these arc not necessarily concessional subsidies to support a political agenda. The Chinese banks are exposed to less risk because they tic their loans to equipment purchase requirements and oil purchase contracts. Through these risk-lowering arrangements, Chinese banks can profit by lending to countries that have been priced out of the sovereign debt market. While it can be difficult to distinguish between the three types of economic statecraft outlined above, we argue that commercial profit is also a major force behind China’s economic statecraft that has been largely overlooked.
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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 | 0.000 |
| 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) | 0.001 | 0.001 |
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