Bonded to the State: A Network Perspective on China's Corporate Debt Market
Bibliographic record
Abstract
A corporate bond market has the potential to play an important role as a supplement to bank-oriented financial systems in emerging markets—functioning in effect as a ‘spare tire’. Yet bond markets typically rely upon formal institutions that are lacking in developing economies. Despite significant institutional weaknesses, China’s corporate bond market has grown to become the third largest in the world. In this article, we use a network perspective to explore the formation, operation, and function of the Chinese corporate bond market. We explain the market’s exponential growth as a result of a network of relationships among state-owned or linked actors that has substituted for formal institutions. But the consequences of this state-centric network may undermine the spare tire function. We begin by unpacking the complexities of the market’s structure and formal regulation, which have been shaped by a surprising degree of regulatory competition. Next, we analyse China’s corporate bond market as a network of relationships that invariably lead back to the state, and explore the consequences of this network on the pricing, rating, and default of corporate bonds. The paper concludes by highlighting several important policy issues raised by our analysis, including the consequences of regulatory competition, the potential role of the bankruptcy system in handling issuer financial distress, and the linkages between the corporate bond market and China’s rapidly expanding shadow banking system. The size, and institutional fragility, of the Chinese corporate bond market illustrate both the accomplishments and limitations of state capitalism.
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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 | 0.002 | 0.001 |
| 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 | 0.000 | 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 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".