Labor Share Fluctuations in Emerging Markets: The Role of the Cost of Borrowing
Bibliographic record
Abstract
This paper contributes to the literature by documenting labor income share fluctuations in emerging economies and proposing an explanation for them. We show that emerging markets differ from developed markets in terms of changes in the labor share over the business cycle. Labor share is more volatile in emerging markets and is pro-cyclical with output, especially in countries facing counter-cyclical interest rates. On the contrary, labor share in developed markets is more stable and slightly counter-cyclical with output. A frictionless RBC model cannot account for these facts. We introduce working capital into an RBC model, which generates liquidity need for labor payments. The main result is that the behavior of the cost of borrowing along with working capital mechanisms can predict the right sign of the comovement between labor share and output, and can partly be responsible for the volatility of labor share. We also show that imperfect financial markets in the form of credit restrictions not only amplify the results for the variability of labor share but also help better explain some of the striking business cycle regularities in emerging markets such as strongly pro-cyclical investment and counter-cyclical net exports.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".