The Role of Interest Rates and Productivity Shocks in Emerging Market Fluctuations
Bibliographic record
Abstract
In this paper we use a quantitative model to explore the potential frictions that distinguish emerging market business cycles from developed small open economies. Following Aguiar and Gopinath (2007) we allow total factor productivity (TFP) to have a stationary and an integrated component. We also allow for shocks to the consumption and investment Euler Equations that operate through the interest rate. These “wedges” represent changes in the intertemporal marginal rate of transformation, which may be due to changes in observed interest rates, unobserved borrowing constraints, or other financial frictions. We estimate the model using data from Mexico and Canada. We show that interest rate shocks orthogonal to domestic TFP fail to explain the behavior of emerging markets. We then allow for interest rates to respond to/co-vary with productivity shocks. We find that emerging market business cycles appear to be driven by large shocks to trend income combined with relatively small transitory shocks tha co-vary with the interest rate.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".