Unveiling inflation: Oil Shocks, Supply Chain Pressures, and Expectations
Bibliographic record
Abstract
After decades of a stable environment with low inflation in most advanced economies, global inflation rates surged unexpectedly during the pandemic and have remained elevated since. This paper demonstrates that inflation expectations have significantly amplified the global demand and supply shocks triggered by the pandemic, playing a crucial role in sustaining elevated inflation in the post-pandemic regime. We establish this finding by applying a structural vector autoregression model that includes various shocks to global demand and supply, along with domestic inflation and inflation expectations, across six economies: the United States, Canada, New Zealand, the Euro area, the United Kingdom, and Norway. First, we document that global demand and supply shocks in the oil market, as well as disruptions in global supply chains, have been major drivers of the recent inflation surge in all these economies. Then, through various counterfactual exercises, we demonstrate that inflation expectations generally amplify the transmission of global shocks to inflation — particularly in Canada, New Zealand, and the US during the post-pandemic period. As a result, managing inflation expectations should remain a crucial policy objective to mitigate their amplifying effects on inflation.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".