Digitalization and Inflation: A Review of the Literature
Bibliographic record
Abstract
In the past few years, many have postulated that the possible disinflationary effects of digitalization could explain the subdued inflation in advanced economies. In this note, we review the evidence found in the literature. We look at three main channels. First, we find that changes in the prices of information and communication technology-related goods and services included in the CPI have had a negligible effect on inflation in Canada. Second, we find that, due to the small share of e-commerce in Canada and the remarkably similar behaviour of online and offline prices, the “Amazon effect” has only had a small disinflationary impact to date. As e-commerce grows, however, downward pressure on inflation may amplify in the future through increased competition, but digitalization may also increase market concentration. Finally, although cost-efficient technologies should lead to increased productivity, which would put downward pressure on inflation, this effect has yet to appear in the statistics. Overall, we find it unlikely that digitalization has so far had a significant effect on inflation in Canada.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".