Liquidity, Redistribution, and the Welfare Cost of Inflation
Bibliographic record
Abstract
This paper studies the long run welfare costs of inflation in a micro-founded model with trading frictions and costly liquidity management. Agents face uninsurable idiosyncratic uncertainty regarding trading opportunities in a decentralized goods market and must pay a fixed cost to rebalance their liquidity holdings in a centralized liquidity market. By endogenizing the participation decision in the liquidity market, this model endogenizes the responses of velocity, output, the degree of market segmentation, as well as the distribution of money. We find that, compared to the traditional estimates based on a representative agent model, the welfare costs of inflation are significantly smaller due to distributional effects of inflation. The welfare cost of increasing inflation from 0% to 10% is 0.62% of income for the U.S. economy and 0.20% of income for the Canadian economy. Furthermore, the welfare cost is generally non-linear in the rate of inflation, depending on the endogenous responses of the liquidity market participation to inflation and liquidity management costs.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".