Moving Closer or Drifting Apart: Distributional Effects of Monetary Policy
Bibliographic record
Abstract
Our paper picks up the current controversial debate about increasing (income) inequality due to recent monetary policy measures in major advanced economies. We use a VAR framework identified with sign restrictions to figure out how income inequality related measures react to monetary policy in six different advanced economies. These countries differ by their absolute income inequality as well as their redistribution. We choose the U.S., Canada and South Korea as countries with very little redistribution and Sweden, the Czech Republic and Hungary as countries with relatively high redistribution. While all economies experience an increase in Gini coeffcients of gross income in the presence of an expansionary monetary policy shock, only the U.S., Canada and South Korea also show a significant response in Gini coeffcient of net income. To figure out how the transmission of monetary policy to income inequality works we pick up the two major channels dominant in the literature: The employment channel and the income composition channel. The latter is analyzed by data from national accounts concerning two different kinds of income households receive: Labor related income and capital payments, both net. While we find that capital owners profit disproportionately in the less redistributing countries, we observe a more even reaction in both income types. This indicates that the harmful effects of expansionary monetary policy on the market income distribution are mitigated if the degree of redistribution is high.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".