Staggered Contracts, Intermediate Goods, and the Dynamic Effects of Monetary Shocks on Output, Inflation, and Real Wages
Bibliographic record
Abstract
This paper investigates the contributions of staggered price contracts, staggered wage contracts, and an input-output production structure in generating the observed persistence of real output and inflation, and the weak but persistent response of real wages following monetary shocks. It examines the interactions of these three mechanisms in a dynamic general equilibrium (DGE) environment, with pricing decision and wage setting rules derived from individual optimization. Following a monetary shock, (i) a staggered wage model generates more persistence in both inflation and output than does a staggered price model when intermediate goods are used in production; (ii) adding intermediate goods causes a tradeoff between output persistence and inflation persistence: it magnifies the autocorrelations of output while reducing those of inflation in both the short and medium horizons; (iii) a combination of staggered prices and staggered wages is required to generate the observed weak but persistent response of real wages to a monetary shock, and incorporating intermediate goods in such a model is essential to make the real wage response weakly procyclical.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".