Extending the Textbook Dynamic AD-AS Framework with Flexible Inflation Expectations, Optimal Policy Response to Demand Changes, and the Zero-Bound on the Nominal Interest Rate
Bibliographic record
Abstract
Many popular macroeconomics textbooks have recently adopted the dynamic aggregate demand-aggregate supply framework to analyze business cycle fluctuations and the effects of monetary policy. This brings the textbook treatment much closer to the research frontier, although a major remaining difference is the treatment of inflation expectations. Textbook treatments typically assume adaptive expectations for tractability. In this paper, we extend the model presented in Mankiw [1] by incorporating a more flexible form of expectation formation that is determined as a weighted average of past inflation and the inflation target. This brings the treatment closer to rational expectations and allows for a discussion of costless disinflation. Monetary policy is assumed to follow a Taylorrule, but we allow for deviations from the rule to motivate a discussion regarding optimal monetary policy response to demand shocks. We also include a shock to the risk-premium on the interest rate relevant for demand relative to the policy rate set by the Central Bank, and impose the zero-bound on the nominal interest rate in the solution of the model. These features allow for the analysis of the recent financial crisis, monetary policy falling into a liquidity trap, and the desirability of a temporary increase in the inflation target. Finally, we make available an Excel sheet with which students can analyze the effect of shocks to the economy using impulse responses and dynamic aggregate demand-aggregate supply diagrams.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".