An Empirical Analysis of the Conduct and Effects of Monetary Policy
Bibliographic record
Abstract
This dissertation provides an empirical investigation on the implementation and effects of monetary policy. Chapter 2 examines how interest rate policy is determined at the European Central Bank. I provide empirical evidence against the notion that monetary policy at the European Central Bank favors the national interests of the largest member states. Instead, policy can best be described by a simple voting model where the median interest rate prevails. By mandate member countries are required to consider economic conditions in the broader Euro area when setting interest rate policy and, as I show, there is little empirical evidence suggesting that this is not the case. Because larger countries make up a larger fraction of these economic conditions, policy will favor their economic interests more often than not. The remainder of this dissertation uses data from the Survey of Professional Forecasters to examine the effects of monetary policy on the term structure of inflation expectations in the United States. In Chapter 3 I use the unobserved components model to estimate the term structure of inflation expectations from 1992–2018. I show how the model can be extended to allow for two departures from rational expectations and find that both channels are statistically significant. Contractionary monetary policy lowers inflation expectations after a lag of several years, an effect which is driven by the response of long-run inflation expectations which remain permanently lower after the policy move. Because interest rates and long-run inflation expectations are cointegrated, contractionary monetary policy additionally lowers future interest rates. In Chapter 4 I propose a method to calculate the impulse response of the term structure using local projections. The method uses the law of iterated expectations to derive a set of linear cross-equation restrictions which substantially reduce the number of parameters to estimate. I apply the term structure local projections to estimate the response of the term structures of inflation expectations and interest rates after a monetary policy shock. My results confirm the findings in Chapter 3: higher interest rates today cause both inflation expectations and interest rates to decline in the future.
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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 | 0.006 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".