Quantifying the Federal Reserve's objectives using a structural vector autoregressive model
Bibliographic Data
| ID | 9724607 |
|---|---|
| Authors | Shengliang Ou (0000-0001-9190-108X, Shanghai Jiao Tong University), Donghai Zhang (0000-0003-0141-809X, National University of Singapore, corresponding author) |
| Year | 2025 |
| Volume | 92 |
| Issue | 366 |
| Pages | 351-367 |
| Publication date | 2025-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Economica (JOURNAL) |
| Journal identifiers | ISSN: 0013-0427 • E-ISSN: 1468-0335 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/ecca.12571 |
| OpenAlex | W4407140959 |
| Language | EN |
| References cited | 45 |
The objective of the Federal Reserve (the Fed), namely, its dovish stance, is often blamed for the so‐called Great Inflation. A popular proxy for the Fed's dovish stance is constructed using the inflation coefficients in estimated Taylor rules. However, for a welfare‐optimizing central bank, the estimated Taylor coefficients are not sufficient for inferring its underlying preference. We quantify the Fed's objective—the targeting rule—relying on a conditional estimator that is free of the classical simultaneity problem. We discover that the Fed's targeting rule remained stable during the pre‐ and post‐Volcker periods—the opposite of what is implied through a Taylor rule estimation
Autoregressive model · Econometrics · Economics · Economic, financial, and policy analysis · Market Dynamics and Volatility · Monetary Policy and Economic Impact
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| Highly cited | No |
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