Assessing Generalized Method-of-Moments Estimates of the Federal Reserve Reaction Function
Bibliographic Data
| ID | 19418693 |
|---|---|
| Authors | Éric Jondeau (0000-0002-5647-2010, Université Paris-Est Créteil), Hervé Le Bihan (Banque de France), Clémentine Gallès (Université Toulouse-I-Capitole) |
| Year | 2004 |
| Volume | 22 |
| Issue | 2 |
| Pages | 225-239 |
| Publication date | 2004-04-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1198/073500104000000118 |
| OpenAlex | W1974029565 |
| Language | EN |
| References cited | 42 |
Estimating a forward-looking monetary policy rule by the generalized method of moments (GMM) has become a popular approach. We reexamine estimates of the Federal Reserve reaction function using several GMM estimators and a maximum likelihood (ML) estimator. First, we show that over the baseline period 1979–2000, these alternative approaches yield substantially different parameter estimates. Using Monte Carlo simulations, we show that the finite-sample GMM bias can account for only a small part of the discrepancy between estimates. We find that this discrepancy is more plausibly rationalized by the serial correlation of the policy shock, causing misspecification of GMM estimators through lack of instrument exogeneity. This correlation pattern is related to a shift in the reaction function parameters around 1987. Reestimating the reaction function over the 1987–2000 period produces GMM estimates that are very close to the ML estimate
Econometrics · Endogeneity · Estimator · Generalized method of moments · Monte Carlo method · Statistics · Fiscal Policy and Economic Growth · Market Dynamics and Volatility · Mathematics · Monetary Policy and Economic Impact
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| Citation velocity | historical |
|---|---|
| Highly cited | No |