на главную поиск contacts

Monetary Policy under Model and Data-Parameter Uncertainty

Опубликовано на портале: 22-12-2007
Journal of Monetary Economics. 2007.  Vol. 54. No. 7. P. 2083-2101. 
Empirical Taylor rules are much less aggressive than those derived from optimization-based models. This paper analyzes whether accounting for uncertainty across competing models and (or) real-time data considerations can explain this discrepancy. It considers a central bank that chooses a Taylor rule in a framework that allows for an aversion to the second-order risk associated with facing multiple models and measurement-error configurations. The paper finds that if the central bank cares strongly enough about stabilizing the output gap, this aversion leads to significant declines in the coefficients of the Taylor rule even if the central bank's loss function assigns little weight to reducing interest rate variability. Furthermore, a small degree of aversion can generate an optimal rule that matches the empirical Taylor rule

Аннотация статьи представлена на сайте ScienceDirect. Полный текст статьи находится в закрытом доступе

Препринт (полный текст) статьи размещен на сайте Правительства Канады, на сайте Банка Канады и на сайте Econometric Society
Ключевые слова

См. также:
Frank Smets
Journal of Monetary Economics. 2003.  Vol. 50. No. 6. P. 1293-1309. 
Frederic S. Mishkin, Klaus Schmidt-Hebbel
NBER Working Paper Series. 2001.  No. 8397.
Сергей Михайлович Дробышевский, Анна Михайловна Козловская, Павел Вячеславович Трунин
Pierpaolo Benigno, Gianluca Benigno
Journal of Monetary Economics. 2006.  Vol. 53. No. 3. P. 473-506. 
Paul D. Mizen, Mervyn K. Lewis