Publication: Estimating US persistent and transitory monetary shocks: implications for monetary policy
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2011-09
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Abstract
This paper proposes an estimation method for persistent and transitory monetary shocks using the
monetary policy modeling proposed in Andolfatto et al, [Journal of Monetary Economics, 55
(2008), pp.: 406-422]. The contribution of the paper is threefold: a) to deal with non-Gaussian
innovations, we consider a convenient reformulation of the state-space representation that enables
us to use the Kalman filter as an optimal estimation algorithm. Now the state equation allows
expectations play a significant role in explaining the future time evolution of monetary shocks; b)
it offers the possibility to perform maximum likelihood estimation for all the parameters involved
in the monetary policy, and c) as a consequence, we can estimate the conditional probability that a
regime change has occurred in the current period given an observed monetary shock. Empirical
evidence on US monetary policy making is provided through the lens of a Taylor rule, suggesting
that the Fed’s policy was implemented accordingly with the macroeconomic conditions after the
Great Moderation. The use of the particle filter produces similar quantitative and qualitative
findings. However, our procedure has much less computational cost.
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Kalman filter, Non-normality, Particle filter, Monetary policy