Abstract
This paper introduces a model that addresses the key worldwide features of modern monetary policy making: the discreteness of policy interest rates both in magnitude and in timing, the preponderance of status quo decisions, policy inertia and regime switching. We capture them by developing a new dynamic discrete-choice model with switching among three latent policy regimes (dovish, neutral and hawkish), estimated via the Gibbs sampler with data augmentation. The simulations and an application to federal funds rate target demonstrate that ignoring these features leads to biased estimates, worse in- and out-of-sample fit, and qualitatively different inference. Using all Federal Open Market Committees (FOMC) decisions made both at scheduled and unscheduled meetings as sample observations, we model the Federal Reserves response to real-time data available right before each meeting, and control for the endogeneity of monetary policy shocks. The new model, fitted for Greenspans tenure, correctly predicts the directions of about 90% of the next decisions on the target rate (hike, no change, or cut) out of sample during Bernankes term including the status quo decisions after reaching the zero lower bound, while the conventional linear model fails to adequately tackle the zero bound and wrongly predicts further cuts.
Highlights
We develop a dynamic model of discrete ordered choice with lagged latent dependent variables among regressors and with time-varying transition probabilities of switching among three latent regimes interpreted in the interest-rate-setting context as easing, neutral and tight monetary policy stances
We develop a new dynamic discrete-choice model for monetary policy interest rates
Central banks typically adjust policy rates by discrete increments and often leave them unchanged in different economic circumstances; if central banks make a change, it is usually followed by further changes in the same direction
Summary
We develop a dynamic model of discrete ordered choice with lagged latent dependent variables among regressors and with time-varying transition probabilities of switching among three latent regimes interpreted in the interest-rate-setting context as easing, neutral and tight monetary policy stances. The observed discrete change yt is conditional on a latent discrete variable st∗ (coded as −1, 0, or 1 if the central bank policy regime is easing, neutral or tight, respectively) Both yt and st∗ are determined in an ordered probit fashion as yt |(st∗ = −1) = j yt |(st∗ = 0) = 0, yt |(st∗ = 1) = j if if c−j−1 < rt−∗ ≤ c−j for j ≤ 0,. The technical problems with the computation of the equilibria, caused by the discreteness and nonlinearity of the policy rule, would become exacerbated by the unobserved switching among three latent regimes
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