Uncovering the Hit List for Small Inflation Targeters: A Bayesian Structural Analysis

By Kam, Timothy; Lees, Kirdan et al. | Journal of Money, Credit & Banking, June 2009 | Go to article overview

Uncovering the Hit List for Small Inflation Targeters: A Bayesian Structural Analysis


Kam, Timothy, Lees, Kirdan, Liu, Philip, Journal of Money, Credit & Banking


IN THE RECENTLY POPULAR CLASS of dynamic stochastic general equilibrium (DSGE) models, private economic agents such as consumers and firms are often modeled as optimizing decision makers. However, central bank behavior is typically described by a reduced-form monetary policy rule rather than a set of deeper monetary policy objectives often institutionally defined. Empirical estimates obtained from reduced-form monetary policy rules are functions of both the underlying structure of the economy and policy objectives. Characterizing policy from the level of policy objectives allows one to distinguish changes in the policy rule that result from changes to structural parameters in the economy, from, changes in policy objectives.

Modeling the deeper central bank objectives enables us to empirically infer the importance a central bank places on particular institutionally defined monetary policy objectives such as inflation stabilization and output stabilization. In this paper, we apply this simple idea to a new empirical problem for small open economies. We treat the central bank as an optimizing agent, thus placing the central bank on the same footing as the other optimizing agents in the model economy. We identify the macroeconomic objectives of three of the earliest explicit small-open-economy inflation targeters--Australia, Canada, and New Zealand, over the period 1990Q1-2005Q3. We estimate the same DSGE model for each country and reverse engineer stabilization objectives that are conditioned on the structure of each economy.

Contributions. A considerable number of studies utilize loss function parameters for optimal monetary policy experiments (e.g., Rudebusch and Svensson 1999, Levin and Williams 2003, Del Negro and Schorfheide 2005). However, Dennis (2006) argues that typical loss function parameterizations may be inconsistent with the data. In particular, these yield aggressive policy rules that are inconsistent with the observed interest-rate-smoothing behavior documented in the literature (see Lowe and Ellis 1997).

This paper contributes to this debate by explicitly identifying the loss function parameters for three microfounded small open economies conditioned on historical data. In particular, we ask the questions of (i) whether our sample central banks explicitly care about stabilizing the real exchange rate and (ii) whether their policy preferences are similar overall. In doing so, our approach yields a slightly deeper insight into institutionally defined policy preferences. This is in contrast to empirical analyses (e.g., Lubik and Schorfheide 2007) that inquire into the behavioral responses of central banks. We also provide the link between our empirical analysis of uncovering what central bank preferences are and the resulting implication for policy behavior. We argue and show that it is straightforward to derive the mapping from preferences to equilibrium behavior (i.e., reduced-form policy rules) for the central banks, but the converse is not the case, if we begin the analysis from an ad hoc behavioral rule.

The results from our analysis will help inform monetary policy experiments seeking optimal policy rules for open economy inflation targeters. Estimates of macroeconomic policy objectives can potentially enhance both the transparency and accountability of the practical implementation of monetary policy. Most inflation-targeting central banks describe themselves as "flexible" in their approach to inflation targeting, implying central banks objectives embody factors beyond simply inflation. However, while central banks are often explicit about the macroeconomic variables they are concerned with, the trade-offs across these macroeconomic objectives are never elucidated. We believe transparency is enhanced by providing explicit statements of how alternative stabilization objectives are weighted (see Svensson 2005) and our analysis provides such statements.

Finally, historical estimates of stabilization objectives (conditioned on an explicit structural and microfounded model) provide a framework for central bank boards or government agencies tasked with assessing central bank performance. …

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