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Empirical Economics

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13-07-2020

Is the future really observable? A practical approach to model monetary policy rules

Author: Hardik A. Marfatia

Published in: Empirical Economics | Issue 3/2021

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Abstract

We take a practical approach to model the forward-looking monetary policy rule. Unlike existing studies, we recognize that the forward-looking components—future inflation and output growth—are intrinsically unobserved at the time policy formulation. Using the unobserved components framework, we extract the latent components of the policy rule from the short-term and long-term Greenbook forecasts, both individually and in combination, and jointly estimate the policy parameters. We also consider correlations between different components and combine the forecasts from the survey of professional forecasters and the inflation index bonds market. Evidence suggests that the Federal Reserve follows an inflation-tilted policy rule and the long-term state of economy gets a higher weight than the short term. Also, the policy reaction is more aggressive when interconnections between different components of the policy rule are considered.

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Note that the objective of the paper is to develop a new approach to model forward-looking MP function, and not to explicitly test and/or estimate the extent of bias in the estimates.

We would like to highlight that the new approach is remarkably different from the existing studies. Further, the sample period is also different. Hence, one should compare results with a grain of salt.

We consider different sources of forecasts to model MP function in a separate section below.

We acknowledge that Morley et al. (2003) models the cyclical component of inflation as an AR(2) process. Though this is related, it differs slightly in the present context. However, it is important to recognize that the approach used in the paper is novel and in the absence of any preset benchmarks, it is only appropriate to ensure that the model specifications meet the conditions laid by the literature on unobserved component modeling.

Introducing higher-order dynamics is both unnecessary and unwanted. First, it increases the curse of dimensionality, and second, we have tested and found that higher-order lags are statistically insignificant. Thus, it will only lead to losing the important degrees of freedom. We further study interconnections between different components of the model. This also acts as a robustness check of our results.

The only limitation of using Greenbook forecasts is that the data are available exclusively to the Board of Governors staffers, which are publicly available with a 5-year lag. This restricts the use of Greenbook forecasts as a part of the information set of market participants. Nikolsko-Rzhevskyy (2011) provides an alternative approach to overcome the data availability limitation of using Greenbook forecast as a proxy for modeling monetary policy function. The study separately estimates inflation and output forecasts from different model specifications and uses forecasts as close as possible to the Greenbook to estimate the Taylor rule. This strategy overcomes the limitation of the 5-year lag in availability of the Greenbook data.

The results are robust to alternate choice of shadow rates proposed in the literature, for example, Bauer and Rudebusch 2016. Further, one can argue that the estimates of monetary function have an element of uncertainty to the extent the shadow interest rate is seen as a noisy reading of the monetary policy stance. However, the robustness testing of the model provides evidence against the argument that uncertainty in estimates of monetary function is due to the use of a particular shadow rate data. Nevertheless, this does not circumvent the issue that the estimates are conditioned on the shadow rate data used for the ZLB period. The robustness test section elaborates on these issues.

See, for example, Orphanides (2001, (2002, (2004).

There is a rich literature on the links between uncertainty and effectiveness of policy (Brainard 1967; Clarida et al. 1999; Rudebusch 2001; Onatski and Stock 2002; Marfatia 2014, 2015; among others).

Since the paper does not aim at providing the best forecast of the monetary policy rule, which of course is important in itself, we keep the forecasting exercise for future explorations. An in-depth out-of-sample forecasting analysis is also warranted because of the operational constraint that the Greenbook data are publicly available only with a 5-year lag.

Interested researcher should, however, note that HM rate is conditioned on the proxy measure of policy stance during the ZLB period. Though we perform robustness tests using alternative proxy measure in the ZLB period, the HM rate should be interpreted keeping this limitation in mind that it does not completely circumvent the issue that the estimates are conditioned on a stance of policy at the ZLB. We acknowledge anonymous referee(s) for pointing out this limitation.

Though this was in the context of decomposing the level of GDP into its trend and cycle, one can relate this in the present case.

Since the investors intent is to earn returns only in real terms, any difference between a nominal bond (which provides nominal returns) and inflation-protected bond (which provides real returns) should, in theory, exclusively be attributed to future inflation expectations.

Break even inflation rates are also used to model inflation expectation in the new Keynesian Phillips curve (Marfatia 2018).

In interpreting the results, caution is warranted because break-even inflation rates are only available after 2003. Hence, the sample period is different for the results presented in columns 9–10 of Table 4.

For complementary evidence on alternative specifications for computing shadow rates, see Bauer and Rudebusch (2016), Krippner (2013), Christensen and Rudebusch (2014), Ichiue and Ueno (2015), and Kim and Singleton (2012).

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Title: Is the future really observable? A practical approach to model monetary policy rules
Author: Hardik A. Marfatia
Publication date: 13-07-2020
Publisher: Springer Berlin Heidelberg
Published in: Empirical Economics / Issue 3/2021
Print ISSN: 0377-7332
Electronic ISSN: 1435-8921
DOI: https://doi.org/10.1007/s00181-020-01910-7

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