Advocates of quantitative easing (QE) policies have emphasized some evidence that structural models do not predict long-term asset yields as well as naive forecasts, implying that predictions of price reversals cannot be profitable and that QE effects are not transitory. The purpose of this study is to reconsider the out-of-sample forecasting performance of structural time series processes relative to that of a random walk with or without drift.
This study uses bivariate vector autoregression and Markov switching representations to generate out-of-sample forecasts of ten-year sovereign bond yields, when the information set is augmented by including the growth rate of the monetary base, and the estimation relies on monthly data from countries that have pursued unconventional policies over the last decade.
The results show that naive forecasts are not better than those of structural time series models, based on root mean squared errors, while the Markov model provides additional information on price reversals, through probabilistic inferences regarding policy regime switches, which can induce agents to counteract QE interventions and reduce their effectiveness.
The novel features of this work are the use of a large information set including the instrument of unconventional monetary policy, the use of a structural model (Markov process) that can really inform about potential asset price reversals and the use of a large sample over which QE policies have been pursued.
The author is indebted to two anonymous referees for valuable comments and suggestions. Of course, the author alone is responsible for any errors.
Kirikos, D.G. (2022), "Are quantitative easing effects transitory? Evidence from out-of-sample forecasts", Journal of Financial Economic Policy, Vol. 14 No. 6, pp. 811-822. https://doi.org/10.1108/JFEP-04-2022-0099
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