2015
DOI: 10.26509/frbc-ec-201503
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Measuring Inflation Forecast Uncertainty

Abstract: Looking across a range of statistical models, we consider the likely path of future inflation and the uncertainty surrounding the models' predictions. The models suggest that inflation is on a rising path, and while inflation forecast uncertainty is somewhat elevated relative to the norms of the last 20 years, core inflation uncertainty is relatively low. For both inflation rates, forecast uncertainty is much lower as of the first quarter of 2015 than it was around the Great Recession.

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Cited by 6 publications
(4 citation statements)
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References 24 publications
(16 reference statements)
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“…Interestingly, the patterns seen in the case of quarterly inflation provide stronger evidence of shifts in uncertainty over time (see Figure A13 in the appendix). Moreover, the broader movements in the uncertainty estimates implied by our density nowcasts for quarterly inflation are similar to uncertainty estimates reported elsewhere in the literature using stochastic volatility models (e.g., Knotek, Zaman, and Clark, 2015).…”
Section: Time-varying Properties Of the Grand Combination: Weights Usupporting
confidence: 86%
See 1 more Smart Citation
“…Interestingly, the patterns seen in the case of quarterly inflation provide stronger evidence of shifts in uncertainty over time (see Figure A13 in the appendix). Moreover, the broader movements in the uncertainty estimates implied by our density nowcasts for quarterly inflation are similar to uncertainty estimates reported elsewhere in the literature using stochastic volatility models (e.g., Knotek, Zaman, and Clark, 2015).…”
Section: Time-varying Properties Of the Grand Combination: Weights Usupporting
confidence: 86%
“…Combination methods that produce density estimates derived from a richer set of models tend to display a higher degree of skewness and kurtosis in the predictive densities. We also find evidence of time-varying variances (i.e., uncertainty in the nowcast estimates) that echo the broader patterns reported elsewhere in the inflation uncertainty literature using stochastic volatility models (e.g., Carriero, Clark, and Marcellino, 2019;Knotek, Zaman, and Clark, 2015).…”
Section: Inflationsupporting
confidence: 85%
“…3. As discussed in Knotek et al (2015), the size of realized shocks in most macroeconomic models can vary over time, but the shocks are assumed to be drawn from a distribution with a standard deviation that is fi xed. Models with stochastic volatility allow the standard deviation of the size of the shocks to change over time.…”
Section: Resultsmentioning
confidence: 99%
“…The forecasting superiority of these models is documented in the following recent studies: Clark, 2011;Faust and Wright, 2013;Clark andDoh, 2014, Chan, Clark, andKoop, 2015;and Tallman and Zaman, forthcoming. 2. See Stock and Watson, 2007;Clark, 2011;D'Agostino et al, 2013;and Tallman and Zaman, forthcoming. To get a sense of how forecast uncertainty differs between models with and without time-varying volatility see Knotek et al, 2015, who look at the evolution of infl ation forecast uncertainty across a variety of models including some with and without time-varying volatility. Three of the models used in this analysis were also used in that study.…”
Section: Footnotesmentioning
confidence: 99%