Underlying Inflation in a Dsge Model

ALVES, FELIPE ALDUINO

doi:10.17771/pucrio.acad.37298

Cited by 1 publication

(2 citation statements)

References 12 publications

(18 reference statements)

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“…The reduction of noise helps explain why Phillips curves estimated with, e.g., trimmed-mean inflation, are much more successful. To our knowledge,Alves (2014) is the only extant study using trimmed inflation in a DSGE model 2. In like manner, the trimmed-mean PCE has been shown to be a very good signal of the MTT in PCE inflation; seeMertens (2016).…”

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confidence: 90%

“…These two series have been shown to be useful signals of the MTT in CPI inflation. 2 For this reason, these and other similar measures have been gaining traction and are increasingly used in empirical studies, not only in the forecasting context (e.g., Smith, 2004 Schoenle and Smith 2023) but also in many other contexts as well, including: establishing and testing the robustness of stylized inflation facts (Bryan and Cecchetti, 1999;Verbrugge, 1999;Fang, Miller and Yeh, 2010); understanding inflation uncertainty (Metiu and Prieto, 2023); discriminating between models of price adjustment (Ashley and Ye, 2012); locating a stable Phillips curve (Ball and Mazumder, 2011;Stock and Watson, 2020;Ashley and Verbrugge, 2023); studying the effects of oil supply shocks (Kilian, 2008); understanding inflation expectations and their relationship to inflation (Verbrugge and Zaman, 2021); and understanding post-Great Recession and post-COVID inflation dynamics (Ball and Mazumder, 2011;Mazumder, 2018;Ball et al, 2021; Ball, Leigh, and Mishra 2022; Verbrugge and Zaman 2023b; Cotton et al, 2023). They have also been suggested as a superior measure for monetary policy targeting and communication (Cecchetti and Groshen, 2001; Dolmas and Koenig, 2019; Verbrugge, 2022).…”

Section: Introductionmentioning

confidence: 99%

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The Effect of Component Disaggregation on Measures of the Median and Trimmed-Mean CPI

Garciga,

Verbrugge,

Zaman

2024

Working Paper (Federal Reserve Bank of Cleveland)

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For decades, the Federal Reserve Bank of Cleveland (FRBC) has produced median and trimmed-mean consumer price index (CPI) measures. These have proven useful in various contexts, such as forecasting and understanding post-COVID inflation dynamics. Revisions to the FRBC methodology have historically involved increasing the level of disaggregation in the CPI components, which has improved accuracy. Thus, it may seem logical that further disaggregation would continue to enhance its accuracy. However, we theoretically demonstrate that this may not necessarily be the case. We then explore the empirical impact of further disaggregation along two dimensions: shelter and non-shelter components. We find that significantly increasing the disaggregation in the shelter indexes, when combined with only a slight increase in non-shelter disaggregation, improves the ability of the median and trimmed-mean CPI to track the medium-term trend in CPI inflation and marginally increases predictive power over future movements in CPI inflation. Finally, we examine the practical implications of our preferred degree of disaggregation. Our preferred measure of the median CPI suggests that trend inflation was lower pre-pandemic, while both our preferred median and trimmed-mean measures suggest a faster acceleration in trend inflation in 2021. We also find that higher disaggregation marginally weakens the Phillips curve relationship between median CPI inflation and the unemployment gap, though it remains statistically significant.

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confidence: 90%