Does the Phillips curve help to forecast euro area inflation?

Bańbura, Marta; Bobeica, Elena

doi:10.1016/j.ijforecast.2021.12.001

Cited by 11 publications

(4 citation statements)

References 67 publications

(100 reference statements)

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“…Despite being much more sophisticated than the AO model, the limited performance of the univariate UCSV model is in line with the literature (see, e.g. Jarocinski and Lenza 2018 and Banbura and Bobeica 2023).…”

Section: Resultssupporting

confidence: 85%

Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter*

Martins,

Verona

2024

Oxf Bull Econ Stat

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We forecast US inflation with a new Keynesian Phillips curve (NKPC) in the frequency domain. Our method consists of decomposing the time series of inflation and its NKPC predictors into several frequency bands, forecasting separately each frequency component of inflation, and then summing up those forecasts to obtain the forecast for aggregate inflation. We find that (i) accurately forecasting the low frequency of inflation is, on average, crucial to successfully forecast inflation; (ii) our NKPC low‐frequency forecast model consistently and significantly outperforms the time‐series NKPC and standard benchmark models; (iii) the low frequencies of inflation expectations and unemployment are the key predictors; and (iv) optimally switching on / off the forecasts of each frequency components of inflation at each period allows to outstandingly track inflation and show that all frequencies of inflation matter.

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Section: Resultssupporting

confidence: 85%

Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter*

Martins,

Verona

2024

Oxf Bull Econ Stat

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“…where infl is the inflation rate for country i at time t, GDP is real GDP (Deniz et al, 2016), GSF denotes global supply factors, credit shows domestic liquidity (Cardoso and Vieira, 2016), energy is global oil prices (Bala and Chin, 2018), non-energy indicates commodity prices (Forbes, 2019), GGDP is global GDP (Forbes, 2019), rer denotes the real exchange rate defined as the real effective rate (Sek et al, 2015), open shows trade openness (Deniz et al, 2016), ucl defines unit labor cost (Mohanty and Klau, 2001), and unempl proxies the economic slack (Banbura and Bobeica, 2023). DUMFIN is a global financial crisis dummy (taking one from 2008:3 to 2009:4, and zero otherwise), DUMCOV is a COVID-19 dummy (taking one from 2020:1 to 2022:4, and zero otherwise), and DUMUKR is a Russian-Ukraine conflict dummy (taking one from 2022:1 to 2022:4, and zero otherwise).…”

Section: Resultsmentioning

confidence: 99%

Eurozone inflation: fresh projections from global factors

Apergis

2024

Econ Bus Lett

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This study identifies the contributions of global factors in determining eurozone inflation. The analysis makes use of an augmented Phillips curve model of inflation, as well as panel data estimates. The findings document the importance of such factors in forecasting inflation, thus, confirming the substantial role of external factors in eurozone inflation. The findings survived certain model specifications. Therefore, monetary, and fiscal policymakers should explicitly consider both domestic and global conditions to anchor inflation expectations in forming specific strategies for taming inflation expectations.

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“…Giraitis et al (2013) adopted a rolling window of 20 or 30 quarters to forecast 97 US quarterly macroeconomic series from 1970 to 2008, including price level and money supply. Bańbura and Bobeica (2023) used a rolling window of 20 quarters to forecast the quarter‐on‐quarter inflation in the euro area from 1994 to 2018. Rossi and Inoue (2012), however, found that different window sizes may affect forecasting performances, suggesting that the window size could be important for forecasting accuracy.…”

Section: Literature Reviewmentioning

confidence: 99%

Inflation forecasting with rolling windows: An appraisal

Hall,

Tavlas,

Wang

et al. 2024

Journal of Forecasting

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We examine the performance of rolling windows procedures in forecasting inflation. We implement rolling windows augmented Dickey–Fuller (ADF) tests and then conduct a set of Monte Carlo experiments under stylized forms of structural breaks. We find that as long as the nature of inflation is either stationary or non‐stationary, popular varying‐length window techniques provide little advantage in forecasting over a conventional fixed‐length window approach. However, we also find that varying‐length window techniques tend to outperform the fixed‐length window method under conditions involving a change in the inflation process from stationary to non‐stationary, and vice versa. Finally, we investigate methods that can provide early warnings of structural breaks, a situation for which the available rolling windows procedures are not well suited.

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Does the Phillips curve help to forecast euro area inflation?

Cited by 11 publications

References 67 publications

Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter*

Forecasting Inflation with the New Keynesian Phillips Curve: Frequencies Matter*

Eurozone inflation: fresh projections from global factors

Inflation forecasting with rolling windows: An appraisal

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