The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area

Busetti, Fabio; Caivano, Michele

doi:10.1007/s00181-015-0982-3

Cited by 109 publications

(5 citation statements)

References 17 publications

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“…16 One of the most important versions in modern macroeconomics is the so-called New Keynesian Phillips curve; see, for example, Galí and Gertler (1999) and Rudd and Whelan (2005). Recent empirical literature taking a less structural appoach and relying on various techniques from time series economectrics includes Svensson (2015), Busetti and Caivano (2016), Chan et al (2016) and Knotek and Zaman (2017).…”

Section: Other Measures Of Resource Utilizationmentioning

confidence: 99%

A note on the stability of the Swedish Phillips curve

Karlsson

Österholm

2019

Empir Econ

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We use Bayesian techniques to estimate bivariate VAR models for Swedish unemployment rate and inflation. Employing quarterly data from 1995Q1 to 2018Q3 and new tools for model selection, we compare models with time-varying parameters and/or stochastic volatility to specifications with constant parameters and/or covariance matrix. The evidence in favour of a stable dynamic relationship between the unemployment rate and inflation is mixed. Model selection based on marginal likelihood calculations indicates that the relation is time varying, whereas the use of the deviance information criterion suggests that it is constant over time; we do, however, note consistent evidence in favour of stochastic volatility. An out-of-sample forecast exercise is also conducted, but similarly provides mixed evidence regarding which model to favour. Importantly though, even if time-varying parameters are allowed for, our results do not suggest that the Phillips curve has been flatter in more recent years. This finding thereby questions the explanation that a flatter Phillips curve is the cause of the low inflation that Sweden has experienced in recent year. Keywords Inflation • Unemployment • Time-varying parameters • Stochastic volatility JEL Classification C11 • C32 • E32 We are grateful to Mikael Apel, Paola Di Casola, Henry Ohlsson, two anonymous referees, the editor, the associate editor and seminar participants at the Ministry of Finance (in Sweden), the 6th Swedish National Conference in Economics and the 10th Nordic Econometric Meeting for valuable comments. Rafael Barros De Rezende kindly provided data on the shadow rate and Joshua Chan generously shared Matlab code.

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Section: Other Measures Of Resource Utilizationmentioning

confidence: 99%

A note on the stability of the Swedish Phillips curve

Karlsson

Österholm

2019

Empir Econ

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“…1210 The growth rate of potential output should be as smooth as possible 11. We tried different calibrations and finally chose the one that, in our view, delivers a plausible long-run growth rate of real GDP 12. See Banca d'Italia (2016).…”

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confidence: 99%

Real and financial cycles: estimates using unobserved component models for the Italian economy

et al. 2019

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In this paper we examine the empirical features of both the business and financial cycles in Italy. We employ univariate and multivariate trend-cycle decompositions based on unobserved component models. Univariate estimates highlight the different cyclical properties (persistence, duration and amplitude) of real GDP and real credit to the private sector. Multivariate estimates uncover the presence of feedback effects between the real and financial cycles. At the same time, in the most recent period (2015-2016), the multivariate approach highlights a wider output gap than that estimated by the univariate models considered in this paper.JEL Classification: C32, E32, E44.

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“…First, the results presented in the paper are based on a standard HP filter with smoothing parameter λ = 1600 but the findings would be similar for other plausible values of λ. As an example, we consider the trend-cycle decomposition of euro area GDP estimated in Busetti and Caivano (2016) using Bayesian techniques with an informative prior for the cycle periodicity (in order to take into account the official business cycle chronology). A good approximation for that model is an HP filter with λ = 18500, 19 which implies wider and more persistent cyclical swings than for λ = 1600.…”

Section: Discussionmentioning

confidence: 99%

Domestic and Global Determinants of Inflation: Evidence from Expectile Regression*

2021

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The paper investigates the role of domestic and global determinants of euro area core inflation. We analyse the entire conditional distribution of inflation by estimating a Phillips curve type relationship using an expectile regression approach, extended to capture time-varying effects. The main findings are as follows. First, both the domestic and foreign output gap are significant drivers of euro area core inflation, once external demand pressures are properly orthogonalized in a modified measure of domestic gap. However, the inflationary impact of the domestic component is relatively stronger. Second, the domestic output gap has a bigger influence in the right tail of the conditional distribution of inflation. Third, adding international price pressures in the regression weakens the link between inflation and the foreign output gap. Fourth, in a time-varying perspective, there is an increase in the response of inflation to the domestic gap in the last decade but only at the lower quantiles. Overall, the evidence on the so-called "globalization hypothesis" is mixed: while the pass-through to inflation of foreign prices and the exchange rate increased over time at all quantiles, the impact of global slack remained broadly stable, particularly in the central part of the distribution.

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The trend–cycle decomposition of output and the Phillips curve: Bayesian estimates for Italy and the Euro area

Cited by 109 publications

References 17 publications

A note on the stability of the Swedish Phillips curve

A note on the stability of the Swedish Phillips curve

Real and financial cycles: estimates using unobserved component models for the Italian economy

Domestic and Global Determinants of Inflation: Evidence from Expectile Regression*

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