Failing to Forecast Low Inflation and Phillips Curve Instability: A Euro‐Area Perspective

Abstract

Professional forecasters failed to anticipate the sharp fall in inflation in the euro area in 2013-2014. We investigate whether this forecasting failure can be partly attributed to a break in the elasticity of inflation to the output gap. Using structural break tests and time-varying parameter models, we find that this elasticity has indeed increased substantially in the past 2 years. We offer two (observationally equivalent) interpretations of this result. The first is that the increase in the cyclicality of inflation has stemmed from lower nominal rigidities or weaker strategic complementarities in price setting. A second possibility is that current output gap estimates are understating the amount of spare capacity in the economy. We estimate that, in order to reconcile the observed fall in inflation with the historical correlation between consumer prices and the business cycle, the output gap should be wider by around one third.

The Slope of the Euro Area Phillips Curve: Always and Everywhere the Same?

“…Figure 1 illustratively plots HICP inflation and survey measures of expected inflation from Consensus Economics for the EA. As reported by Constâncio (2015), inflation forecasts indeed underestimate inflation in 2010-12, but overestimate it since 2013 (also compare Riggi and Venditti (2015)) (Note 3).…”

“…Ireland, Greece, Spain, Cyprus, Portugal, and Slovenia. Further, Riggi and Venditti (2015) investigate the recent 2013/14 overshooting of Consensus Economics inflation forecasts and conclude either confirmed increases in slope coefficients in the respective period or imprecise measurement of current output gaps to be the reason.…”

Has the wage Phillips curve changed in the euro area?

“…Following Riggi and Venditti (2015), we resort to the kernel-based non-parametric estimators proposed by Giraitis et al (2013). This type of estimators is based on the idea Values reported are the average across h = 0,…,4 where the result of the test is coded with 1 if the test rejects at the 10% the null hypothesis of constant parameters in favour of time-varying parameters, with 0 if the null hypothesis of constant parameters cannot be rejected at the 10% that in the presence of structural breaks, older observations should be discounted more than more recent ones.…”

“…On the one hand, some papers show that in recent years, the negative relationship between price inflation and economic slack has become stronger (see e.g. Giannone et al 2014;Riggi and Venditti 2015). Yet the twin puzzles observed in the USA occurred also in the Euro area (see Ciccarelli and Osbat 2017).…”

I Will Survive. Pricing Strategies of Financially Distressed Firms

“… Also in Bodnar et al (2017), which also exploit the WDN survey, principal component analysis has been applied to the variables on …nancial constraints; besides, the same work provides a validation of the replies given by …rms using external sources 25. …”