Forecasting inflation with an uncertain output gap

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe output gap (measuring the deviation of output from its potential) is a crucial concept in the monetary policy framework, indicating demand pressure that generates inflation. The output gap is also an important variable in itself, as a measure of economic fluctuations. However, its definition and estimation raise a number of theoretical and empirical questions. This paper evaluates a series of univariate and multivariate methods for extracting the output gap, and compares their value added in predicting inflation. The multivariate measures of the output gap have by far the best predictive power. This is in particular interesting, as they use information from data that are not revised in real time. We therefore compare the predictive power of alternative indicators that are less revised in real time, such as the unemployment rate and other business cycle indicators. Some of the alternative indicators do as well, or better, than the multivariate output gaps in predicting inflation. As uncertainties are particularly pronounced at the end of the calculation periods, assessment of pressures in the economy based on the uncertain output gap could benefit from being supplemented with alternative indicators that are less revised in real time.

The Usefulness of Output Gaps for Policy Analysis

“…However, the significance of this result is limited as the authors do not verify whether simpler models would have performed as well. For Norway, Bjørnland et al (2006) find that multivariate measures of the output gap in a Phillips-curve-type forecasting equation produce more accurate inflation forecasts than an AR benchmark model. However, alternative indicators of the cycle, such as the employment gap or an index of financial variables, are found to perform equally well and in some cases even better than the multivariate methods.…”

Identification and Real-Time Forecasting of Norwegian Business Cycles

“…Most studies, see for instance Bjørnland (2000), and Bjørnland et al (2008), analyze the growth cycle based on quarterly national accounts. To our knowledge, there are only two earlier studies aiming to date classical turning points in the Norwegian economy.…”

Estimating the Output Gap of Pakistan on Quarterly Frequency Using Structural Methods

“…In line with Bjørnland et al (2006), I estimate a three variable SVAR; I implement long run restrictions consistent with Blanchard and Quah (1989). Where, Blanchard and Quah (1989) use long run restrictions on a two variable model in VAR methodology by subjecting it to structural constraints in order to draw long run (permanent) shocks and short run (transitory) shocks to the system.…”

“…Clark (1987) and Harvey and Jaeger (1993) estimate output gap using this methodology and conclude in its favor. Recently Cayen and Van Norden (2004), Bjørnland et al (2006), Aroujo et al (2004), Adnan and Safdar (2008) conclude favorably for Unobserved components model in estimating output gap. It is worthwhile to note here that Unobserved components method and Multivariate HP filter method share some similar grounds as the output gap In both methods is estimated by sequentially evaluating the likelihood function using Kalman filter method (see Benes et al, 2004).…”