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Forecasting Inflation Using the Phillips Curve : Evidence from Swedish Data

Gabrielyan, Diana - 2016

This paper studies the forecasting ability of various Phillips curve specifications in a pseudo out-of-sample exercise for Swedish inflation over the period 1980-2014. Three measures of inflation are considered –– headline inflation, underlying inflation, GDP deflator inflation, in addition...

Persistent link: https://www.econbiz.de/10012981015

The possible unemployment cost of average inflation below a credible target : a replication study of Svensson (American Economic Journal: Macroeconomics, 2015)

Oraby, Ramy - In: Journal of comments and replications in economics 1 (2022), pp. 1-21

United States. Overall, the replication exercise successfully confirms the conclusions of Svensson (2015). In both Sweden and … long run Phillips curve recorded -0.75 in Sweden and -0.23 in the United States. While the average inflation rate in the … United States was very close to its targeted level, the average inflation rate in Sweden was 0.6 per- centage points below …

Persistent link: https://www.econbiz.de/10013179358

Testing near-rationality using detailed survey data

Bryan, Michael F.; Palmqvist, Stefan Ulf - 2005

detailed surveys of household inflation expectations for the United States and Sweden, we find that the data are generally … broad, qualitative terms. Moreover, the combination of a low-inflation environment and an inflation target in Sweden has …

Persistent link: https://www.econbiz.de/10011585061

Trend-cycle decomposition of output and euro area inflation forecasts : a real-time approach based on model combination

Guérin, Pierre; Maurin, Laurent; Mohr, Matthias - In: Macroeconomic dynamics 19 (2015) 2, pp. 363-393

Persistent link: https://www.econbiz.de/10011308645

Forecasting US inflation using Markov dimension switching

Prüser, Jan - 2017

This study considers Bayesian variable selection in the Phillips curve context by using the Bernoulli approach of Korobilis (2013a). The Bernoulli model, however, is unable to account for model change over time, which is important if the set of relevant predictors changes over time. To tackle...