Lanne, Markku and Luoto, Jani (2010): Has U.S. Inflation Really Become Harder to Forecast?
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Recently Stock and Watson (2007) showed that since the mid-1980s it has been hard for backward-looking Phillips curve models to improve on simple univariate models in forecasting U.S. inflation. While this indeed is the case when the benchmark is a causal autoregression, little change in forecast accuracy is detected when a noncausal autoregression is taken as the benchmark. In this note, we argue that a noncausal autoregression indeed provides a better characterization of U.S. inflation dynamics than the conventional causal autoregression and it is, therefore, the appropriate univariate benchmark model.
|Item Type:||MPRA Paper|
|Original Title:||Has U.S. Inflation Really Become Harder to Forecast?|
|Keywords:||Inflation forecast; Noncausal time series; Phillips curve|
|Subjects:||C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods; Simulation Methods
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E31 - Price Level; Inflation; Deflation
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C23 - Models with Panel Data; Longitudinal Data; Spatial Time Series
|Depositing User:||Markku Lanne|
|Date Deposited:||09. Apr 2011 00:17|
|Last Modified:||14. Feb 2013 21:22|
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