22 Years of inflation assessment and forecasting experience at the bulletin of EU & US inflation and macroeconomic analysis
Eva Senra
Authors registered in the RePEc Author Service: Antoni Espasa
DES - Working Papers. Statistics and Econometrics. WS from Universidad Carlos III de Madrid. Departamento de EstadÃstica
Abstract:
The Bulletin of EU & US Inflation and Macroeconomic Analysis (BIAM) is a monthly publication that has been reporting real time analysis and forecasts for inflation and other macroeconomic aggregates for the Euro Area, the US and Spain since 1994. The BIAM inflation forecasting methodology stands on working with useful disaggregation schemes, using leading indicators when possible and applying outliers' correction. The paper relates this methodology to corresponding topics in the literature and discusses the design of disaggregation schemes. It concludes that those schemes would be useful if they were formulated according to economic, institutional and statistical criteria aiming to end up with a set of components with very different statistical properties for which valid single-equation models could be built. The BIAM assessment, which derives from a new observation, is based on (a) an evaluation of the forecasting errors (innovations) at the components' level. It provides information on which sectors they come from and allows, when required, for the appropriate correction in the specific models. (b) In updating the path forecast with its corresponding fan chart. Finally, we show that BIAM real time Euro Area inflation forecasts compare successfully with the consensus from the ECB Survey of Professional Forecasters, one and two years ahead.
Keywords: Indirect; forecast; Outliers; Disaggregation (search for similar items in EconPapers)
JEL-codes: C13 (search for similar items in EconPapers)
Date: 2017-06
New Economics Papers: this item is included in nep-eec, nep-for, nep-mac and nep-mon
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:cte:wsrepe:24678
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