Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/19497
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dc.contributor.authorGlück, Heinzen_US
dc.contributor.authorSchleicher, Stefan P.en_US
dc.date.accessioned2009-01-28T15:58:59Z-
dc.date.available2009-01-28T15:58:59Z-
dc.date.issued2004en_US
dc.identifier.urihttp://hdl.handle.net/10419/19497-
dc.description.abstractWe start from the assertion that a useful monetary policy design should be founded onmore realistic assumptions about what policymakers can know at the time when policydecisions have to be made. Since the Taylor rule – if used as an operational device -implies a forward looking behaviour, we analyze the reliability of the input information.We investigate the forecasting performance of OECD projections for GDP growth ratesand inflation. We diagnose a much better forecasting record for inflation rates comparedto GDP growth rates, which for most countries are almost uninformative at the time aTaylor rule should sensibly be applied. Using this data set, we find significantdifferences between Taylor rules estimated over revised data compared to real-timedata. There is evidence that monetary policy seems to react more actively in real timethan rules estimated over revised data suggest.Given the evidence of systematic errors in OECD forecasts, in a next step we attempt tocorrect for these forecast biases and check to which extent this can lower the errors ininterest rate policy setting. An ex-ante simulation for the years 1991 to 2001 supportsthe proposal that correcting for forecast errors and biases based on an error model canlower the resulting policy error in interest rate setting for most countries underconsideration. In addition we investigate to what extent structural changes in the policyreaction behaviour can be handled with moving instead of expanding samples.Our results point out that the information set available needs a careful examinationwhen applied to instrument rules like those of the Taylor type. Limited forecast qualityand significant data revisions recommend a more sophisticated handling of the datedinformation, for which we present an operational procedure that has the potential ofreducing the risk of severe policy errors.en_US
dc.language.isoengen_US
dc.publisher|aDeutsche Bundesbank |cFrankfurt a. M.-
dc.relation.ispartofseries|aDiscussion paper Series 1 / Volkswirtschaftliches Forschungszentrum der Deutschen Bundesbank |x2004,30en_US
dc.subject.jelC82en_US
dc.subject.jelC53en_US
dc.subject.jelE52en_US
dc.subject.ddc330en_US
dc.subject.keywordMonetary policy rulesen_US
dc.subject.keywordeconomic forecastingen_US
dc.subject.keywordOECDen_US
dc.subject.keywordreal-time dataen_US
dc.subject.stwKonjunkturprognoseen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwStatistischer Fehleren_US
dc.subject.stwTaylor-Regelen_US
dc.subject.stwGeldpolitiken_US
dc.subject.stwSchätzungen_US
dc.subject.stwG-7-Staatenen_US
dc.titleForecast quality and simple instrument rules: a real-time data approachen_US
dc.typeWorking Paperen_US
dc.identifier.ppn473006650en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:bubdp1:2296-

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