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dc.contributor.authorArmah, Nii Ayien_US
dc.contributor.authorSwanson, Normanen_US
dc.date.accessioned2011-06-14en_US
dc.date.accessioned2012-06-25T11:57:26Z-
dc.date.available2012-06-25T11:57:26Z-
dc.date.issued2011en_US
dc.identifier.urihttp://hdl.handle.net/10419/59477-
dc.description.abstractCentral banks regularly monitor select financial and macroeconomic variables in order to obtain early indication of the impact of monetary policies. This practice is discussed on the Federal Reserve Bank of New York website, for example, where one particular set of macroeconomic indicators is given. In this paper, we define a particular set of indicators; that is chosen to be representative of the typical sort of variable used in practice by both policy-setters and economic forecasters. As a measure of the adequacy; of the indicators, we compare their predictive content with that of a group of observable factor proxies selected from amongst 132 macroeconomic and financial time series, using the diffusion index methodology of Stock and Watson (2002a,b) and the factor proxy methodology of Bai and Ng (2006a,b) and Armah and Swanson (2010). The variables that we predict are output growth and inflation, two representative variables from our set of indicators that are often discussed when assessing the impact of monetary policy. Interestingly, we find that thc indicators are all contained within the set the observable variables that proxy our factors. Our findings, thus, support the notion that a judiciously chosen set of macroeconomic indicators can effectively provide the same macroeconomic policy-relevant information as that contained in a largescale time series dataset. Of course, the large-scale datasets are still required in order to select the key indicator variables or confirm one's prior choice of key variables. Our findings also suggest that certain yield spreads; are also useful indicators. The particular spreads that we find to be useful are the difference between Treasury or corporate yields and the federal funds rate. After conditioning on these variables, traditional spreads, such as the yield curve slope and the reverse yield gap are found to contain no additional marginal predictive content. We also find that the macroeconomic indicators (not including spreads) perform best when forecasting inflation in non-volatile time periods, while inclusion of our spread variables improves predictive accuracy in times of high volatility.en_US
dc.language.isoengen_US
dc.publisherDep. of Economics, Rutgers, the State Univ. of New Jersey New Brunswick, NJen_US
dc.relation.ispartofseriesWorking Papers, Department of Economics, Rutgers, the State University of New Jersey 2011,15en_US
dc.subject.jelC22en_US
dc.subject.jelC33en_US
dc.subject.jelC51en_US
dc.subject.ddc330en_US
dc.subject.keyworddiffusion indexen_US
dc.subject.keywordfactoren_US
dc.subject.keywordfederal reserve banken_US
dc.subject.keywordforecasten_US
dc.subject.keywordmacroeconometricsen_US
dc.subject.keywordmonetary policyen_US
dc.subject.keywordparameter estimation erroren_US
dc.subject.keywordproxyen_US
dc.subject.stwWirtschaftsindikatoren_US
dc.subject.stwKonjunkturindikatoren_US
dc.subject.stwGeldpolitiken_US
dc.subject.stwWirkungsanalyseen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwSchätztheorieen_US
dc.subject.stwTheorieen_US
dc.subject.stwSchätzungen_US
dc.subject.stwUSAen_US
dc.titleSome variables are more worthy than others: New diffusion index evidence on the monitoring of key economic indicatorsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn662052536en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Working Papers, Department of Economics, Rutgers University

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