Estimating the Output Gap Using Business Survey Data - A Bivariate Structural Time Series Model for the German Economy
AbstractThis paper deals with the estimation of the output gap. We use uni- and bivariate unobserved components models in order to decompose the observed German GDP-series into trend, cycle and seasonal components. The results show that using the ifo business assessment variable as an indicator for the cycle the estimation of the output gap is much more precise and out-of-sample forecasts exhibit smaller prediction errors.
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Bibliographic InfoPaper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 233.
Date of creation: 2000
Date of revision:
Output gap; unobserved component models; survey data;
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- Erich Langmantel, 2001. "Verlaufen die Konjunkturzyklen im Euro-Land ähnlich?," Ifo Schnelldienst, Ifo Institute for Economic Research at the University of Munich, vol. 54(06), pages 53-54, October.
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- Sascha O. Becker & Klaus Wohlrabe, 2008. "European Data Watch: Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Schmollers Jahrbuch : Journal of Applied Social Science Studies / Zeitschrift für Wirtschafts- und Sozialwissenschaften, Duncker & Humblot, Berlin, vol. 128(2), pages 307-319.
- Sascha O. Becker & Klaus Wohlrabe, 2007. "Micro Data at the Ifo Institute for Economic Research – The “Ifo Business Survey”, Usage and Access," Ifo Working Paper Series Ifo Working Paper No. 47, Ifo Institute for Economic Research at the University of Munich.
- Gebhard Flaig, 2002. "Unoberserved Components Models for Quarterly German GDP," CESifo Working Paper Series 681, CESifo Group Munich.
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