IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!)

Citations for "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence"

by Kholodilin Konstantin Arkadievich & Siliverstovs Boriss

For a complete description of this item, click here. For a RSS feed for citations of this item, click here.
as in new window

  1. Christian Seiler, 2012. "On the Robustness of the Balance Statistics with respect to Nonresponse," Ifo Working Paper Series Ifo Working Paper No. 126, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  2. Katja Drechsel & Rolf Scheufele, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10, Halle Institute for Economic Research.
  3. Boriss Siliverstovs & Konstantin A. Kholodilin, 2010. "Assessing the Real-Time Informational Content of Macroeconomic Data Releases for Now-/Forecasting GDP: Evidence for Switzerland," Discussion Papers of DIW Berlin 970, DIW Berlin, German Institute for Economic Research.
  4. Konstantin Arkadievich Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2008. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(2), pages 195-207.
  5. Drechsel, Katja & Scheufele, Rolf, 2010. "Should We Trust in Leading Indicators? Evidence from the Recent Recession," IWH Discussion Papers 10/2010, Halle Institute for Economic Research (IWH).
  6. repec:jns:jbstat:v:227:y:2007:i:1:p:87-101 is not listed on IDEAS
  7. David Iselin & Boriss Siliverstovs, 2016. "Using newspapers for tracking the business cycle: a comparative study for Germany and Switzerland," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1103-1118, March.
  8. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52, July.
  9. Klaus Abberger & Klaus Wohlrabe, 2006. "Einige Prognoseeigenschaften des ifo Geschäftsklimas - Ein Überblick über die neuere wissenschaftliche Literatur," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
  10. Robert Lehmann & Klaus Wohlrabe, 2015. "Forecasting GDP at the Regional Level with Many Predictors," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 226-254, 05.
  11. Dreger, Christian & Kholodilin, Konstantin A. & Ulbricht, Dirk & Fidrmuc, Jarko, 2016. "Between the hammer and the anvil: The impact of economic sanctions and oil prices on Russia’s ruble," Journal of Comparative Economics, Elsevier, vol. 44(2), pages 295-308.
  12. Katja Drechsel & Rolf Scheufele, 2012. "The Financial Crisis from a Forecaster’s Perspective," Credit and Capital Markets, Credit and Capital Markets, vol. 45(1), pages 1–26.
  13. Klaus Abberger & Sascha O. Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung: Bestand, Verwendung, Zugang," Ifo Working Paper Series Ifo Working Paper No. 44, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  14. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators under Real-Time Condition," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 54(4), pages 293-318.
  15. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
  16. Drechsel, Katja & Scheufele, Rolf, 2012. "The performance of short-term forecasts of the German economy before and during the 2008/2009 recession," International Journal of Forecasting, Elsevier, vol. 28(2), pages 428-445.
  17. Klaus Wohlrabe, 2011. "Konstruktion von Indikatoren zur Analyse der wirtschaftlichen Aktivität in den Dienstleistungsbereichen," ifo Forschungsberichte, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 55.
  18. Staszewska-Bystrova Anna, 2013. "Modified Scheffé’s Prediction Bands," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(5-6), pages 680-690, October.
  19. Selen Baser Andic & Fethi Ogunc, 2015. "Variable Selection for Inflation : A Pseudo Out-of-sample Approach," Working Papers 1506, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  20. Dovern, Jonas, 2006. "Predicting GDP components : do leading indicators increase predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy (IfW).
  21. Anna Scharschmidt & Klaus Wohlrabe, 2011. "Sektorale Prognosen im Verarbeitenden Gewerbe," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
  22. Jonas Dovern, 2006. "Predicting GDP Components. Do Leading Indicators Increase Predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy.
  23. Schumacher Christian, 2011. "Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 28-49, February.
  24. Christian Seiler, 2014. "On the robustness of balance statistics with respect to nonresponse," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing,Centre for International Research on Economic Tendency Surveys, vol. 2014(2), pages 45-62.
  25. 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.
  26. Gerit Vogt, 2009. "Konjunkturprognose in Deutschland. Ein Beitrag zur Prognose der gesamtwirtschaftlichen Entwicklung auf Bundes- und Länderebene," ifo Beiträge zur Wirtschaftsforschung, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 36, July.
  27. Christian Aßmann & Jens Hogrefe & Roman Liesenfeld, 2009. "The decline in German output volatility: a Bayesian analysis," Empirical Economics, Springer, vol. 37(3), pages 653-679, December.
  28. Christian Seiler, 2014. "The determinants of unit non-response in the Ifo Business Survey," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 8(3), pages 161-177, September.
  29. Jan Grossarth-Maticek & Johannes Mayr, 2008. "Medienberichte als Konjunkturindikator," Ifo Schnelldienst, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 61(07), pages 17-29, 04.
  30. repec:zbw:iwhdps:10-10 is not listed on IDEAS
  31. Wong, Shirly Siew-Ling & Puah, Chin-Hong & Abu Mansor, Shazali & Liew, Venus Khim-Sen, 2012. "Early warning indicator of economic vulnerability," MPRA Paper 39944, University Library of Munich, Germany.
  32. Christina Ziegler, 2009. "Testing Predicitive Ability of Business Cycle Indicators for the Euro Area," Ifo Working Paper Series Ifo Working Paper No. 69, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  33. 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 - Leibniz Institute for Economic Research at the University of Munich.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.