IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_1202.html
   My bibliography  Save this paper

Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey

Author

Listed:
  • Thomas A. Knetsch

Abstract

Inventory fluctuations are an important phenomenon in business cycles. However, the preliminary data on inventory investment as published in the German national accounts are tremendously prone to revision and therefore ill-equipped to diagnose the current stance of the inventory cycle. The Ifo business survey contains information on the assessments of inventory stocks in manufacturing as well as in retail and wholesale trade. Static factor analysis and a method building on canonical correlations are applied to construct a composite index of inventory fluctuations. Based on recursive estimates, the different variants are assessed as regards the stability of the weighting schemes and the ability to forecast the "true" inventory fluctuations better than the preliminary official releases.

Suggested Citation

  • Thomas A. Knetsch, 2004. "Evaluating the German Inventory Cycle – Using Data from the Ifo Business Survey," CESifo Working Paper Series 1202, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_1202
    as

    Download full text from publisher

    File URL: http://www.cesifo-group.de/DocDL/cesifo1_wp1202.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Zarnowitz, Victor, 1985. "Recent Work on Business Cycles in Historical Perspective: A Review of Theories and Evidence," Journal of Economic Literature, American Economic Association, vol. 23(2), pages 523-580, June.
    2. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 631-653.
    3. Doz, C. & Lenglart, F., 1998. "Analyse factorielle dynamique: test du nombre de facteurs, estimation, et application a l'enquete de conjoncture dans l'industrie," Papers 9831, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..
    4. N. Gregory Mankiw & Matthew D. Shapiro, 1986. "News or Noise? An Analysis of GNP Revisions," NBER Working Papers 1939, National Bureau of Economic Research, Inc.
    5. Victor Zarnowitz, 1984. "Recent Work on Business Cycles in Historical Perspective: Review of Theories and Evidence," NBER Working Papers 1503, National Bureau of Economic Research, Inc.
    6. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    7. West, Kenneth D, 1996. "Asymptotic Inference about Predictive Ability," Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
    8. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    9. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Alan S. Blinder & Louis J. Maccini, 1991. "Taking Stock: A Critical Assessment of Recent Research on Inventories," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 73-96, Winter.
    12. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
    13. Vahid, Farshid & Engle, Robert F., 1997. "Codependent cycles," Journal of Econometrics, Elsevier, vol. 80(2), pages 199-221, October.
    14. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 369-380, October.
    15. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    16. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
    17. James G. MacKinnon, 1990. "Critical Values for Cointegration Tests," Working Papers 1227, Queen's University, Department of Economics.
    18. Engle, Robert F & Kozicki, Sharon, 1993. "Testing for Common Features: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(4), pages 393-395, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Klaus Abberger & Sascha Becker & Barbara Hofmann & Klaus Wohlrabe, 2007. "Mikrodaten im ifo Institut für Wirtschaftsforschung – Bestand, Verwendung und Zugang," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 1(1), pages 27-42, June.
    2. Knetsch, Thomas A., 2004. "The Inventory Cycle of the German Economy," Discussion Paper Series 1: Economic Studies 2004,09, Deutsche Bundesbank.
    3. 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.

    More about this item

    Keywords

    inventory investment; revisions; composite indices; canonical correlation; factor models; national accounts data; Ifo business survey; Germany;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_1202. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Klaus Wohlrabe). General contact details of provider: http://edirc.repec.org/data/cesifde.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.