IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-13-00073.html
   My bibliography  Save this article

Liquidity in the liquidity crisis: evidence from Divisia monetary aggregates in Germany and the European crisis countries

Author

Listed:
  • Makram El-shagi

    (California State University - Long Beach & Halle Institute for Economic Research)

  • Logan J Kelly

    (University of Wisconsin)

Abstract

While there has been much discussion of the role of liquidity in the recent financial crises, there has been little discussion of the use of macroeconomic aggregation techniques to measure total liquidity available to the market. In this paper, we provide an approximation of the liquidity development in six Euro area countries from 2003 to 2013. We show that properly measured monetary aggregates contain significant information about liquidity risk.

Suggested Citation

  • Makram El-shagi & Logan J Kelly, 2014. "Liquidity in the liquidity crisis: evidence from Divisia monetary aggregates in Germany and the European crisis countries," Economics Bulletin, AccessEcon, vol. 34(1), pages 63-72.
    • Handle: RePEc:ebl:ecbull:eb-13-00073
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2014/Volume34/EB-14-V34-I1-P7.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Tobias Knedlik & Gregor Von Schweinitz, 2012. "Macroeconomic Imbalances as Indicators for Debt Crises in Europe," Journal of Common Market Studies, Wiley Blackwell, vol. 50(5), pages 726-745, September.
    2. William A. Barnett, 2000. "Economic Monetary Aggregates: An Application of Index Number and Aggregation Theory," Contributions to Economic Analysis, in: The Theory of Monetary Aggregation, pages 11-48, Emerald Group Publishing Limited.
    3. Carmen M. Reinhart & Graciela L. Kaminsky, 1999. "The Twin Crises: The Causes of Banking and Balance-of-Payments Problems," American Economic Review, American Economic Association, vol. 89(3), pages 473-500, June.
    4. Alessi, Lucia & Detken, Carsten, 2011. "Quasi real time early warning indicators for costly asset price boom/bust cycles: A role for global liquidity," European Journal of Political Economy, Elsevier, vol. 27(3), pages 520-533, September.
    5. Kelly, Logan J. & Barnett, William A. & Keating, John W., 2011. "Rethinking the liquidity puzzle: Application of a new measure of the economic money stock," Journal of Banking & Finance, Elsevier, vol. 35(4), pages 768-774, April.
    6. Mr. Abdul d Abiad, 2003. "Early Warning Systems: A Survey and a Regime-Switching Approach," IMF Working Papers 2003/032, International Monetary Fund.
    7. Barnett, William A. & Chauvet, Marcelle, 2011. "How better monetary statistics could have signaled the financial crisis," Journal of Econometrics, Elsevier, vol. 161(1), pages 6-23, March.
    8. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    9. Barnett, William A., 2012. "Getting it Wrong: How Faulty Monetary Statistics Undermine the Fed, the Financial System, and the Economy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262516888, April.
    10. Livio Stracca, 2004. "Does Liquidity Matter? Properties of a Divisia Monetary Aggregate in the Euro Area," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(3), pages 309-331, July.
    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. Darvas, Zsolt, 2015. "Does money matter in the euro area? Evidence from a new Divisia index," Economics Letters, Elsevier, vol. 133(C), pages 123-126.
    2. El-Shagi, Makram & Tochkov, Kiril, 2022. "Shadow of the colossus: Euro area spillovers and monetary policy in Central and Eastern Europe," Journal of International Money and Finance, Elsevier, vol. 120(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. El-Shagi, Makram & Kelly, Logan, 2019. "What can we learn from country-level liquidity in the EMU?," Journal of Financial Stability, Elsevier, vol. 42(C), pages 75-83.
    2. Geraldine Dany-Knedlik & Martina Kämpfe & Tobias Knedlik, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 123-139, February.
    3. Panayotis Michaelides & Mike Tsionas & Panos Xidonas, 2020. "A Bayesian Signals Approach for the Detection of Crises," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(3), pages 551-585, September.
    4. Barnett, William A. & Su, Liting, 2020. "Financial Firm Production Of Inside Monetary And Credit Card Services: An Aggregation Theoretic Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 24(1), pages 130-160, January.
    5. Sarlin, Peter & von Schweinitz, Gregor, 2021. "Optimizing Policymakers’ Loss Functions In Crisis Prediction: Before, Within Or After?," Macroeconomic Dynamics, Cambridge University Press, vol. 25(1), pages 100-123, January.
    6. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
    7. von Schweinitz, Gregor & Sarlin, Peter, 2015. "Signaling Crises: How to Get Good Out-of-Sample Performance Out of the Early Warning System," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112964, Verein für Socialpolitik / German Economic Association.
    8. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    9. John W. Keating & Logan J. Kelly & A. Lee Smith & Victor J. Valcarcel, 2019. "A Model of Monetary Policy Shocks for Financial Crises and Normal Conditions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(1), pages 227-259, February.
    10. William A. Barnett & Neepa B. Gaekwad, 2018. "The Demand for Money for EMU: a Flexible Functional Form Approach," Open Economies Review, Springer, vol. 29(2), pages 353-371, April.
    11. Barnett, William A. & Han, Qing & Zhang, Jianbo, 2021. "Monetary services aggregation under uncertainty: A behavioral economics extension using Choquet expectation," Journal of Economic Behavior & Organization, Elsevier, vol. 182(C), pages 437-447.
    12. William A. Barnett & Liting Su, 2017. "Financial Firm Production Of Inside Monetary And Credit Card Services: An Aggregation Theoretic Approach1," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201707, University of Kansas, Department of Economics, revised Oct 2017.
    13. El-Shagi, M. & Knedlik, T. & von Schweinitz, G., 2013. "Predicting financial crises: The (statistical) significance of the signals approach," Journal of International Money and Finance, Elsevier, vol. 35(C), pages 76-103.
    14. Knedlik, Tobias, 2014. "The impact of preferences on early warning systems — The case of the European Commission's Scoreboard," European Journal of Political Economy, Elsevier, vol. 34(C), pages 157-166.
    15. Richard G. Anderson & Barry E. Jones, 2011. "A comprehensive revision of the U.S. monetary services (divisia) indexes," Review, Federal Reserve Bank of St. Louis, vol. 93(Sep), pages 325-360.
    16. Belongia, Michael T. & Ireland, Peter N., 2014. "The Barnett critique after three decades: A New Keynesian analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 5-21.
    17. Knedlik, Tobias, 2012. "The European Commission’s Scoreboard of Macroeconomic Imbalances – The Impact of Preferences on an Early Warning System," IWH Discussion Papers 10/2012, Halle Institute for Economic Research (IWH).
    18. Markus Holopainen & Peter Sarlin, 2015. "Toward robust early-warning models: A horse race, ensembles and model uncertainty," Papers 1501.04682, arXiv.org, revised Apr 2016.
    19. Magnus Saß, 2024. "Detecting excessive credit growth: An approach based on structural counterfactuals," Berlin School of Economics Discussion Papers 0046, Berlin School of Economics.
    20. James J. Heckman & Apostolos Serletis, "undated". "Introduction to Internally Consistent Modeling, Aggregation, Inference, and Policy," Working Papers 2014-73, Department of Economics, University of Calgary, revised 29 Sep 2014.

    More about this item

    Keywords

    European debt crisis; Divisia aggregation; Liquidity aggregates; Signaling models; Index Number Theory;
    All these keywords.

    JEL classification:

    • E4 - Macroeconomics and Monetary Economics - - Money and Interest Rates
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    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:ebl:ecbull:eb-13-00073. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.