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A small monetary system for the euro area based on German data

Author

Listed:
  • Helmut Lütkepohl

    (European University Institute, Florence, Italy)

  • Ralf Brüggemann

    (Humboldt-Universität Berlin, Berlin, Germany)

Abstract

Previous euro area money demand studies have used aggregated national time series data from the countries participating in the European Monetary Union (EMU). However, aggregation may be problematic because macroeconomic convergence processes have taken place in the countries of interest. Therefore, in this study, quarterly German data until 1998 are combined with data from the euro area from 1999 until 2002 and these series are used for fitting a small vector error correction model for the monetary sector of the EMU. A stable long-run money demand relation is found for the full sample period. Moreover, impulse responses do not change much when the sample period is extended by the EMU period provided the break in the extended data series is captured by a simple dummy variable. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Helmut Lütkepohl & Ralf Brüggemann, 2006. "A small monetary system for the euro area based on German data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 683-702.
  • Handle: RePEc:jae:japmet:v:21:y:2006:i:6:p:683-702
    DOI: 10.1002/jae.864
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    References listed on IDEAS

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    Cited by:

    1. Mardi Dungey, 2010. "Discussion of The Economic Consequences of Oil Shocks: Differences across Countries and Time," RBA Annual Conference Volume,in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.
    2. Dreger, Christian & Wolters, Jürgen, 2010. "M3 Money Demand and Excess Liquidity in the Euro Area," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 459-472.
    3. Edda Claus & Mardi Dungey & Renée Fry, 2008. "Monetary Policy in Illiquid Markets: Options for a Small Open Economy," Open Economies Review, Springer, vol. 19(3), pages 305-336, July.
    4. Anderson, Heather M. & Dungey, Mardi & Osborn, Denise R. & Vahid, Farshid, 2011. "Financial integration and the construction of historical financial data for the Euro Area," Economic Modelling, Elsevier, vol. 28(4), pages 1498-1509, July.
    5. Heather Anderson & Mardi Dungey & Denise Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," Money Macro and Finance (MMF) Research Group Conference 2006 99, Money Macro and Finance Research Group.
    6. Ralf Brüggemann & Helmut Lütkepohl, 2005. "Uncovered Interest Rate Parity and the Expectations Hypothesis of the Term Structure: Empirical Results for the U.S. and Europe," SFB 649 Discussion Papers SFB649DP2005-035, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    7. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "Pooling versus model selection for nowcasting with many predictors: an application to German GDP," Discussion Paper Series 1: Economic Studies 2009,03, Deutsche Bundesbank.
    8. Ralf Brüggemann & Helmut Lütkepohl & Massimiliano Marcellino, 2008. "Forecasting euro area variables with German pre-EMU data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 465-481.
    9. Aaron Mehrotra, 2008. "Demand for Money in Transition: Evidence from China’s Disinflation," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 14(1), pages 36-47, February.
    10. Katrin Assenmacher-Wesche, 2008. "Modeling Monetary Transmission in Switzerland with a Structural Cointegrated VAR Model," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(II), pages 197-246, June.
    11. Marcellino, Massimiliano & Schumacher, Christian, 2007. "Factor-MIDAS for now- and forecasting with ragged-edge data: a model comparison for German GDP," Discussion Paper Series 1: Economic Studies 2007,34, Deutsche Bundesbank.
    12. Christian Dreger & Jürgen Wolters, 2009. "Money velocity and asset prices in the euro area," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 36(1), pages 51-63, February.
    13. Smith, Ron, 2009. "EMU and the Lucas Critique," Economic Modelling, Elsevier, vol. 26(4), pages 744-750, July.
    14. Dreger, Christian & Wolters, Jürgen, 2010. "Investigating M3 money demand in the euro area," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 111-122, February.
    15. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP1," Working Papers 333, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    16. repec:kap:iaecre:v:14:y:2008:i:1:p:36-47 is not listed on IDEAS
    17. Mitra, Sinchan & Sinclair, Tara M., 2012. "Output Fluctuations In The G-7: An Unobserved Components Approach," Macroeconomic Dynamics, Cambridge University Press, vol. 16(03), pages 396-422, June.
    18. Ralf Brüggemann & Jing Zeng, 2015. "Forecasting Euro-Area Macroeconomic Variables Using a Factor Model Approach for Backdating," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 22-39, February.
    19. Helmut Lütkepohl, 2010. "Forecasting Aggregated Time Series Variables: A Survey," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2010(2), pages 1-26.
    20. Angelini, Elena & Marcellino, Massimiliano, 2011. "Econometric analyses with backdated data: Unified Germany and the euro area," Economic Modelling, Elsevier, vol. 28(3), pages 1405-1414, May.
    21. Sousa, Ricardo M., 2010. "Housing wealth, financial wealth, money demand and policy rule: Evidence from the euro area," The North American Journal of Economics and Finance, Elsevier, vol. 21(1), pages 88-105, March.
    22. Paredes, Joan & Pedregal, Diego J. & Pérez, Javier J., 2014. "Fiscal policy analysis in the euro area: Expanding the toolkit," Journal of Policy Modeling, Elsevier, vol. 36(5), pages 800-823.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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