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The Stability of Money Demand in the Long Run: An Empirical Study from Italy

In: Advances in Cross-Section Data Methods in Applied Economic Research

Author

Listed:
  • Chaido Dritsaki

    (University of Western Macedonia)

Abstract

The stability of money demand is a crucial issue for the effectiveness of monetary policy in each country and is being threatened when important changes are taking place in its monetary policy. Applying ARDL technique and error correction model (ECM) developed by Pesaran et al. (2001), this paper aims to examine the factors that influence money demand in Italy for the period 1960–2017. The results of ARDL technique and ECM show that there is both a long-run and short-run relationship among variables used. Real income, long-run interest rate, and inflation comply with the expectations of monetary theory. Finally, the results of CUSUM and CUSUMSQ stability tests and unit circle confirm the long-run relationship among variables and also that the stability condition is satisfied when money demand for Italy is estimated with M1 variable for the examined period.

Suggested Citation

  • Chaido Dritsaki, 2020. "The Stability of Money Demand in the Long Run: An Empirical Study from Italy," Springer Proceedings in Business and Economics, in: Nicholas Tsounis & Aspasia Vlachvei (ed.), Advances in Cross-Section Data Methods in Applied Economic Research, chapter 0, pages 401-418, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-38253-7_25
    DOI: 10.1007/978-3-030-38253-7_25
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    More about this item

    Keywords

    Money demand stability; ARDL model; Vector error correction model; Stability of the coefficients; Monetary aggregates; Italy;
    All these keywords.

    JEL classification:

    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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