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Money growth variability and output: evidence with credit card-augmented Divisia monetary aggregates

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  • Liu Jinan

    (Department of Economics, University of Calgary, Calgary, Alberta, T2N 1N4, Canada)

  • Serletis Apostolos

    (Department of Economics, University of Calgary, Calgary, Alberta, T2N 1N4, Canada)

Abstract

We reexamine the effects of the variability of money growth on output, raised by Mascaro and Meltzer (1983), in the era of the increasing use of alternative payments, such as credit cards. Using a bivariate VARMA, GARCH-in-Mean, asymmetric BEKK model, we find that the volatility of the credit card-augmented Divisia M4 monetary aggregate has a statistically significant negative impact on output from 2006:7 to 2019:3. However, there is no effect of the traditional Divisia M4 growth volatility on real economic activity. We conclude that the balance sheet targeting monetary policies after the financial crisis in 2007–2009 should pay more attention on the broad credit card-augmented Divisia M4 aggregate to address economic and financial stability.

Suggested Citation

  • Liu Jinan & Serletis Apostolos, 2020. "Money growth variability and output: evidence with credit card-augmented Divisia monetary aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-11, December.
    • Handle: RePEc:bpj:sndecm:v:24:y:2020:i:5:p:11:n:7
    DOI: 10.1515/snde-2019-0106
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    References listed on IDEAS

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    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Barnett, William & Chauvet, Marcelle & Leiva-Leon, Danilo & Su, Liting, 2016. "Nowcasting nominal gdp with the credit-card augmented Divisia monetary aggregates," MPRA Paper 73246, University Library of Munich, Germany.
    3. Khandokar Istiak & Apostolos Serletis, 2017. "Monetary policy and leverage shocks," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 22(2), pages 115-128, April.
    4. 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.
    5. Ali Jadidzadeh & Apostolos Serletis, 2019. "The Demand for Assets and Optimal Monetary Aggregation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(4), pages 929-952, June.
    6. William A. Barnett, 2000. "The Optimal Level of Monetary Aggregation," Contributions to Economic Analysis, in: The Theory of Monetary Aggregation, pages 125-149, Emerald Group Publishing Limited.
    7. Liu, Jinan & Dery, Cosmas & Serletis, Apostolos, 2020. "Recent monetary policy and the credit card-augmented Divisia monetary aggregates," Journal of Macroeconomics, Elsevier, vol. 64(C).
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    10. Barnett, William & Chauvet, Marcelle & Leiva-Leon, Danilo & Su, Liting, 2016. "Nowcasting Nominal GDP with the Credit-Card Augmented Divisia Monetary," Studies in Applied Economics 59, The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise.
    11. Serletis, Apostolos & Shahmoradi, Akbar, 2006. "Velocity And The Variability Of Money Growth: Evidence From A Varma, Garch-M Model," Macroeconomic Dynamics, Cambridge University Press, vol. 10(5), pages 652-666, November.
    12. Mascaro, Angelo & Meltzer, Allan H., 1983. "Long- and short-term interest rates in a risky world," Journal of Monetary Economics, Elsevier, vol. 12(4), pages 485-518, November.
    13. Michael T. Belongia, 1984. "Money growth variability and GNP," Review, Federal Reserve Bank of St. Louis, vol. 66(Apr), pages 23-31.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    More about this item

    Keywords

    credit card-augmented Divisia monetary aggregates; multivariate GARCH-in-mean; optimal monetary aggregation;
    All these keywords.

    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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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