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DEPENDENCE STRUCTURE BETWEEN MONEY AND ECONOMIC ACTIVITY: A MARKOV-SWITCHING COPULA VEC APPROACH

Published online by Cambridge University Press:  10 June 2021

Apostolos Serletis  and
Libo Xu
Apostolos Serletis*
Affiliation:
University of Calgary
Libo Xu
Affiliation:
University of San Francisco
*
Address correspondence to: Apostolos Serletis, Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, Canada. E-mail: [email protected]. Phone: (403) 220-4092. Fax: (403) 282-5262.
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Abstract

This paper examines correlation and dependence structures between money and the level of economic activity in the USA in the context of a Markov-switching copula vector error correction model. We use the error correction model to focus on the short-run dynamics between money and output while accounting for their long-run equilibrium relationship. We use the Markov regime-switching model to account for instabilities in the relationship between money and output, and also consider different copula models with different dependence structures to investigate (upper and lower) tail dependence.

Keywords

Divisia Monetary AggregatesMarkov Regime SwitchingDependenceCopula
Type
Articles
Information
Macroeconomic Dynamics , Volume 26 , Issue 8 , December 2022 , pp. 2141 - 2160
Copyright
© Cambridge University Press 2021

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Footnotes

This paper examines correlation and dependence structures between money and the level of economic activity in the USA in the context of a Markov-switching copula vector error correction model. We use the error correction model to focus on the short-run dynamics between money and output while accounting for their long-run equilibrium relationship. We use the Markov regime-switching model to account for instabilities in the relationship between money and output, and also consider different copula models with different dependence structures to investigate (upper and lower) tail dependence.

References

Bai, J. and Ng, S. (2005) Tests for skewness, kurtosis, and normality for time series data. Journal of Business and Economic Statistics 23, 49–60.CrossRefGoogle Scholar
Balcilar, M., Gupta, R. and Miller, S. M. (2015) Regime switching model of US crude oil and stock market prices: 1859 to 2013. Energy Economics 49, 317–327.CrossRefGoogle Scholar
Barnett, W. A. (1978) The user cost of money. Economics Letters 1, 145–149.CrossRefGoogle Scholar
Barnett, W. A. (1980) Economic monetary aggregates: An application of index number and aggregation theory. Journal of Econometrics 14, 11–48.CrossRefGoogle Scholar
Barnett, W. A. (2016) Friedman and Divisia monetary measures. In: Cord, R. A. and Hammond, D. (eds.), Milton Friedman: Contributions to Economics and Public Policy, pp. 265–291. Oxford: Oxford University Press.Google Scholar
Barnett, W. A. and Chauvet, M. (2011) How better monetary statistics could have signaled the financial crisis. Journal of Econometrics 161, 6–23.CrossRefGoogle Scholar
Barnett, W. A., Liu, J., Mattson, R. S. and van den Noort, J. (2013) The new CFS Divisia monetary aggregates: Design, construction, and data sources. Open Economies Review 24, 101–124.CrossRefGoogle Scholar
Belongia, M. T. and Ireland, P. N. (2014) The Barnett critique after three decades: A new Keynesian analysis. Journal of Econometrics 183, 5–21.CrossRefGoogle Scholar
Belongia, M. T. and Ireland, P. N. (2015) Interest rates and money in the measurement of monetary policy. Journal of Business and Economic Statistics 33, 255–269.CrossRefGoogle Scholar
Belongia, M. T. and Ireland, P. N. (2016) Money and output: Friedman and Schwartz revisited. Journal of Money, Credit and Banking 48, 1223–1266.CrossRefGoogle Scholar
Belongia, M. T. and Ireland, P. N. (2018) Targeting constant money growth at the zero lower bound. International Journal of Central Banking 14, 159–204.Google Scholar
Bonett, D. G. and Wright, T. A. (2000) Sample size requirements for estimating pearson, kendall and spearman correlations. Psychometrika 65, 23–28.CrossRefGoogle Scholar
Dery, C. and Serletis, A. (forthcoming) Interest rates, money, and economic activity. Macroeconomic Dynamics. https://www.cambridge.org/core/journals/macroeconomic-dynamics/article/abs/interest-rates-money-and-economic-activity/3B2A01D7DBBD9F6BDBFD9F91531E7AB5#cited-by-modalGoogle Scholar
Ellington, M. (2018) The case for Divisia monetary statistics: A Bayesian time-varying approach. Journal of Economic Dynamics and Control 96, 26–41.CrossRefGoogle Scholar
Frank, M. J. (1979) On the simultaneous associativity of F(x, y) and x + y − F(x, y). Aequationes Mathematicae 19, 194–226.CrossRefGoogle Scholar
Friedman, M. (1961) The lag effect of monetary policy. Journal of Political Economy 69, 447–466.CrossRefGoogle Scholar
Hafer, R. W. and Jansen, D. W. (1991) The demand for money in the United States: Evidence from cointegration tests. Journal of Money, Credit and Banking 23, 155–168.CrossRefGoogle Scholar
Hamilton, J. D. (1988) A neoclassical model of unemployment and the business cycle. Journal of Political Economy 96, 593–617.Google Scholar
Hamilton, J. D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357–384.CrossRefGoogle Scholar
Hendrickson, J. R. (2014) Redundancy or mismeasurement? A reappraisal of money. Macroeconomic Dynamics 18, 1437–1465.Google Scholar
Jadidzadeh, A. and Serletis, A. (2019) The demand for assets and optimal monetary aggregation. Journal of Money, Credit and Banking 51, 929–952.Google Scholar
Joe, H. (1997) Multivariate Models and Dependence Concepts. London: Chapman & Hall.Google Scholar
Johansen, S. (1988) Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12, 231–254.CrossRefGoogle Scholar
Koop, G., Pesaran, M. H. and Potter, S. M. (1996) Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74, 119–147.CrossRefGoogle Scholar
Serletis, A. and Gogas, P. (2014) Divisia monetary aggregates, the great ratios, and classical money demand functions. Journal of Money, Credit and Banking 46, 229–241.CrossRefGoogle Scholar
Serletis, A. and Rahman, S. (2013) The case for Divisia money targeting. Macroeconomic Dynamics 17, 1638–1658.CrossRefGoogle Scholar
Serletis, A. and Shahmoradi, A. (2006) Velocity and the variability of money growth: Evidence from a VARMA, GARCH-M model. Macroeconomic Dynamics 10, 652–666.CrossRefGoogle Scholar
Serletis, A. and Xu, L. (2020) Money supply volatility and the macroeconomy. Macroeconomic Dynamics 24, 1392–1402.CrossRefGoogle Scholar
Sklar, A. (1959). Fonctions de repartition an dimensions et leurs marges. Publ Inst Statist Univ Paris 8, 449–460.Google Scholar