Investigating the Dynamic Relationship between the Money Growth and Inflation in Iran: An Econophysics Analysis of Quantity Theory of Money

Document Type : Research Paper

Authors

1 Ph.D. Candidate in Economics, Islamic Azad University, Aligoudarz Branch

2 Assistant Professor of Economics, Ayatullah Boroujerdi University

3 Assistant Professor Economics, Ayatollah Borujerdi University

Abstract

In the current research, using the wavelet method and coherence analysis, it is tried to redefine the relationship between the growth of money (the monetary base and liquidity) and inflation in the economy of Iran. To this end, using the available seasonal data (1982-2017), the coherence of these variables is investigated in different time periods. Unexpectedly, the results indicate that in assessment of the relationship between liquidity and inflation, monetary policies based on liquidity changes has no significant impact on the inflation, but the growth of monetary base in the middle and long term has a direct relationship with inflation and this justifies quantity money theory in Iran more than liquidity variable. Therefore, it seems that, in the long run, the change in liquidity factor is not a suitable strategy for Iran's economy, but in the case of the monetary base, the result is somewhat different and shows in the medium and long term it will have significant impact on monetary policy and inflation. In other words, despite the current study suggests the liquidity variable is endogenous (lag effect) in the short and middle term, but according to available information, one cannot rule out the exogenous hypothesis of the monetary base in the Iranian economy. So, in the long run, on the basis of quantity money theory, money supply (especially monetary base) is still a powerful policy tool owned by the Central Bank of Iran. It is important to note that with regard to special potential of wavelet method in which the simultaneous investigation of short-term and long-term causality is done between time series of variables and the severity of the relationship between them, one cannot consider the inflation as a monetary phenomenon in all periods of times.

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References

  1. Aguiar‐Conraria, L., & Soares, M. J. (2014). The continuous wavelet transform: moving beyond uni‐and bivariate analysis. Journal of Economic Surveys, 28(2), 344-375.‏
  2. Aguiar-Conraria, L., Martins, M. M., & Soares, M. J. (2012). The yield curve and the macro-economy across time and frequencies. Journal of Economic Dynamics and Control, 36(12), 1950-1970.
  3. Atrkar Roshan, S. A. R. (2014). Inflation and Money supply growth in Iran: Empirical evidences from cointegration and causality. Iranian Economic Review, 18(1), 131-152 (In Persian).
  4. Bloomfield, D. S., McAteer, R. J., Lites, B. W., Judge, P. G., Mathioudakis, M., & Keenan, F. P. (2004). Wavelet phase coherence analysis: application to a quiet-sun magnetic element. The Astrophysical Journal, 617(1), 623.
  5. Jiang, C., Chang, T., & Li, X. L. (2015). Money growth and inflation in China: New evidence from a wavelet analysis. International Review of Economics & Finance, 35, 249-261.
  6. Dadgar, Y, & Rahmani, T (2003) Fundamentals and Principles of Economics, Qom, Institute of Boostan Book, pp. 303-304 (In Persian).
  7. Diulio, E (2013) Theory and Macroeconomic Problems, Hamid Reza Arbab, Tehran, Nizar Ney, p. 421 (In Persian).
  8. Dowd, K., Cotter, J., & Loh, L. (2011). US core inflation: A wavelet analysis. Macroeconomic Dynamics, 15(4), 513-536..
  9. Goffe, W. L (1994). Wavelets in macroeconomics: An introduction. In Computational techniques for econometrics and economic analysis (pp. 137-149). Springer, Dordrecht.
  10. 10. Goupillaud, P., Grossmann, A., & Morlet, J. (1984). Cycle-octave and related transforms in seismic signal analysis. Geoexploration, 23(1), 85-102.
  11. 11. Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear processes in geophysics, 11(5/6), 561-566.
  12. 12. Hacker, R. S., Karlsson, H. K., & Månsson, K. (2014). An investigation of the causal relations between exchange rates and interest rate differentials using wavelets. International Review of Economics & Finance, 29, 321-329.
  13. 13. Hoseini, S., Mohtashemi, S. (2011). The Relationship between Inflation and Liquidity Growth in Iran's Economy, Breakdown or Sustainability? Economic Research Faculty of Economics, Tehran University, 3(8), 21-62 (In Persian).
  14. 14. Hudgins, L., Friehe, C. A., & Mayer, M. E. (1993). Wavelet transforms and atmopsheric turbulence. Physical Review Letters, 71(20), 3279.
  15. 15. Loh, L. (2013). Co-movement of Asia-Pacific with European and US stock market returns: A cross-time-frequency analysis. Research in International Business and Finance, 29, 1-13..
  16. 16. Kakuei, N., & Naghdi, Y. (2011). Money and inflation in Iran: Evidence based on P*. Quarterly: Journal of Economic Research, 2(14), 135-156 (In Persian).
  17. 17. Mitra, S. (2006). A wavelet filtering based analysis of macroeconomic indicators: the Indian evidence. Applied mathematics and computation, 175(2), 1055-1079.
  18. 18. Nademi, Y., & Kochyani, R. (2017). Investigating the Coexistence of Stock, Currency and Gold Markets in the Iranian Economy from Coherence Analysis and Equophysic Approach. Journal of Financial Engineering and Management of Securities, 31(8), 149-166 (In Persian).
  19. 19. Rahmani, Timur (2005) Macroeconomics, Tehran, Brothers, Ninth Edition, vol. 1(2), pp. 233-239,209 (In Persian).
  20. 20. Ramsey, J. B., & Lampart, C. (1998). The decomposition of economic relationships by time scale using wavelets: expenditure and income. Studies in Nonlinear Dynamics & Econometrics, 3(1).
  21. 21. Reboredo, J. C., & Rivera-Castro, M. A. (2014). Wavelet-based evidence of the impact of oil prices on stock returns. International Review of Economics & Finance, 29, 145-176.
  22. 22. Rua, A. (2012). Money growth and inflation in the euro area: A time‐frequency view. Oxford Bulletin of Economics and Statistics, 74(6), 875-885.
  23. 23. Sahabi, B., Soleymani, S., Khezri, S., & Khezri, S. (2012). The Effects of Liquidity Growth on Inflation in Iran's Economy: Model Changes in Diet. Economic Strategy, 5(16), 26-62 (In Persian).
  24. 24. Samimi, A., & Mohamadi, M. (2014). An analysis of the evolution of the monetary economy. Monetary research – banking, 19(7), 1-25 (In Persian).
  25. 25. Shakeri, A. (2008). The Macroeconomics of Theories and Policies, Tehran, Pars Nojsan, p. 2, p. 912 (In Persian).
  26. 26. Sharif, M. (2008) Macroeconomics, Tehran, Information Publishing, First Printing, pp. 140-142 (In Persian).
  27. 27. Taqavi, M (2004) Principles of Economics 2 (Macroeconomics), Tehran, Payame Noor University, p. 243-247 (In Persian).
  28. 28. Tiwari, A. K., Mutascu, M., & Andries, A. M. (2013). Decomposing time-frequency relationship between producer price and consumer price indices in Romania through wavelet analysis. Economic Modelling, 31, 151-159.
  29. 29. Tiwari, A. K., Suresh, K. G., Arouri, M., & Teulon, F. (2014). Causality between consumer price and producer price: evidence from Mexico. Economic Modelling, 36, 432-440.
  30. Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological society, 79(1), 61-78..
  31. 31. Voiculescu, M., & Usoskin, I. (2012). Persistent solar signatures in cloud cover: spatial and temporal analysis. Environmental Research Letters, 7(4), 044004.
  32. Yarmohamadi, J., & Erfani, A. (2016) Exogenos test of money in Iranian economy. Financial Economics Quarterly, 11(23) (In Persian).

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