Is There Chaos in Inflation Data?

Pritha Das

Department of Mathematics, Bengal Engineering and Science University, Shibpur, Howrah, India.

DOI: 10.4236/jamp.2014.25026                

Abstract

Economic indicators are snippets of financial and economic data published regularly by governmental agencies and the private sector. An exchange rate represents the value of one currency in another and it fluctuates over time. ForEx rates are affected by many highly correlated economic, political and even psychological factors. It was observed that changes in the exchange rate are related to news in the fundamentals which cover Inflation for the country concerned. In a series of work, we investigated and confirmed the chaotic property of ForEx Rates of several countries. In this perspective, we concentrate on nonlinear data analysis of inflation data of nine countries. We find existence of chaos in inflation data for some countries.

Keywords

Inflation, Surrogate Method, Lyapunov Exponent, Chaos

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Das, A. and Das, P. (2007) Chaotic Analysis of the Foreign Exchange Rates. Applied Mathematics & Computation, 185, 388-396.
[2]	Gürsan, Ç., Ali, H.B. and Das, A. (2012) A Linearization Based Non-Iterative Approach to Measure the Gaussian Noise Level for Chaotic Time Series. Chaos, Solitons & Fractals, 45, 266-278.
[3]	Das, A., Das, P. and Gürsan, Ç. (2012) Chaotic Analysis of the Foreign Exchange Rates during 2008 to 2009 Recession. African Journal of Business Management, 6, 5226-5233.
[4]	Das, P. and Das, A. (2013) Comparison of Recession during 2008-2009 and 2009-2013 Through Chaotic Analysis of The Foreign Exchange Rates. J. Contemporary Manag., 2, 100-112.
[5]	Forex.com at http://www.forex.com/forex_economic_indicators.html
[6]	Guastello, S.J. (1995) The Search for a Natural Rate of Price Inflation: US 1948-1995. Chaos Network, 7, 16-23.
[7]	Guastello, S.J. (2001) Attractor Stability in Unemployment and Inflation Rates. Evolutionary Controversies in Economics, 2001, 89-99.
[8]	Augustine, C.A. (2011) Are Inflation Rates Really Nonstationary? New Evidence from Non-linear STAR Framework and African Data. International Journal of Economics and Finance, 3, 97-108.
[9]	Inflation.eu-Worldwide Inflation Data. http://www.inflation.eu
[10]	Department of Census and Statistics (2001) Movements of Sri Lanka CCPI, Government of Sri Lanka. http://www.statistics.gov.lk/
[11]	Singapore Inflation Data, Government of Singapore. http://data.gov.sg
[12]	Theiler, J., Eubank, S., Longtin, A., Galdrikian, B. and Farmer, J. (1992) Testing for Nonlinearity in Time Series: The Method of Surrogated Data. Physica D, 58, 77-94.
[13]	Parlitz, U., Wedekind, I., Lauterborn, W. and Merkwirth, C. (2011) TSTOOL & User Manual, Ver. 1.11, DPI Göttingen. www.physik3.gwdg.de/tstool/gpl.txt
[14]	The MathWorks, Inc. (2002) MATLAB Release13.
[15]	Wolf, A., Swift, J.B., Swinney, L.H. and Vastano, J.A. (1985) Determining Lyapunov Exponent from a Time Series. Physica D, 16, 285-317.
[16]	Wall Street J. Nov 1-3, 2013. www.wsj.com