Nonstationarity Modeling of Economic and Financial Time Series
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Nonstationarity Modeling of Economic and Financial Time Series

Authors: C. Slim


Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: Stationarity, unit root tests, economic time series.

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[1] Box, G., and G. Jenkins (1976): Time Series Analysis Forecasting and Control. San Francisco.
[2] Nelson and Plosser (1982), trends and random walks in macroeconomic time series, Journal of monetary Economic, 10, 139-162.
[3] Boswijk, P. H. (1992): Cointegration, Identification and Exogeneity: Inference in Structural Error Correction Models. Thesis Publisher, Tinbergen Institute Research Series, Amsterdam.
[4] Stock (1994), unit roots, structural break and trends, Handbook of Econometrics, Vol.4, North HollandP. Schotmanand.
[5] Dickey, D., and W. Fuller (1979): Distribution of the Estimator for the autoregressive Time Series with a Unit Root, Journal of the American Statistical Association, 74, 427--431.
[6] Hamilton, J, D. (1994), Time Series Analysis, Published by Princeton University Press.
[7] Phillips (1987): "Time Series Regression with a Unit Root" Econometrica 55, 277-301.
[8] Phillips, P. C., and P. Perron (1988): Testing for a Unit Root in Time Series Regression, Biometrica, 75, 335--346.
[9] Leybourne and Newbold (1999), the behaviour of Dickey Fuller and Philips Perron tests under the alternatives hypothesis, Econometrics Journal, 2, 92-106.
[10] Kwiatkowski, Phillips, Schmidt and Shin (1992), testing the null hypothesis of stationary against the alternative of a unit root: how sure are we that economic time series have a unit root?, Journal of Econometrics, 54, 159-178.
[11] Campbelland Perron (1991) "Pitfalls and opportunities: what macroeconomists should know about unit roots, NBER Macroeconomics Annual, 1991, 6, 141-201.
[12] Christiano, L., and M. Eichenbaum (1990): Unit Roots in Real GNP: do we Know and do we Care?, Carnegie-Rochester Conference Series on Public Policy, 32, 7--61.