By taking natural log transformation and successive differencing, one can convert the non stationary time series
into a stationary series.
Equation 1 contains no intercept and trend; this means that X is a stationary time series
with a zero mean if the null hypothesis is rejected.
(1949), Extrapolation, Interpolation and Smoothing of Stationary Time Series
, Chichester, Wiley.
However, when a shock occurs to a stationary time series
there is a tendency for the series to return to the long-run mean of the series.
Conclusion: In time series modeling of annual groundnut production amounts from the period of 1950-2015, the non-stationary time series were converted into stationary time series
after taking the first difference of the data.
Responding to criticisms of the original Dickey and Fuller (1979) ADF unit root test from Gamber and Sorensen, Haslag, Nieswiadomy, and Slottje (1994) apply the unit root tests of Phillips and Perron (1988) and suggest that significant nonlinearities are not present in the [real] net discount ratio and that the variable can be represented as a stationary time series
where, all variables are stationary time series
, [DELTA] is the first difference operator and the [R1.sub.t-1], [R2.sub.t-1] and [R3.sub.t-1] are the lagged values of the error correction terms derived from the long run cointegration equation.
"Effects of the Hodrick-Prescott Filter on Trend and Difference Stationary Time Series
: Implications for Business Cycle Research," Journal of Economic Dynamics and Control, 19, 1995, pp.
After taking the first differences of the original (non-stationary) time series data on cotton lint, stationary time series
data were obtained and exposed to cointegration analysis to determine whether any long-term relationships among the variables exist and whether the series were integrated.
Shocks to a stationary time series
may be temporary.
According to the operational definition of Wiener-Granger causality in the time domain, one covariance stationary time series
at causes another covariance stationary time series
[b.sub.t], if better forecasts of [b.sub.t] can be made by using the knowledge of at, for t < 0, after exploiting all relevant information on past values of [b.sub.t].
In a previous article in this Journal (Haslag, Nieswiadomy, and Slottje, 1991), we provided evidence consistent with the notion that the net discount ratio is a stationary time series
. Gamber and Sorensen's comment reexamines this issue and claims that the net discount ratio is nonstationary.