UJI STASIONERITAS DATA INFLASI KOTA PADANG PERIODE 2014-2019
Keywords:
stationary, non autocorrelation, Phillips-Peron Test, Augmented Dickey Fuller Test, InflationAbstract
The stationarity of a time series can have a significant influence on its properties and forecasting behavior. A time series is therefore said to be stationary is its mean, variance, and covariances remain constant over time. A problem associated with nonstationary variabels, and frequently faced by econometricians when dealing with time series data, is the spurious regression. An apparent indicator of such spurious regression was a particularly low level for the Durbin-Watson statistics, combined with an acceptable R2. Statistical test for stationarity have proposed by Dickey and Fuller (1979). The distribution theory supporting the Dickey-Fuller test assumes that the errors are statistically independent and have a constant variance. Phillips and Peron (1988) developed a generalization of the Dickey-Fuller procedure that the error terms are correlated and not have constant variance. In this paper, we use Augemented Dickey Fuller test and Phillips-Peron test for inflation data in Padang Municipality for the time period 2014-2019. The data showed upward trend and the error terms are correlated. The empirical results showed that the inflation data in Padang Municipality is a stationary series