UJI STASIONERITAS DATA INFLASI DENGAN PHILLIPS-PERON TEST - Maruddani, Di Asih I; Tarno, Tarno; Anisah, Rokhma Al (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2008)
The classical regression model was devised to handle relationships between stationary variables. It should not be applied to nonstationary series. A time series is therefore said to be stationary is its mean, variance, and covariances remain constant over time. A problem associated with nonstationary variables, 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 Phillips-Peron test for inflation data in Indonesia for the time period 1996-2003. The data showed upward trend and the error terms are correlated. The empirical results showed that the inflation data in Indonesia is a nonstationary series. Â Keywords : stationarity, non autocorrelation, Phillips-Peron Test, inflation