Study of Inflation using Stationary Test with Augmented Dickey Fuller & Phillips-Peron Unit Root Test (Case in Bukittinggi City Inflation for 2014-2019)

Afnita Roza (Fuctional Youth Statistics, Statistics of Padang Municipality, Padang, Indonesia)
Evony Silvino Violita (Islamic Business, Faculty of Economics and Business, Universitas Indonesia, Depok, Indonesia)
Sherly Aktivani (BPS Young Expert Statistician Padang City, Indonesia)

Eksakta : Berkala Ilmiah Bidang MIPA
Vol. 23 No. 02 (2022): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)

This classical regression model is designed to handle the relationship between stationary variables and should not be applied to non-stationary series. A time series data is said to be stationary if the mean, variance, and covariance remain constant over time. The problem associated with non-stationary variables, and often encountered by researchers when dealing with time series data, is spurious regression. A clear indicator of false regression is the low Durbin-Watson statistic but has a higher coefficient of determination (R2). Therefore, before doing modeling or forecasting using time series data, it is very important to do a stationary test. In this study, we use inflation data in the City of Bukittinggi from January 2014 to December 2019 as a case study. The data shows an uptrend and correlated error terms. Empirical results show that inflation data in Bukittinggi City is a stationary series.