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

1 Fuctional Youth Statistics, Statistics of Padang Municipality, Padang, Indonesia
2 Islamic Business, Faculty of Economics and Business, Universitas Indonesia, Depok, Indonesia
3 BPS Young Expert Statistician Padang City, Indonesia
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Abstract

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.

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How to Cite

1.
Study of Inflation using Stationary Test with Augmented Dickey Fuller & Phillips-Peron Unit Root Test (Case in Bukittinggi City Inflation for 2014-2019). EKSAKTA [Internet]. 2022 Jun. 30 [cited 2026 Aug. 25];23(02):106-1. Available from: http://eksakta.ppj.unp.ac.id/index.php/eksakta/article/view/303