Autoregressive Vector (VAR) Method in Analyzing Inflation Persistence in Indonesia

Abstract

One of the most important economic variables is inflation. It is known that some changes in each major variable in the economy are caused by the rate of inflation, such as unemployment and future economic conditions. This is what makes inflation a variable that is often observed and tested, both theoretically and empirically. Economic development is said to run well if supported by stable inflation values, which will later serve to make the population more prosperous in the future. This research is a quantitative research using secondary data, namely inflation and CPI data from January 2018 to December 2022. Data obtained from Bank Indonesia and the Indonesian Central Bureau of Statistics. This study aims to see persistence in Indonesia and see the effect of CPI on inflation both in the long and short term. Where the model used in this study is using the VAR model of differential levels, because the data is not stationary at the level level. Determination of the optimal lag length is obtained from the lowest Akaike Information Criterion (AIC) value. The results of the analysis show that the persistence of inflation in Indonesia is fairly high. This is because the lag value in inflation is close to 1 or even more, which is 6.71. The high persistence of inflation is expected to cause shocks that affect the inflation rate in Indonesia. Then the length of time it takes for inflation to return to the equilibrium position is about 1 year and a half or 18 months. Furthermore, for the effect of inflation on CPI, in this case it has an influence in the long run, while for the short term influence is only influenced by its own variables.

Authors and Affiliations

Nisa Marlina, Irwan Suriadi

Keywords

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  • EP ID EP721476
  • DOI 10.47191/ijmra/v6-i10-17
  • Views 25
  • Downloads 0

How To Cite

Nisa Marlina, Irwan Suriadi (2023). Autoregressive Vector (VAR) Method in Analyzing Inflation Persistence in Indonesia. International Journal of Multidisciplinary Research and Analysis, 6(10), -. https://europub.co.uk/articles/-A-721476