Robust regression modelling for inflation factor in the Indonesian economy development

¹ Mathematics Department, Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, Surabaya, East Java, Indonesia
² Mathematics and Statistics Department, Thaksin University, Phatthalung, Thailand

^* Corresponding author: ayuninsofro@unesa.ac.id

Abstract

Inflation is a general and continuous increase in the prices of goods and services over a while. Inflation is measured by the Consumer Price Index (CPI) indicator to calculate the average price change of a package of goods and services households consume over time. Inflation in Indonesia is not in a precarious condition. However, it also states that inflation in Indonesia could rise. This rise can affect the sustainable development goals (SDGs). Therefore, Indonesia needs to have inflation data scrutinized every year. This study aims to examine and show the factors that affect inflation. Robust regression is an important method to analyze data contaminated by outliers and provide more flexible results. So that it can produce robust regression models and determine what factors significantly affect inflation in Indonesia by the research objectives, this study’s research type is experimental research with literature studies. The variable used is Inflation in Indonesia, which is the dependent variable of the study, and the other four independent variables are export value, interest rate, money supply, and exchange rate. After that, a robust regression model with maximum likelihood type (M) estimation, scale (S) estimation, and least median of squares (LMS) estimation will be obtained, and the best model will be selected. The results show that the least median of squares (LMS) estimation is the best with the acquisition of an Akaike information criteria value of -390.1363. Furthermore, the high and low inflation in 20182022 is influenced by interest rates, money supply and export value.