APLIKASI MODEL GARCH PADA DATA INFLASI BAHAN MAKANAN INDONESIA PERIODE 2005.1- 2010.6
Teguh Santoso, Maruto Umar Basuki
Abstract
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Teguh Santoso, Maruto Umar Basuki
Abstract
Open-access reader
In econometric time series analysis, data which have high volatility would be very risky to be used as a basis for forecasting, including the volatility of food prices in Indonesia. Time series data have a tendency to have a constant confounding error variance over time. Appropriate econometric model to estimate such behavior is called the Autoregressive Conditional Heteroscedasticity (ARCH) model and the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. This paper attempts to use ARCH/GARCH models to explain the behavior of food price inflation in Indonesia in time period of 2005.1 to 2010.6. It is explained that by incorporating elements of ARCH/GARCH, better estimates will be achieved.
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In econometric time series analysis, data which have high volatility would be very risky to be used as a basis for forecasting, including the volatility of food prices in Indonesia. Time series data have a tendency to have a constant confounding error variance over time. Appropriate econometric model to estimate such behavior is called the Autoregressive Conditional Heteroscedasticity (ARCH) model and the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model. This paper attempts to use ARCH/GARCH models to explain the behavior of food price inflation in Indonesia in time period of 2005.1 to 2010.6. It is explained that by incorporating elements of ARCH/GARCH, better estimates will be achieved.
Key concepts: Autoregressive conditional heteroskedasticity, Heteroscedasticity, Econometrics, Autoregressive model, Volatility (finance), Arch, Conditional variance, Economics