CONSUMER PRICE INDEX MODELING USING A MIXED TRUNCATED SPLINE AND KERNEL SEMIPARAMETRIC REGRESSION APPROACH
Abstract
Some semiparametric regression model approaches include spline, kernel, Fourier series, and wavelet. Semiparametric regression modelling can involve more than one independent variable (multivariable), a parametric approach is usually combined with one of the nonparametric approaches, such as combining a parametric approach with a nonparametric kernel. If a consumer price index model can be built based on the variables that influence it, predictions of consumer price percentages can be made, which it is hoped will help the government determine policies to control consumer price inflation, especially in NTB Province. The data used in this research includes the consumer price index and the factors that influence it according to districts/cities in NTB Province from 2022 to April 2024. The data source was obtained from secondary data at BPS NTB Province. This research design uses a mixed semiparametric approach of truncated spline and kernel regression. Based on calculations, the predicted results of the consumer price index in NTB Province show that the predicted data graph is very close to the actual data . Modelling the consumer price index in NTB Province is a model with 2 knot points, where the model efficiency has the smallest GCV value of 0.001507. The model goodness value is 0.99, meaning that the variables used can explain 99% of the model variability.
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References
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