DOI: https://doi.org/10.14710/medstat.12.2.129-139

MODELING CENTRAL JAVA INFLATION AND GRDP RATE USING SPLINE TRUNCATED BIRESPON REGRESSION AND BIRESPON LINEAR MODEL

*Suparti Suparti  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Alan Prahutama  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Agus Rusgiyono  -  Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, Indonesia
Sudargo Sudargo  -  PGRI Semarang University, Indonesia
Open Access Copyright (c) 2019 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Inflation and Gross Regional Domestic Income (GRDP) are two macroeconomic variables of a region that are correlated with each other. GRDP prices constant (real) can be used as an indicator of economic growth in a region from year to year. Inflation is calculated from the CPI rate and economic growth is calculated from the GRDP rate. Inflation and economic growth in an area are influenced by several factors including bank interest rates. Analysis of data consisting of 2 correlated responses can be performed with birespon regression analysis. In this research, modeling of inflation data and the rate of GRDP through birespon data modeling uses spline truncated nonparametric method and birespon linear parametric method. The purpose of this study is to model inflation data and the Central Java GRDP rate using spline truncated birespon regression. The results are compared with the birespon linear regression model. By using quarterly data from the first quarter of 2007 - the second quarter of 2019, the spline truncated model is better than the linear model, because the spline truncated model has a smaller MSE and R2 is greater than the linear model. Both models have the same performance which is quite good.
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Keywords: Inflation; GRDP; Spline Biresponse

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