PERAMALAN INFLASI DI INDONESIA: DYNAMIC MODEL AVERAGE

M. Rizki Nasution, Dede Ruslan, Ahmad Albar Tanjung

Abstract


This research is to forecast inflation in Indonesia on a national scale. Forecasting use in samples and out of samples as research. Converting results using the Dynamic Dynamic Model can give results. The estimation results are carried out in the BVAR form. In forecasting using time series data for the period 2010 to 2019. Forecasting with the value of RMSE is selected in the IHK_SAND variable and another variable IHK_PROD is accepted; INF; CPI_BM; IHK_PALGBB; IHK_KES; IHK_TKJK; and IHK_MJMRT.

Keywords


Performance; Dynamic Model Average; DMA; Forecasting in Inflation

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References


Basri, S., Yusuf, Y., & Putra, H. (2014). Perbandingan Tingkat Inflasi Provinsi Riau Dengan Tingkat Inflasi Provinsi Yang Berbatasan Langsung Dengan Provinsu Riau (Sumatera Utara, Sumatera Barat Dan Jambi) Selama Periode 2009 - 2013. Jurnal Online Mahasiswa Fakultas Ekonomi Universitas Riau, 1(2), 1–13.

Fajar, M., & Padjadjaran, U. (2018). Meningkatkan Akurasi Peramalan dengan Menggunakan Metode Hybrid Singular Spectrum Analysis-Multilayer Perceptron Neural Networks. (February). https://doi.org/10.13140/RG.2.2.34999.01443

Irawati, L., Tarno, T., & Yasin, H. (2015). Peramalan Indeks Harga Konsumen 4 Kota Di Jawa Tengah Menggunakan Model Generalized Space Time Autoregressive (Gstar). None, 4(3), 553–562.

Juhro, S. M., & Iyke, B. N. (2019). Forecasting Indonesian inflation within an inflation-targeting framework: Do large-scale models pay off? Buletin Ekonomi Moneter Dan Perbankan, 22(4), 423–436. https://doi.org/10.21098/bemp.v22i4.1235

Koop, G., & Korobilis, D. (2011). UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so? Economic Modelling, 28(5), 2307–2318. https://doi.org/10.1016/j.econmod.2011.04.008

Rosy, M. R. S. S. (2013). PERAMALAN INDEKS HARGA KONSUMEN ( IHK ) KOTA MALANG BULAN JANUARI SAMPAI BULAN JUNI TAHUN 2013 MENGGUNAKAN METODE AUTOREGRESSIVE INTEGRATED MOVING AVERAGE ( ARIMA ) Rosy M ., Rahardjo S ., Susiswo Jurusan Matematika Fakultas MIPA Universitas Negeri Malang.

Wright, J. H. (2009). Forecasting US inflation by bayesian model averaging. Journal of Forecasting, 28(2), 131–144. https://doi.org/10.1002/for.1088




DOI: http://dx.doi.org/10.25105/me.v28i2.7085

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