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Abstract
Forecasting is estimating the size or number of something in the future. Regression model that enters current independent variable value, and lagged value is called distributed-lag model, if it enters one or more lagged value, it is called autoregressive. Koyck method is used for dynamic model which the lagged length is unknown, for the known lagged length it is used the Almon method. Vector Autoregressive (VAR) is a method that explains every variable in the model depend on the lag movement from the variable itself and all the others variable. This research aimed to explain the application of Autoregressive distributed-lag model and Vector Autoregressive (VAR) method for the forecasting for export amount in DIY. It takes export amount in DIY and inflation data, kurs, and Indonesias foreign exchange reserve. Forecasting formation: defining Koyck and Almon distributed-lag dynamic model, then the best model is chosen and distribution-lag dynamic forecasting is performed. After that it is performed stationary test, co-integration test, optimal lag examination, granger causality test, parameter estimation, VAR model stability, and performs forecasting with VAR method. The forecasting result shows MAPE value from ARDL method obtained is 0.475812%, while MAPE value from VAR method is 0.464473%. Thus it can be concluded that Vector Autoregressive (VAR) method is more effective to be used in case study of export amount in DIY forecasting.
Keywords: Koyck; Almon; Lag; Autoregressive Distributed-Lag; Vector Autoregressive;
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References
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- Anton H., dan Susilo I., 2000, Aljabar Linear Elementer. Jakarta: Erlangga.
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References
Ansofino, dkk., 2016, Buku Ajar Ekonometrika, Edisi pertama.Yogyakarta: Deepublish.
Anton H., dan Susilo I., 2000, Aljabar Linear Elementer. Jakarta: Erlangga.
Djuraidah, Anik., Dewi Retno Sari Saputro., dan Aji Hamin Wigena, 1993, Model Vektor Autoregressive (VAR) Untuk Peramalan Curah Hujan di Indramayu. Forum Statistika dan Komputasi, 7-11.
G.S Madala., 1992, Introduction to Econometrics, Edisi 2. New York; Mac Millan PC.
Gujarati, Damodar N., 2003, Basic Econometrics. Singapura: McGraw-Hill,Inc.
Ispriyanti, Dwi., Firdha Rahmatika Pratami., dan Sudarno, 2016, Peramalan Dinamis Produksi Padi di Jawa Tengah Menggunakan Metode Koyck dan Almon. Jurnal Gaussian, 5, 91-97.
Makridakis., 1999, Metode dan Aplikasi Peramalan, Edisi 2. Jakarta: Binarupa Aksara.
Prasetya, Hery., 2009, Manajemen Operasi. Jakarta: Yogyakarta : MedPress.
Rosadi, Dedi., 2012, Ekonometrika Dan Nalisis Runtun Waktu Terapan Dengan Eviews.Yogyakarta: Penerbit Andi.
Setiawan., dan Desi Mustika., 2014, Peramalan Penjualan Sepeda Motor di Jawa Timur dengan Menggunakan Model Dinamis. Jurnal Sains dan Seni Pomits, 3, 224-229.
Sudjana.,1986., Metode Statistika. Tarsito: Bandung.
Sugito., Wilis Ardiana Pradana., dan Rita Rahmawati, 2016, Analisis Pengaruh Kurs Rupiah Terhadap Indeks Harga Saham Gabungan Menggunakan Distributed-lag Model. Jurnal Gaussian, 5, 221-227.
Supranto, J., 1995, Pengantar Statistik bidang hukum. Jakarta: Rineka Cipta.
Widarjono, Agus., 2007, Ekonometrika Teori dan Aplikasi untuk Ekonomi dan bisnis, Edisi kedua. Yogyakarta: Fakultas Ekonomi UII.