Judul | : | PENDUGAAN PARAMETER MODEl DISTRIBUTED LAG POLA POLINOMIAL MENGGUNAKAN METODE ALMON | |||
Abstrak | : | The distributed lag model is a regression model that describes the relationship between the dependent variable of a given period and the independent variables of a certain or previous periods. The model can be used to determine the impact of the independent variable to dependent variables over time and forecast time series data for the next periods. There are two forms of distributed lag model that have been widely proposed in the estimation of distributed lag regression model. The first form is proposed by Koyck and the second form by Almon. This paper aims to apply the Almon model to examine the effect of the ratio of BOPO (Operating Cost and Operating Income) to the ROA (Return on Asset) of a government bank based on quarterly data, to estimate its parameters, to examine the feasibility of the model, and to predict the next quarter. Results shows that distributed lag model is = 10.110 - 0.078 + 0.015 + 0.026 – 0.045 with Yt is ROA, and Xt is the ratio BOPO on the 1st quarter until the previous 3 quarters. The model is quite good according to the determination coefficient that is 0.75, no autocorrelation in the model, t test and F test are also significant. Based on the model, the value of ROA ratio next quarter predicted 4.63%. The decrease in profitability ROA ratio is due to an increase in interest expense while interest income can not compensate |
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Tahun | : | 2021 | Media Publikasi | : | Jurnal Nasional Terakreditasi B |
Kategori | : | Jurnal | No/Vol/Tahun | : | 15 / 4 / 2021 |
ISSN/ISBN | : | doi.org/10.30598/barekengvol15iss4pp761-772 | |||
PTN/S | : | Universitas Pakuan | Program Studi | : | MATEMATIKA |
Bibliography | : | Intriligator, M. Econometrics Models, Techniques, and Applications 2nd Edition. Los Angeles: University of California. 2006 Veerbek, M., 2005, A Guide to Modern Econometrics, Second Edition. Prentice Hall, Englewood Cliffs, New York University. Pradana, W.A, R. Rahmawati, S. Sugito. 2016. Analisis Pengaruh Kurs Rupiah terhadap Indeks Harga Saham Gabungan Menggunakan Distributed Lag Model. Jurnal Gaussian Vol 5 No. 1 : 221-227. Majid, A., Aslam, M., Altaf, S., & Amanullah, M. 2019. Addressing the distributed lag models with heteroscedastic errors. Communications in Statistics - Simulation and Computation, 1–19. Rangkuti, A. 2007. Kombinasi Penaksiran Model Lag Terdistribusi Dengan Ekspektasi Adaptif Dan Penyesuaian Parsial. Jurnal Matematika, Statistika, dan Komputasi Vol 3 No.2 : 96-102. Aqibah, M., N. L. P. Suciptawati, dan IW. Sumarjaya. 2020. Model Dinamis Autoregressive Distributed Lag (Studi Kasus: Pengaruh Kurs Dolar Amerika dan Inflasi terhadap Harga Saham Tahun 2014-2018). E-Jurnal Matematika Universitas Udayana Vol. 9(4) : 240-250. Lukman, and Adewale, F. 2021. Almon KL Estimator for The Distributed Lag Model. Arab Journal of Basic and Applied Science Vol 28 Issue 1 : 406-412 Gujarati, D. N. 2006. Essentials of Econometrics. Third Edition. New York: The McGraw-Hill. Laporan Keuangan Triwulan PT. Bank Rakyat Indonesia (Persero). www.bri.co.id. [diakses:15 Mei 2019]. Widarjono, A. 2007. Ekonometrika: Teori dan Aplikasi untuk Ekonomi dan Bisnis. Edisi Kedua. Yogyakarta: Ekonisia Fakultas Ekonomi. Universitas Indonesia. Walpole, R.E. 2008. Probability and Statistics for Enginenereer Scientists 8 edition. New Jersey: Prentice Hall Mardiatmoko, G. 2020. Pentingnya Uji Asumsi Klasik pada Model Regresi Linear Berganda. Barekeng: Jurnal Ilmu Matematika dan Terapan Vol 14 Issue 3 : 333 - 342 Sembiring, R. K. 2003. Analisis Regresi. Edisi Kedua. Bandung: Penerbit ITB. Supranto, J. Statistik Teori dan Aplikasi. Edisi Ketujuh Jilid 2. Jakarta: Erlangga. 2009. Santoso, S. Buku Latihan SPSS Statistik Parametrik. Jakarta: Elex Media Komputindo. 2000. |
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URL | : | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/3885 |