GROSS REGIONAL DOMESTIC PRODUCT FORECASTS USING TREND ANALYSIS: CASE STUDY OF BANGKA BELITUNG PROVINCE

Nurmalita Oktaviana, Nurisqi Amalia

Abstract


Gross Regional Domestic Product (GRDP) is one of the important indicators to determine the economic conditions in the region. This study aims to forecast the Gross Regional Domestic Product (GRDP) of the Province of Bangka Belitung Islands which is dominated by tourism sector. This forecasting to be expected to give information to formulate a type of policy action that will be conducted by decision makers based on GRDP data. GRDP data are from the first quarter of 2010 to the fourth quarter of 2017 on the basis of constant prices in 2010. Data sources are obtained from Central Bureau of Statistics (BPS) of the Province of Bangka Belitung Islands. The forecasting method used is the research is trend analysis. The results of the GRDP forecasting of Bangka Belitung Province in the first quarter of 2018 to the fourth quarter of 2022 shows an increasing trend. It can be seen from historical data that shows an increasing trend as evidenced from the graph on linear trends. The increasing trend in GRDP of the Bangka Belitung Islands Province for the next five years is supported by government policies that prioritize the tourism sector. Consequently, by prioritizing the tourism sector, this will increase economic growth and can reduce GRDP dependency on mining sector, especially tin that has been continuously decreased.


Keywords


Forecasting; GRDP; Time Series; Trend Analysis

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References


Abel, A.B., and Bernake, B.S. (2001). Macroeconomics. New York: Addison Wesley Longman. Inc.

Aref, F. (2011). The Effects of Tourism on Quality of Life: A Case Study of Shiraz. Iran. Life Science Journal, 8(2), 26-30.

Badan Perencanaan Pembangunan Daerah. (2018). Rencana Pembangunan Jangka Menengah Daerah (RPJMD) Provinsi Bangka Belitung Tahun 2017-2022. (Online) Belitung. Available from http://bappeda.babelprov.go.id (Accessed: 29th March, 2018).

Badan Pusat Statistik Provinsi Bangka Belitung. (2018). PDRB Triwulanan Provinsi Kepulauan Bangka Belitung Atas Dasar Harga Konstan Menurut Lapangan Usaha (Million Rupiahs) 2010-2017. (Online) Jakarta. Available from https://babel.bps.go.id/ (Accessed: 29th, March 2018).

Bangka Belitung Provinsi. (2018). Pertumbuhan Ekonomi Tantangan Terbesar Provinsi Bangka Belitung. (Online) Belitung. Available from http://babelprov.go.id (Accessed: 29th, March 2018).

Bappenas. (2018). Sistem Informasi dan Manajemen Data Dasar Regional. Analisis Pembangunan Wilayah Provinsi Bangka Belitung. (Online) Jakarta. Available from http://simreg.bappenas.go.id. (Accessed: 29th, March 2018).

Dajan, A. (1986). Pengantar Metode Statistik. Jilid I. Jakarta: LP3ES.

Dias, F., Pinheiro, M., and Rua, A. (2015). Forecasting Portuguese GDP with factor models: Pre and post-crisis evidence. Economic Modelling 44, 266-272.

Dovern, J. (2013). When are GDP forecasts updated? Evidence from a large international panel. Economics Letters 120, 521-524.

Gregory, P.R., and Stuart, R.C. (1992). Comparative Economic’System. Fourth Edition. New Jersey: Houghton Mifflin Company.

Hanke, John, et.al. (2003). Peramalan Bisnis. Jakarta: Pearson Education Asia Ptc. Ltd dan PT. Pren Hallindo.

Jansen, W.J., Jin, X., and de Winter., J.M. (2016). Forecasting and nowcasting real GDP: Comparing statistical models and subjective forecasts. International Journal of Forecasting 32, 411-436.

Jiang, Y., Guo, Y., and Zhang, Y. (2017). Forecasting China’s GDP growth using dynamic factors and mixed-frequency data. Economic Modelling 66, 132-138.

Makridakis, S., Andersen, A., Carbone, R., Fildes, R., Hibon, M., Lewandowski, R., Newton, J., Parzen, E. and Winkler, R.. (1982) The accuracy of extrapolation (time series) methods: Results of a forecasting competition. Journal of the Royal Statistical Society. Series D (The Statistician), 34(2), 261-262.

Maity, B., and Chatterjee, B. (2012). Forecasting GDP growth rates of India: An empirical study. International Journal of Economics and Management Sciences, 1(9), 52-58.

Modis, T. (2013). Long-term GDP forecasts and the prospects for growth. Technological Forecasting & Social Change 80, 1557-1562.

Pleanggra, F. and Yusuf, E.A. (2012). Analisis Pengaruh Jumlah Obyek Wisata, Jumlah Wisatawan dan Pendapatan Perkapita Terhadap Pendapatan Retribusi Obyek Pariwisata 35 Kabupaten/ Kota di Jawa Tengah Doctoral dissertation. Fakultas Ekonomika dan Bisnis. Universitas Diponegoro.

Projogo, M.J. (1976): Pengantar Pariwisata Indonesia; Jakarta: Direktorat Jenderal Pariwisata.

Rahardja, P., and Manurung, M. (2001). Teori Ekonomi Makro: Suatu Pengantar. Jakarta: LP FE Universitas Indonesia.

Sebele, L.S. (2010). Community-Based Tourism Ventures. Benefits and Challenges: Khama Rhino Sanctuary Trust. Central District. Botswana. Tourism Management, 31, 136-146.

Satria, I., Yasin, H., and Suparti. (2015). Proyeksi Data Produk Domestik Bruto (PDB) dan Foreign Direct Investment (FDI) Menggunakan Vector Autoregressive (VAR). Jurnal Gaussian, 4(4), 895-905.

Sujitno, S. (2007). Dampak Kehadiran Timah Indonesia Sepanjang Sejarah Pada Aspek Politik Ekonomi Sosial Budaya. Jakarta: Cempaka Publishing.

Utama, M.S. and Wirawan, I.G.P.N. (2014). Model Box-Jenkins Dalam Rangka Peramalan Produk Domestik Regional Bruto Provinsi Bali. Universitas Uda-yana. Jurnal Buletin Studi Ekonomi, 19(1), 92-104.

Untong, A., Kaosa-ard, M., Ramos, V., Sangkakorn, K., and Rey-Maquieria, J. (2010). Factors Influencing Local Resident Support for Tourism Development: A Structural Equation Model. The APTA Conference 2010. Macau.

UNWTO. (2013). Sustainable Tourism for Development Guidebook. Madrid. Spain: World Tourism Organization.

Wabomba, M.S., Mutwiri, M.P., and Frederick, F. (2016). Modeling and Forecasting Kenyan GDP Using Autoregressive Integrated Moving Average (ARIMA). Science Journal of Applied Mathematics and Statistics, 4(2), 64-73.

Xu. Q., Zhuo, X., Jiang, C., Liu, X. and Liu, Y. (2018). Group penalized unrestricted mixed data sampling model with application to forecasting US GDP growth. Economic Modelling 75, 221-236.




DOI: https://doi.org/10.18196/jesp.19.2.5005

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