Mapping the Forecasting Value of Gross Regional Domestic Product (GRDP) of East Nusa Tenggara Province with Spatial Dynamic Panel Data Models Approach
Keywords:
Gross Regional Domestic Product, Dynamic Panel Spatial Prediction, Mean Absolute Percentage Error
Abstract
The Province of East Nusa Tenggara (NTT) is categorized as a lagging region based on the value of Gross Regional Domestic Product (GRDP) and belongs to the lowest group at the national level. This underdevelopment has become a special concern for the government in every work program. This condition is an appropriate reference for periodic analysis in a certain time series. The analysis is carried out in various aspects that are dynamic by paying attention to spatial conditions, because each region has different characteristics. One of the main concerns is the value of GRDP, which is a measure of the welfare of a region. The estimation of the regency / city GRDP value model in NTT Province has been carried out, so the existing model is then used for prediction analysis based on updated real time data which is then mapped to see the distribution of GRDP values as a description of actual conditions. The prediction process is carried out using a method that is able to accommodate the characteristics of spatial data and a combination of time series and cross section data, so the appropriate method is dynamic panel spatial. The prediction results obtained the accuracy value of the Mean Absolute Percentage Error (MAPE) criterion of 7.47%, which means less than 20%, so it can be concluded that the dynamic panel spatial models is the right method to be used to forecasting the value of district/city GRDP in NTT Province for the next period of time. The prediction results obtained by the distribution of GRDP values are divided into four categories, namely low, medium, high and very high, which are marked by different colors on the mapping.Downloads
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Baltagi, B. H. (2021). Econometric Analysis of Panel Data (Springer Texts in Business and Economics) - Sixth Edition. In Springer.
Baltagi, B. H., Fingleton, B., & Pirotte, A. (2014). Estimating and forecasting with a dynamic spatial panel data model. Oxford Bulletin of Economics and Statistics, 76(1), 112–138. https://doi.org/10.1111/obes.12011
Buan, F. C H; Ludji, Dian Grace., Maure, O. P. (2023). Leibniz: Jurnal Matematika. Jurnal Matematika, 1(1), 21–35.
Buan, F. C. H., Fitriani, R., & Nurjannah. (2021). Estimating Gross Regional Domestic Product (GRDP ) District / City in East Nusa Tenggara with Spatial Dynamic Panel Data. Wacana, 24(4), 190–194.
de Myttenaere, A., Golden, B., Le Grand, B., & Rossi, F. (2016). Mean Absolute Percentage Error for regression models. Neurocomputing, 192, 38–48. https://doi.org/10.1016/j.neucom.2015.12.114
Elhorst, J. P. (2014). Dynamic Spatial Panels: Models, Methods and Inferences. SpringerBriefs in Regional Science, 95–119. https://doi.org/10.1007/978-3-642-40340-8_4
LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. In Introduction to Spatial Econometrics (Issue March). https://doi.org/10.1111/j.1467-985x.2010.00681_13.x
Published
2023-06-30
How to Cite
Buan, F., & Ludji, D. (2023). Mapping the Forecasting Value of Gross Regional Domestic Product (GRDP) of East Nusa Tenggara Province with Spatial Dynamic Panel Data Models Approach. Jurnal Saintek Lahan Kering, 6(1), 26-28. https://doi.org/https://doi.org/10.32938/slk.v6i1.2247
Section
Original research article
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