GRDP forecasting through night-time light data: Evidence from Indonesia

Agung Andiojaya (Statistician, Central Bureau of Statistic-Indonesia, Indonesia)
R.R. Nefriana (Statistician, Central Bureau of Statistic-Indonesia, Indonesia)
Riana Rizka (Statistician, Central Bureau of Statistic-Indonesia, Indonesia)
Titi Kanti Lestari (Statistician, Central Bureau of Statistic-Indonesia, Indonesia)

Jurnal Inovasi Ekonomi
Vol. 8 No. 01 (2023): April

Gross Regional Domestic Product (GRDP) is a widely used macroeconomic indicator to measure socioeconomic development. A comprehensive GRDP calculation requires complete data available from the national level down to minor administrative areas. However, institutions that carry out GRDP calculations often face challenges in obtaining complex data at smaller administrative levels. This paper explores the use of nighttime light (NTL) data as an alternative data source to estimate GRDP and its changes. The results of the panel data regression with random effects show that NTL data is statistically significant in describing GRDP in various Indonesian provinces. However, during the pandemic, NTL was not substantial in describing GRDP and showed movements that were not in line with GRDP.