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Satellite Data for Nowcasting : Estimating Cambodia’s GDP in Real Time Using Satellite Data in a Machine Learning Framework / Iyke Maduako, Dharana Rijal, Alberto Sanchez Rodelgo.
- Format:
- Book
- Government document
- Author/Creator:
- Maduako, Iyke.
- Series:
- Selected Issues Papers; Selected Issues Paper ; No. 2026/001
- Selected Issues Papers
- Language:
- English
- Physical Description:
- 1 online resource (12 pages)
- Place of Publication:
- Washington, D.C. : International Monetary Fund, 2026.
- Summary:
- Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining satellite-derived indicators (e.g., nighttime lights, NO₂ emissions, vegetation indices) with traditional high-frequency indicators in a machine learning framework significantly improves the accuracy of GDP nowcasts. Moreover, satellite data enables closer examination of subnational patterns, providing granular, near-real-time insights into economic activity. These findings highlight the potential of non-traditional approaches to complement conventional methods and strengthen macroeconomic surveillance in data-scarce environments.
- Notes:
- Description based on print version record.
- ISBN:
- 979-82-290-3533-0
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