Predicting Poverty Using Geospatial Data in Thailand
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Cited by:
- Hofer, Martin & Sako, Tomas & Martinez, Jr., Arturo & Addawe, Mildred & Durante, Ron Lester, 2020. "Applying Artificial Intelligence on Satellite Imagery to Compile Granular Poverty Statistics," ADB Economics Working Paper Series 629, Asian Development Bank.
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Keywords
big data; computer vision; data for development; machine learning algorithm; multidimensional poverty; official statistics; poverty; SDG; Thailand;All these keywords.
JEL classification:
- C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
- D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
- I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
- O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2021-05-31 (Big Data)
- NEP-CMP-2021-05-31 (Computational Economics)
- NEP-DEV-2021-05-31 (Development)
- NEP-SEA-2021-05-31 (South East Asia)
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