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Inference for the measurement of poverty in the presence of a stochastic weighting variable
Thuysbaert, Bram - In: Journal of economic inequality 6 (2008) 1, pp. 33-55
Persistent link: https://www.econbiz.de/10003711021
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Alternative weighting structures for multidimensional poverty assessment
Cavapozzi, Danilo; Han, Wei; Miniaci, Raffaele - In: Journal of economic inequality 13 (2015) 3, pp. 425-447
Persistent link: https://www.econbiz.de/10011327437
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Polarization measurement for ordinal data
Kobus, Martyna - In: Journal of economic inequality 13 (2015) 2, pp. 275-297
Persistent link: https://www.econbiz.de/10011327463
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Small area estimation-based prediction methods to track poverty : validation and applications
Christiaensen, Luc J.; Lanjouw, Peter; Luoto, Jill; … - In: Journal of economic inequality 10 (2012) 2, pp. 267-297
Persistent link: https://www.econbiz.de/10009625916
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Well-being inequality and reference groups : an agenda for new research
Praag, Bernard M. S. van - In: Journal of economic inequality 9 (2011) 1, pp. 111-127
Persistent link: https://www.econbiz.de/10009298957
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Multidimensional polarization for ordinal data
Kobus, Martyna; Kurek, Radosław - In: Journal of economic inequality 17 (2019) 3, pp. 301-317
Persistent link: https://www.econbiz.de/10012224970
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Predicting poverty using geospatial data in Thailand
Puttanapong, Nattapong; Martinez, Arturo M.; Addawe, Mildred - 2020
Poverty statistics are conventionally compiled using data from household income and expenditure survey or living …
Persistent link: https://www.econbiz.de/10012403931
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Applying artificial intelligence on satellite imagery to compile granular poverty statistics
Hofer, Martin; Sako, Tomas; Martinez, Arturo; Addawe, … - 2020
The spatial granularity of poverty statistics can have a significant impact on the efficiency of targeting resources …
Persistent link: https://www.econbiz.de/10012403950