A social engineering model for poverty alleviation
- Submitting institution
-
Aston University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 46451859
- Type
- D - Journal article
- DOI
-
10.1038/s41467-020-20201-4
- Title of journal
- Nature Communications
- Article number
- 6345
- First page
- -
- Volume
- 11
- Issue
- -
- ISSN
- 2041-1723
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
-
B - Aston Institute of Urban Technology and the Environment (ASTUTE)
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Mainstream econometrics has traditionally relied on a subjective poverty line to distinguish between rich and poor, an arbitrary metric that is unaffected by social movements, trade and consumption in sectors other than basic food. Combining three streams of learning - mathematics, machine learning and economics – this study has outlined a data based objective poverty line that uses consumption in all forms and hence is a key policy contender. The work has led to keen media interest (Science Mag: https://scienmag.com/poverty-line-concept-debunked-by-new-machine-learning-model/; Phys.Org: https://phys.org/news/2020-12-poverty-line-concept-debunked-machine.html); an entire Springer book chapter (ISBN-9789811522284), and career progression of one of the co-authors (Rice).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
