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The composition of growth matters for poverty alleviation
Abstract
This paper contributes to explain the cross-country heterogeneity of the poverty response to changes in economic growth. It does so by focusing on the structure of output growth. The paper presents a two-sector theoretical model that clarifies the mechanism through which the sectoral composition of growth and associated labor intensity can affect workers' wages and, thus, poverty alleviation. Then it presents cross-country empirical evidence that analyzes first, the differential poverty-reducing impact of sectoral growth at various levels of disaggregation, and the role of unskilled labor intensity in such differential impact. The paper finds evidence that not only the size of economic growth but also its composition matters for poverty alleviation, with the largest contributions from labor-intensive sectors (such as agriculture, construction, and manufacturing). The results are robust to the influence of outliers, alternative explanations, and various poverty measures.
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Citations
Cited by
The (evolving) role of agriculture in poverty reduction—An empirical perspective
Christiaensen, L., Demery, L., & Kuhl, J. (2011) · Journal of Development Economics · doi:10.1016/j.jdeveco.2010.10.006 · Cited by 819
Agricultural Growth and Poverty Reduction: Additional Evidence
de Janvry, A., & Sadoulet, E. (2010) · The World Bank Research Observer · doi:10.1093/wbro/lkp015 · Cited by 484
Agriculture and development: A brief review of the literature
Dethier, J.-J., & Effenberger, A. (2012) · Economic Systems · doi:10.1016/j.ecosys.2011.09.003 · Cited by 380
The Rise of Large Farms in Land Abundant Countries: Do They Have a Future?
Deininger, K., & Byerlee, D. (2012) · World Development · doi:10.1016/j.worlddev.2011.04.030 · Cited by 352
Gaddis, I., & Klasen, S. (2014) · Journal of Population Economics · doi:10.1007/s00148-013-0488-2 · Cited by 338
Metadata
- Authors
- Loayza, N. V., & Raddatz, C.
- Venue
- Journal of Development Economics
- Publisher
- Elsevier BV
- Published
- 2010-09
- Volume
- 93
- Issue
- 1
- Pages
- 137-151
- ISSN
- 0304-3878 (ISSN-L)
- OpenAlex
- W2167475575
- Cited by
- 387
- References
- 0
- FWCI
- 65.13
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
