Redistributive land reforms, agricultural productivity, and structural change: New cross‐national evidence

DEVASHISH MITRA et al.

American Journal of Agricultural Economics2026https://doi.org/10.1002/ajae.70064article
AJG 3ABDC A*
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0.50

Abstract

Large‐scale land reforms constitute a substantial redistribution of wealth and reallocation of agricultural land, which is a major form of asset and production input in developing countries. While land redistribution (from the rich to the poor) remains a highly controversial issue, extensive evidence on its effect is limited. Using the most comprehensive global dataset on land reforms available to date, we investigate the impact of redistributive land reforms on agricultural productivity, along with the resulting structural change in the economy. First, we document that these reforms reduce per‐hectare agricultural output and agricultural mechanization by a statistically significant and quantitatively large amount. Second, these effects get worse with repeated redistributions, underpinning the potentially detrimental impact of ownership insecurity arising from frequent redistributions. Third, we find that the employment share of agriculture increases while the shares of industry and service sectors decrease. Importantly, this reallocation of labor occurs despite falling labor productivity in agriculture, which to begin with is lower than in industry and services, suggesting a reduction in real GDP.

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https://doi.org/https://doi.org/10.1002/ajae.70064

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@article{devashish2026,
  title        = {{Redistributive land reforms, agricultural productivity, and structural change: New cross‐national evidence}},
  author       = {DEVASHISH MITRA et al.},
  journal      = {American Journal of Agricultural Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/ajae.70064},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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