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Agricultural Employment, Wages and Poverty in Developing Countries

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  • Katsushi S. Imai
  • Raghav Gaiha
  • Constanza Di Nucci

Abstract

Drawing upon panel data estimations, we have analysed the relationships among agricultural productivity, employment, technology, openness of the economy, inequality in land distribution and poverty. First, we have identified a number of important factors affecting agricultural productivity, such as agricultural R&D expenditure, irrigation, fertilizer use, agricultural tractor/machinery use, reduction in inequality of land distributions, or reduction in gender inequality. Second, while agricultural wage rate is negatively associated with agricultural productivity and food price in levels, the growth in agricultural wage rate is positively correlated with the growth in agricultural land or labour productivity as well as with the growth in food price, particularly after 2000. Contrary to the ILO’s (2012) claim that the gap has widened recently, this suggests the narrowing gap between wage and labour productivity once we focus on the conditional relationship between the two. Third, agricultural employment per hectare tends to increase agricultural productivity after taking account of the endogeneity of the former, while the growth in agricultural employment per hectare tends to increase the growth in non-agricultural employment over time with adjustment for endogeneity of the former. In this context, we have reviewed the recent literature and emphasised the importance of enhancing agricultural productivity and employment. Fourth, both agricultural growth and non-agricultural growth tend to lead to reduction in overall inequality. Finally, increase in agricultural productivity which is treated as endogenous will reduce poverty significantly through the overall economic growth. Overall, policies to increase agricultural productivity and agricultural employment are likely to increase non-agricultural growth, overall growth and reduce poverty, where guaranteeing gender inequality is likely to be one of the key factors.

Suggested Citation

  • Katsushi S. Imai & Raghav Gaiha & Constanza Di Nucci, 2014. "Agricultural Employment, Wages and Poverty in Developing Countries," Global Development Institute Working Paper Series 20914, GDI, The University of Manchester.
  • Handle: RePEc:bwp:bwppap:20914
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    References listed on IDEAS

    as
    1. Imai, Katsushi S. & Gaiha, Raghav & Garbero, Alessandra, 2017. "Poverty reduction during the rural–urban transformation: Rural development is still more important than urbanisation," Journal of Policy Modeling, Elsevier, vol. 39(6), pages 963-982.
    2. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    3. Katsushi S. Imai & Raghav Gaiha, 2014. "Dynamic and Long-term Linkages among Growth, Inequality and Poverty in Developing Countries," Economics Discussion Paper Series 1410, Economics, The University of Manchester.
    4. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 272-306, June.
    5. Katsushi S. Imai & Gordon Abekah-Nkrumah & Purnima Purohit, 2014. "Is Rural Contribution to Aggregate Poverty Reduction Substantial? New Evidence," Global Development Institute Working Paper Series 20814, GDI, The University of Manchester.
    6. Thirtle, Colin & Lin, Lin & Piesse, Jenifer, 2003. "The Impact of Research-Led Agricultural Productivity Growth on Poverty Reduction in Africa, Asia and Latin America," World Development, Elsevier, vol. 31(12), pages 1959-1975, December.
    7. Hayakawa, Kazuhiko, 2007. "Small sample bias properties of the system GMM estimator in dynamic panel data models," Economics Letters, Elsevier, vol. 95(1), pages 32-38, April.
    8. Katsushi Imai & Raghav Gaiha & Ganesh Thapa, 2010. "Is the Millennium Development Goal on Poverty Still Achievable? The Role of Institutions, Finance and Openness," Oxford Development Studies, Taylor & Francis Journals, vol. 38(3), pages 309-337.
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    More about this item

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • I39 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Other
    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products

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