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On the Determinants of Low Productivity of Rice Farming in Mozambique: Pathways to Intensification

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In Pursuit of an African Green Revolution

Part of the book series: Natural Resource Management and Policy ((NRMP,volume 48))

Abstract

This chapter analyzes a rice farmer panel data set that was collected in 2007/2008 and 2011 in Mozambique. We found that in a rainfed area, farmers expanded their cultivated area as local paddy prices increased in parallel with international rice price trends. However, the average yield decreased as the farmers were approaching to marginal land of their land frontier. To improve yield for further production increases, the production mode must shift from extensification to intensification through the introduction of land-saving technologies, such as irrigation development. A lesson learnt from the Chokwe Irrigation Scheme, the largest scheme of the country, is useful for this aim. A key lesson is that assuring water access is crucially important because timely water application directly increases output and also increases the returns to chemical fertilizer use. In Chokwe, a recent increase in the real price of modern inputs, such as fertilizer and tractors, saw farmers substitute family labor for modern inputs, that is, a return to traditional farming. To recapture the momentum of modernization, our analyses suggest that training and market access are important because those farmers who received a management training program did not give up using animal traction . Additionally, those who had access to rice buyers kept using chemical fertilizer.

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Notes

  1. 1.

    The survey plot is the plot recognized as the most important one by the interviewed household, for which we collected detailed input and output data.

  2. 2.

    Note that the cultivated area of non-survey plots is based on farmers self-claim and we asked this type of question in different manners for double checking purposes. That being said, we received a wide range of answers as reported in the table. For the survey plot we measured the size with a GPS device.

  3. 3.

    We compute the yield based on farmers’ recall of their harvest. Usually, they reported the harvest in terms of container they used (e.g., bags). We convert their answer to kilograms using a converter. For example, the most common container for rice is a 50 kg bag, which is converted to 38 kg of paddy rice (24 % depreciation).

  4. 4.

    For example, FOB price of Thai rice (A1 Super grade) increased from 272 USD/ton to 466 USD/ton by 71 % from 2007 to 2011, while Arabian Gulf FOB price of urea increased from 310 USD/ton to 400 USD/ton (29 %) in the same period.

  5. 5.

    For example, in the Philippines the proportion was 49 % in 1966 and 71 % in 1976 in Laguna, and 60 % in 1967 and 43 % in 1971 in Central Luzon. In Tamil Nadu, India, the proportion was 73 % in 1971.

  6. 6.

    The use of thresher in 2007 is not estimated because only 7 % of the farmers used it. Tractor use and thresher use in 2011 are not estimated because farmers used neither method at all.

  7. 7.

    The variables excluded are average schooling years, number of cattle, credit use, extension service received, and proportion of salary earners.

  8. 8.

    We use a locally weighted scatterplot smoothing method setting bundwidth at 0.8.

References

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Correspondence to Kei Kajisa .

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Appendix

Appendix

Table 2.11 Determinants of paddy yield, fertilizer application, labor input, and animal use in 2011, Chokwe irrigation scheme in Mozambique

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Kajisa, K. (2016). On the Determinants of Low Productivity of Rice Farming in Mozambique: Pathways to Intensification. In: Otsuka, K., Larson, D. (eds) In Pursuit of an African Green Revolution. Natural Resource Management and Policy, vol 48. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55693-0_2

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