Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Re-evaluating the Malawian Farm Input Subsidy Programme

A Corrigendum to this article was published on 13 March 2017

Abstract

The Malawian Farm Input Subsidy Programme (FISP) has received praise as a proactive policy that has transformed the nation's food security, yet irreconcilable differences exist between maize production estimates distributed by the Food and Agriculture Organization of the United Nations (FAO), the Malawi Ministry of Agriculture and Food Security (MoAFS) and the National Statistical Office (NSO) of Malawi. These differences illuminate yield-reporting deficiencies and the value that alternative, politically unbiased yield estimates could play in understanding policy impacts. We use net photosynthesis (PsnNet) as an objective source of evidence to evaluate production history and production potential under a fertilizer input scenario. Even with the most generous harvest index (HI) and area manipulation to match a reported error, we are unable to replicate post-FISP production gains. In addition, we show that the spatial delivery of FISP may have contributed to popular perception of widespread maize improvement. These triangulated lines of evidence suggest that FISP may not have been the success it was thought to be. Lastly, we assert that fertilizer subsidies may not be sufficient or sustainable strategies for production gains in Malawi.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Agricultural yield trends across Malawi (2001–2014), measured using net primary productivity (NPP) and PsnNet.
Figure 2: District-level MoAFS maize production statistics before and after FISP.
Figure 3: Comparison between MoAFS maize estimates and FAO distributed data.
Figure 4: Comparison between the PsnNet-to-yield conversion, FAO distributed maize yield, MoAFS reported maize yield and NSO estimates.
Figure 5: District-level MoAFS maize yield statistics before and after FISP.
Figure 6: District-level maize PsnNet-to-yield statistics before and after FISP.

References

  1. 1

    Sanchez, P. A. En route to plentiful food production in Africa. Nat. Plants 1, 14014 (2015).

    Google Scholar 

  2. 2

    Chirwa, E. W. & Dorward, A. Agricultural Input Subsidies: The Recent Malawi Experience (Oxford Univ. Press, 2013).

    Google Scholar 

  3. 3

    Sachs, J. How Malawi Fed Its Own People (New York Times, 2012).

    Google Scholar 

  4. 4

    Denning, G. et al. Input subsidies to improve smallholder maize productivity in Malawi: toward an African green revolution. PLoS Biol. 7, e1000023 (2009).

    Google Scholar 

  5. 5

    Malawi – Can It Feed Itself? The Economist (1 May 2008).

  6. 6

    Minot, N. & Benson, T. Fertilizer Subsidies in Africa: Are Vouchers the Answer? (International Food Policy Research Institute, 2009).

    Google Scholar 

  7. 7

    Ricker-Gilbert, J., Jayne, T. S. & Chirwa, E. Subsidies and crowding out: a double-hurdle model of fertilizer demand in Malawi. Am. J. Agric. Econ. 93, 26–42 (2011).

    Google Scholar 

  8. 8

    Chinsinga, B. & Poulton, C. Beyond technocratic debates: the significance and transience of political incentives in the Malawi Farm Input Subsidy Programme (FISP). Dev. Policy Rev. 32, s123–s150 (2014).

    Google Scholar 

  9. 9

    Jerven, M. The political economy of agricultural statistics and input subsidies: evidence from India, Nigeria and Malawi. J. Agrar. Chang. 14, 129–145 (2014).

    Google Scholar 

  10. 10

    Dorward, A. Evaluation of the 2006/7 Agricultural Input Subsidy Program—Final Report (School of Oriental and African Studies, 2008).

  11. 11

    Dorward, A. & Chirwa, E. The Malawi Agricultural Input Subsidy Programme: 2005-6 to 2008-9. Int. J. Agric. Sustain. 9, 232–247 (2011).

    Google Scholar 

  12. 12

    Chibwana, C., Fisher, M. & Shively, G. Cropland allocation effects of agricultural input subsidies in Malawi. World Dev. 40, 124–133 (2012).

    Google Scholar 

  13. 13

    Chinsinga, B. & O'Brien, A. Planting Ideas: How Agricultural Subsidies are Working in Malawi (Africa Research Institute, 2008).

    Google Scholar 

  14. 14

    Jayne, T. S. & Rashid, S. Input subsidy programs in sub-Saharan Africa: a synthesis of recent evidence. Agric. Econ. 44, 547–562 (2013).

    Google Scholar 

  15. 15

    Ricker-Gilbert, J., Mason, N. M., Darko, F. A. & Tembo, S. T. What are the effects of input subsidy programs on maize prices? Evidence from Malawi and Zambia. Agric. Econ. 44, 671–686 (2013).

    Google Scholar 

  16. 16

    Jayanthi, H. et al. Modeling rain-fed maize vulnerability to droughts using the standardized precipitation index from satellite estimated rainfall—Southern Malawi case study. Int. J. Disaster Risk Reduct. 4, 71–81 (2013).

    Google Scholar 

  17. 17

    GIEWS Country Briefs—Malawi (FAO, 2016).

  18. 18

    Bastiaanssen, W. G. M. & Ali, S. A new crop yield forecasting model based on satellite measurements applied across the Indus Basin, Pakistan. Agric. Ecosyst. Environ. 94, 321–340 (2003).

    Google Scholar 

  19. 19

    Doraiswamy, P. C. et al. Application of MODIS derived parameters for regional crop yield assessment. Remote Sens. Environ. 97, 192–202 (2005).

    Google Scholar 

  20. 20

    Reeves, M. C., Zhao, M. & Running, S. W. Usefulness and limits of MODIS GPP for estimating wheat yield. Int. J. Remote Sens. 26, 1403–1421 (2005).

    Google Scholar 

  21. 21

    Lobell, D. B. The use of satellite data for crop yield gap analysis. F. Crop. Res. 143, 56–64 (2013).

    Google Scholar 

  22. 22

    Peng, D. et al. Modelling paddy rice yield using MODIS data. Agric. For. Meteorol. 184, 107–116 (2014).

    Google Scholar 

  23. 23

    MODIS Gross Primary Productivity and Net Photosynthesis (MOD17A2H)—V006 (NASA EOSDIS Land Processes DAAC, 2000).

  24. 24

    Running, S., Mu, Q. & Zhao, M. MOD17A2H MODIS/Terra Gross Primary Productivity 8-Day L4 Global 500m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015).

  25. 25

    Zhao, M. & Running, S. W. User's Guide—Daily GPP and Annual NPP (MOD17A2/A3) Products—NASA Earth Observing System MODIS Land Algorithm (NASA EOSDIS Land Processes DAAC, 2015).

  26. 26

    Zhao, M. S., Heinsch, F. A., Nemani, R. R. & Running, S. W. Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens. Environ. 95, 164–176 (2005).

    Google Scholar 

  27. 27

    MODIS Net Primary Productivity (MOD17A3)—Version 055 (NASA EOSDIS Land Processes DAAC), 2000).

  28. 28

    Production, Area Harvested, and Yield of Maize in Malawi (FAO, 2016).

  29. 29

    Crop Production & Area Harvested by Extension Planning Area (Agricultural Production Estimates Survey, MoAFS, 2012).

  30. 30

    National Census of Agriculture and Livestock (NACAL) 2006/07—Main Report (NSO Malawi, 2010).

  31. 31

    Jayne, T. S., Chapoto, A., Minde, I. J. & Donovan, C. The 2008/09 Food Price and Food Security Situation in Eastern and Southern Africa: Implications for Immediate and Longer Run Responses (Michigan State Univ., 2008).

    Google Scholar 

  32. 32

    National Food Security Forecast, April 2013 to March 2014 Bulletin No. 9/13, Vol. 1 (Malawi Ministry of Economic Planning & Development, 2012).

  33. 33

    Malawi Facing Serious Food Crisis. FAO (11 August 2005).

  34. 34

    Malawi 10-Day Rainfall & Agrometeorological Bulletin (WAMIS, 2005).

  35. 35

    Holden, S. & Lunduka, R. Too Poor To Be Efficient? Impacts of the Targeted Fertilizer Subsidy Programme in Malawi on Farm Plot Level Input Use, Crop Choice and Land Productivity (Noragric, 2010).

  36. 36

    Rural Malawi Comprehensive Food Security and Vulnerability Analysis (CFSVA) (WFP, 2010).

  37. 37

    Malawi Vulnerability Assessment Committee (MVAC) Response Program Report (WFP, 2012).

  38. 38

    The Malawi Vulnerability Assessment Committee (MVAC): October 2012 Update Bulletin No. 8, Vol. 2 (MVAC, 2012).

  39. 39

    Malawi: Vulnerability Assessment Committee Results (United Nations Office for the Coordination of Humanitarian Affairs, 2015).

  40. 40

    Snapp, S., Jayne, T. S., Mhango, W., Benson, T. & Ricker-Gilbert, J. Maize Yield Response to Nitrogen in Malawi's Smallholder Production Systems (International Food Policy Research Institute, 2014).

    Google Scholar 

  41. 41

    Mpeketula, P. Soil Organic Carbon Dynamics and Mycorrhizal Fungal Diversity in Contrasting Agroecosystems. PhD thesis, Michigan State Univ. (2016).

  42. 42

    Tully, K., Sullivan, C., Weil, R. & Sanchez, P. The state of soil degradation in sub-Saharan Africa: baselines, trajectories, and solutions. Sustainability 7, 6523–6552 (2015).

    Google Scholar 

  43. 43

    Tadross, M. et al. Growing-season rainfall and scenarios of future change in southeast Africa: implications for cultivating maize. Clim. Res. 40, 147–161 (2009).

    Google Scholar 

  44. 44

    Methods & Standards: Agricultural Production—Crops Primary (FAO, 2016).

  45. 45

    Banda, B. B. CountrySTAT for Sub-Saharan Africa—Malawi Panorama Report II—Project GCP/GLO/208/BMG (FAO, 2011).

  46. 46

    MODIS Land Cover Type (MCD12Q1)—Version 051 (NASA EOSDIS Land Processes DAAC, 2000).

  47. 47

    Land Cover and Land Cover Change of Malawi (1990–2010) (FAO, 2013).

  48. 48

    Global Land Cover (GLC) 2000 (ESA, 2005).

  49. 49

    GlobCover 2005-06 (ESA, 2008).

  50. 50

    GlobCover 2009 (ESA, 2010).

  51. 51

    World Land Use—Land Cover (IFPRI, 2002).

  52. 52

    Messina, J. et al. Population Growth, Climate Change and Pressure on the Land—Eastern and Southern Africa (Global Center for Food Systems Innovation, 2014).

    Google Scholar 

  53. 53

    Establishing Food Security by Improving Maize Production (IFAD); https://www.ruralpovertyportal.org/country/voice/tags/malawi/malawi_foodsecurity

  54. 54

    Zhang, H. & Oweis, T. Water–yield relations and optimal irrigation scheduling of wheat in the Mediterranean region. Agric. Water Manag. 38, 195–211 (1999).

    Google Scholar 

  55. 55

    Earth Observation System Clearing House (ECHO) (NASA EOSDIS, 2009).

  56. 56

    MODIS Reprojection Tool User's Manual—Release 4.1 (USGS Earth Resources Observation and Science Center, 2011).

  57. 57

    ArcGIS Desktop Release 10.0–10.2 (Environmental Systems Research Institute, 2014).

  58. 58

    Amos, B. & Walters, D. T. Maize root biomass and net rhizodeposited carbon. Soil Sci. Soc. Am. J. 70, 1489 (2006).

    Google Scholar 

  59. 59

    Hay, R. K. M. Harvest index: a review of its use in plant breeding and crop physiology. Ann. Appl. Biol. 126, 197–216 (1995).

    Google Scholar 

  60. 60

    Brewer, C. et al. Color Brewer v.2.0 (2016); http://www.ColorBrewer2.org

Download references

Acknowledgements

We are grateful for the expertise and assistance provided by faculty and staff at the Lilongwe University of Agriculture and Natural Resources (LUANAR) and to those at Africa Rising for facilitating our research in the field. Special thanks to M.N. Kakwera of LUANAR and R. Chikowo of Africa Rising. Additional thanks to L. Liu for assistance with database construction. We also thank the reviewers of this manuscript for their many helpful comments. This work was supported by the Bill & Melinda Gates Foundation under Grant OPP1076311 and through support of the United States Agency for International Development AID-OAA-A-13-00006. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the US Agency for International Development or the US Government.

Author information

Affiliations

Authors

Contributions

J.P.M., B.G.P. and S.S.S. contributed equally to writing and researching this work.

Corresponding author

Correspondence to Joseph P. Messina.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Figures 1 and 2. (PDF 456 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Messina, J., Peter, B. & Snapp, S. Re-evaluating the Malawian Farm Input Subsidy Programme. Nature Plants 3, 17013 (2017). https://doi.org/10.1038/nplants.2017.13

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing