IDEAS home Printed from
   My bibliography  Save this paper

Targeting the poor and smallholder farmers: empirical evidence from Malawi


  • Houssou, Nazaire
  • Zeller, Manfred


This paper develops low cost, reasonably accurate, and simple models for improving the targeting efficiency of development policies in Malawi. Using a stepwise logistic regression (weighted) along with other techniques applied in credit scoring, the research identifies a set of easily observable and verifiable indicators for correctly predicting whether a household is poor or not, based on the 2004-05 Malawi Integrated Household Survey data. The predictive power of the models is assessed using out-of-sample validation tests and receiver operating characteristic curves, whereas the model’s robustness is evaluated by bootstrap simulation methods. Finally, sensitivity analyses are performed using the international and extreme poverty lines. The models developed have proven their validity in an independent sample derived from the same population. Findings suggest that the rural model calibrated to the national poverty line correctly predicts the status of about 69% of poor households when applied to an independent subset of surveyed households, whereas the urban model correctly identifies 64% of poor households. Increasing the poverty line improves the model’s targeting performances, while reducing the poverty line does the opposite. In terms of robustness, the rural model yields a more robust result with a prediction margin ±10% points compared to the urban model. While the best indicator sets can potentially yield a sizable impact on poverty if used in combination with a direct transfer program, some non-poor households would also be targeted as the result of model’s leakage. One major feature of the models is that household score can be easily and quickly computed in the field. Overall, the models developed can be potential policy tools for Malawi.

Suggested Citation

  • Houssou, Nazaire & Zeller, Manfred, 2009. "Targeting the poor and smallholder farmers: empirical evidence from Malawi," Research in Development Economics and Policy (Discussion Paper Series) 57988, Universitaet Hohenheim, Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics.
  • Handle: RePEc:ags:uhohdp:57988
    DOI: 10.22004/ag.econ.57988

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Ricker-Gilbert, Jacob & Jayne, Thomas S., 2009. "Do Fertilizer Subsidies Affect the Demand for Commercial Fertilizer? An Example from Malawi," 2009 Conference, August 16-22, 2009, Beijing, China 51606, International Association of Agricultural Economists.
    2. Grootaert, Christiaan & Braithwaite, Jeanine, 1998. "Poverty correlates and indicator-based targeting in Eastern Europe and the Former Soviet Union," Policy Research Working Paper Series 1942, The World Bank.
    3. Ahmed, Akhter U. & Rashid, Shahidur & Sharma, Manohar & Zohir, Sajjad, 2004. "Food aid distribution in Bangladesh," FCND briefs 173, International Food Policy Research Institute (IFPRI).
    4. Jonah B. Gelbach & Lant H. Pritchett, 2000. "Indicator targeting in a political economy: Leakier can be better," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 4(2), pages 113-145.
    5. Wodon, Quentin T., 1997. "Targeting the poor using ROC curves," World Development, Elsevier, vol. 25(12), pages 2083-2092, December.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Houssou, Nazaire & Asante-Addo, Collins & Andam, Kwaw S., 2017. "Improving the targeting of fertilizer subsidy programs in Africa south of the Sahara: Perspectives from the Ghanaian experience," IFPRI discussion papers 1622, International Food Policy Research Institute (IFPRI).

    More about this item


    Food Security and Poverty; Research Methods/ Statistical Methods;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:uhohdp:57988. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.