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Editor's choice From Guesstimates to GPStimates: Land Area Measurement and Implications for Agricultural Analysis

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  • Calogero Carletto
  • Sydney Gourlay
  • Paul Winters

Abstract

Development goals and poverty-reduction policies are often focused on raising agricultural productivity and dependent on farm household level data. Historically, household surveys commonly employed self-reported land area measurements for cost-effectiveness and convenience. However, as we illustrate here, these self-reported estimates may measure land with systematic error resulting in sizable biases. This has led to the increased use of Global Positioning Systems (GPS) and other modern technologies to measure land size. In this article, we compare self-reported (SR) and GPS land measurement to assess the differences between the measures, to identify the sources of differences, and to determine the implications of the different measures on agricultural analysis. The results from the analysis of data from four African countries indicate that SR land areas systematically differ from GPS land measures and that this difference leads to biased estimates of the relationship between land and productivity and consistently low estimates of land inequality. Through the evidence and analysis presented here, we conclude that the more systematic use of GPS-measured land area will result in improved agricultural statistics and more accurate analysis of agricultural relationships, which will better inform future policy.

Suggested Citation

  • Calogero Carletto & Sydney Gourlay & Paul Winters, 2015. "Editor's choice From Guesstimates to GPStimates: Land Area Measurement and Implications for Agricultural Analysis," Journal of African Economies, Centre for the Study of African Economies (CSAE), vol. 24(5), pages 593-628.
  • Handle: RePEc:oup:jafrec:v:24:y:2015:i:5:p:593-628.
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    File URL: http://hdl.handle.net/10.1093/jae/ejv011
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    Cited by:

    1. Abay, Kibrom A. & Abate, Gashaw & Barrett, Christopher B. & Bernard, Tanguy, 2018. "Correlated Non-Classical Measurement Errors, ‘Second Best’ Policy Inference and the Inverse Size-Productivity Relationship in Agriculture," 2018 Annual Meeting, August 5-7, Washington, D.C. 274248, Agricultural and Applied Economics Association.
    2. Wineman, Ayala & Jayne, Thomas S., 2017. "Land Prices Heading Skyward? An Analysis Of Farmland Values Across Tanzania," Feed the Future Innovation Lab for Food Security Policy Research Papers 261670, Michigan State University, Department of Agricultural, Food, and Resource Economics, Feed the Future Innovation Lab for Food Security (FSP).
    3. Desiere, Sam, 2016. "The inverse productivity size relationship: can it be explained by systematic measurement error in self-reported production?," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246971, African Association of Agricultural Economists (AAAE).
    4. Basile Boulay, 2018. "Revisiting the old debate: on the relationship between size and productivity in Tanzania," Discussion Papers 2018-02, University of Nottingham, CREDIT.
    5. Desiere, Sam & Jolliffe, Dean, 2018. "Land productivity and plot size: Is measurement error driving the inverse relationship?," Journal of Development Economics, Elsevier, vol. 130(C), pages 84-98.
    6. Kilic, Talip & Zezza, Alberto & Carletto, Calogero & Savastano, Sara, 2017. "Missing(ness) in Action: Selectivity Bias in GPS-Based Land Area Measurements," World Development, Elsevier, vol. 92(C), pages 143-157.
    7. GOUNDAN, Anatole & MAGNE DOMGHO, Léa Vicky, 2016. "Land Area Measurement bias: Evidence from West African countries," MPRA Paper 75476, University Library of Munich, Germany.
    8. Luo, Yufeng & Chen, Feifei & Qiu, Huanguang, 2018. "Plot size and maize production efficiency in China: agricultural involution and mechanization," 2018 Annual Meeting, August 5-7, Washington, D.C. 274364, Agricultural and Applied Economics Association.
    9. Wineman, Ayala & Jayne, Thomas S., 2017. "Factor Market Activity And The Inverse Farm Sizeproductivity Relationship In Tanzania," Feed the Future Innovation Lab for Food Security Policy Research Papers 265405, Michigan State University, Department of Agricultural, Food, and Resource Economics, Feed the Future Innovation Lab for Food Security (FSP).
    10. repec:eee:deveco:v:132:y:2018:i:c:p:57-74 is not listed on IDEAS
    11. Michler, Jeffrey D. & Josephson, Anna L., 2017. "To Specialize or Diversify: Agricultural Diversity and Poverty Dynamics in Ethiopia," World Development, Elsevier, vol. 89(C), pages 214-226.
    12. Dillon,Andrew S. & Gourlay,Sydney & Mcgee,Kevin Robert & Oseni,Gbemisola O., 2016. "Land measurement bias and its empirical implications : evidence from a validation exercise," Policy Research Working Paper Series 7597, The World Bank.

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