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Measurement Error and Farm Size: Do Nationally Representative Surveys Provide Reliable Estimates? 

Author

Listed:
  • Holden, Stein T.

    (Centre for Land Tenure Studies, Norwegian University of Life Sciences)

  • Makate, Clifton

    (Centre for Land Tenure Studies, Norwegian University of Life Sciences)

  • Tione, Sarah

    (Centre for Land Tenure Studies, Norwegian University of Life Sciences)

Abstract

We assess the reliability of measured farm sizes (ownership holdings) in the Living Standard Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) in Ethiopia and Malawi based on three survey rounds (2012, 2014, 2016) in Ethiopia and four rounds (2010, 2013, 2016, 2019) in Malawi. By using the balanced panel of households that participated in all the rounds, we utilized the within-household variation in reported and measured ownership holdings that, to a large extent, were measured with GPSs and/or with rope and compass. While this gives reliable measures of reported holdings, we detect substantial under-reporting of parcels over time within households. We find that the estimated farm sizes within survey rounds are substantially downward biased due to systematic and stochastic under-reporting of parcels. Such biases are substantial in the data from both countries, in all survey rounds, and in all regions of each country. Based on the analyses, we propose that the maximum within-household reported farm sizes over several survey rounds provide a more reliable proxy for the actual farm size distributions, as these maximum sizes are less likely to be biased due to parcel attrition. The ignorance of this non-classical measurement error is associated with a downward bias in the range of 20-30% in average and median farm sizes and an upward bias in the Gini-coefficients for farm size distributions. We propose ideas for follow-up research and improvements in collecting these data types and draw some policy implications.

Suggested Citation

  • Holden, Stein T. & Makate, Clifton & Tione, Sarah, 2023. "Measurement Error and Farm Size: Do Nationally Representative Surveys Provide Reliable Estimates? ," CLTS Working Papers 7/23, Norwegian University of Life Sciences, Centre for Land Tenure Studies.
  • Handle: RePEc:hhs:nlsclt:2023_007
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    References listed on IDEAS

    as
    1. Abay, Kibrom A. & Abate, Gashaw T. & Barrett, Christopher B. & Bernard, Tanguy, 2019. "Correlated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture," Journal of Development Economics, Elsevier, vol. 139(C), pages 171-184.
    2. Carletto, Calogero & Savastano, Sara & Zezza, Alberto, 2013. "Fact or artifact: The impact of measurement errors on the farm size–productivity relationship," Journal of Development Economics, Elsevier, vol. 103(C), pages 254-261.
    3. Holden, Stein T. & Tilahun, Mesfin, 2020. "Farm size and gender distribution of land: Evidence from Ethiopian land registry data," World Development, Elsevier, vol. 130(C).
    4. Calogero Carletto, 2021. "Better data, higher impact: improving agricultural data systems for societal change [Correlated non-classical measurement errors, ‘second best’ policy inference, and the inverse size-productivity r," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 48(4), pages 719-740.
    5. T. S. Jayne & Milu Muyanga & Ayala Wineman & Hosaena Ghebru & Caleb Stevens & Mercedes Stickler & Antony Chapoto & Ward Anseeuw & Divan van der Westhuizen & David Nyange, 2019. "Are medium‐scale farms driving agricultural transformation in sub‐Saharan Africa?," Agricultural Economics, International Association of Agricultural Economists, vol. 50(S1), pages 75-95, November.
    6. 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, vol. 24(5), pages 593-628.
    7. Gourlay, Sydney & Kilic, Talip & Lobell, David B., 2019. "A new spin on an old debate: Errors in farmer-reported production and their implications for inverse scale - Productivity relationship in Uganda," Journal of Development Economics, Elsevier, vol. 141(C).
    8. William J. Burke & Stephen N. Morgan & Thelma Namonje & Milu Muyanga & Nicole M. Mason, 2019. "Area Mismeasurement Impact on Farmers' Input Choices and Productivity," Feed the Future Innovation Lab for Food Security Policy Research Briefs 303621, Michigan State University, Department of Agricultural, Food, and Resource Economics, Feed the Future Innovation Lab for Food Security (FSP).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Farm size measurement; missing data; measurement error; LSMS-ISA; Ethiopia; Malawi;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment

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