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

Stein T. Holden (), Clifton Makate () and Sarah Tione ()
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Stein T. Holden: Centre for Land Tenure Studies, Norwegian University of Life Sciences, Postal: Centre for Land Tenure Studies, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway
Clifton Makate: Centre for Land Tenure Studies, Norwegian University of Life Sciences, Postal: Centre for Land Tenure Studies, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway
Sarah Tione: Centre for Land Tenure Studies, Norwegian University of Life Sciences, Postal: Centre for Land Tenure Studies, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Aas, Norway

No 4/25, CLTS Working Papers from Norwegian University of Life Sciences, Centre for Land Tenure Studies

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. 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 were mostly measured with GPSs and/or rope and compass. While this gives reliable measures of reported holdings, we detect substantial under-reporting of parcels over time within households that largely have been overlooked in previous studies. The problem causes an unrecognized bias in agricultural statistics. 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. We estimate models with alternative estimators for the ownership holding share of maximum within-household holding to examine factors associated with variation in reported farm sizes. 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 real farm size, 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 of 12-41% 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 relevant policy implications.

Keywords: Farm size measurement; plot attrition; measurement error; LSMS-ISA; Ethiopia; Malawi (search for similar items in EconPapers)
JEL-codes: C81 C83 Q12 Q15 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2025-06-18
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:nlsclt:2025_004

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