From guesstimates to GPStimates : land area measurement and implications for agricultural analysis

By C. Carletto, S. Gourlay, P. Winters. 2013

167 citations recorded by the source corpus.

Land area measurement is a fundamental component of agricultural statistics and analysis. Yet, commonly employed self-reported land area measures used in most analysis are not only potentially measured with error, but these errors may be correlated with agricultural outcomes. Measures employing Global Positioning Systems, on the other hand, while not perfect especially on smaller plots, are likely to provide more precise measures and errors less correlated with agricultural outcomes. This paper uses data from four African countries to compare the use of self-reported and Global Positioning Systems land measures to (1) examine the differences between the measures, (2) identify the sources of the differences, and (3) assess the implications of the different measures on agricultural analysis focusing on the inverse productivity relationship. The results indicate that self-reported land areas systematically differ from Global Positioning Systems land measures and that this difference leads to potentially biased estimates of the relationship between land and productivity.

Subfields: General Agricultural and Biological Sciences, Global and Planetary Change, Soil Science

View Paper: https://www.semanticscholar.org/paper/aead5209b486ec66ff88a7f1509b004bfa4227e7

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In General Agricultural and Biological Sciences

In Global and Planetary Change

In Soil Science

Citations in the corpus

Land productivity and plot size : is measurement error driving the inverse relationship ? (2017, background): “For instance, Carletto et al. (2015) report that farmers overestimate plot size by 103 percent relative to GPS measurement on plots smaller than 0.5 acres (2,000 m²) and underestimate it by 33 percent on plots larger than 5 acres (20,000 m²).”
Measurement Error Mechanisms Matter: Agricultural Intensification with Farmer Misperceptions and Misreporting (2019, unknown): “Several previous studies have found measurement error in self-reported plot size is correlated with true plot area (Carletto et al. 2013; Carletto et al. 2015; Gourlay et al. 2017; Bevis and Barrett, 2019; Abay et al., 2019).”
Revisiting the Farm Size‐Productivity Relationship Based on a Relatively Wide Range of Farm Sizes: Evidence from Kenya (2019, unknown): “Carletto, Gourlay, and Winters (2015) compared self-reported landholding sizes to Global Positioning Systems (GPS) plot measurement using Living Standards Measurement Study (LSMS) data from the World Bank for four African countries and found that farmers tend to overestimate and underestimate…”
Correlated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture (2019, methodology): “…(2013) find that inaccuracies in land area measurement lead to underestimation of the inverse relationship between plot size and productivity while Carletto et al. (2015) show the opposite. correcting for mismeasurement of just one variable can aggravate rather than attenuate bias in the SPR…”
Heterogeneity, Measurement Error, and Misallocation: Evidence from African Agriculture (2019, background): “This pattern of a strong negative relationship between crop yields and plot size within a farmhas been observed inmultiple data sets fromAfrica (Carletto, Gourlay, and Winters 2015; Bevis and Barrett 2017; Carletto et al. 2017).”