Correlated non-classical measurement errors, ‘Second best’ policy inference, and the inverse size-productivity relationship in agriculture
By Christopher B. Barrett, K. Abay, G. Abate, Tanguy Bernard. Journal of Development Economics, 2019
116 citations recorded by the source corpus.
We show analytically and empirically that non-classical measurement errors in the two key variables in a hypothesized relationship can bias the estimated relationship between them in any direction. Furthermore, if the errors are correlated, correcting for either one alone can aggravate bias in the parameter estimate of interest relative to ignoring mismeasurement in both variables, a second best result with implications for a broad class of economic phenomena of policy interest. We illustrate these results empirically by demonstrating the implications of mismeasured agricultural output and plot size for the long-debated (inverse) relationship between size and productivity. Our data from Ethiopia show large discrepancies between farmer self-reported and directly measured values of crop output and plot size; these errors are strongly, positively correlated with one another. In these data, correlated non-classical measurement errors generate a strong but largely spurious estimated inverse size-productivity relationship. We demonstrate empirically our analytical result that correcting for just one measurement problem may aggravate the bias in the parameter estimate of interest. Acknowledgement : This paper benefited from comments by Marc Bellemare, Leah Bevis, Chris Boone, Brian Dillon, John Gibson, Kalle Hirvonen and seminar participants at the African Development Bank. Any remaining errors are the authors sole responsibility.
Subfields: General Agricultural and Biological Sciences, Soil Science
View Paper: https://www.semanticscholar.org/paper/7ca18ef3a57a5b179f2673c0453eb93dc3f2cbda
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In Soil Science
Citations in the corpus
- Eyes in the Sky, Boots on the Ground: Assessing Satellite‐ and Ground‐Based Approaches to Crop Yield Measurement and Analysis (2018, unknown): “…data, and the emerging evidence on systematic measurement errors in farmerreported crop production estimates that may have a bearing on fundamental relationships in smallholder production systems (Gourlay, Kilic, and Lobell 2017; Desiere and Jolliffe 2018; Abay et al. 2019; Wossen et al. 2019).”
- NIGHT LIGHTS IN ECONOMICS: SOURCES AND USES1 (2020, background): “Thus, the failure of 22 There is also a literature that relies on annual changes in DMSP night lights as RHS variables, for detecting manipulation of reported GDP growth rates, which are the variables used on the left hand side (e.g. Chan et al, 2019; Martinez, 2018).”
- Measurement Error Mechanisms Matter: Agricultural Intensification with Farmer Misperceptions and Misreporting (2019, unknown): “The implications of such correlated measurement error are examined by Abay et al. (2019).”