Land Measurement Bias and its Empirical Implications: Evidence from a Validation Exercise

31 Pages Posted: 20 Apr 2016

See all articles by Andrew Dillon

Andrew Dillon

Michigan State University

Sydney Gourlay

World Bank - Development Data Group

Kevin McGee

World Bank

Gbemisola Oseni

World Bank

Date Written: March 14, 2016

Abstract

This paper investigates how land size measurements vary across three common land measurement methods (farmer estimated, Global Positioning System (GPS), and compass and rope), and the effect of land size measurement error on the inverse farm size relationship and input demand functions. The analysis utilizes plot-level data from the second wave of the Nigeria General Household Survey Panel, as well as a supplementary land validation survey covering a subsample of General Household Survey Panel plots. Using this data, both GPS and self-reported farmer estimates can be compared with the gold standard compass and rope measurements on the same plots. The findings indicate that GPS measurements are more reliable than farmer estimates, where self-reported measurement bias leads to over-reporting land sizes of small plots and under-reporting of large plots. The error observed across land measurement methods is nonlinear and results in biased estimates of the inverse land size relationship. Input demand functions that rely on self-reported land measures significantly underestimate the effect of land on input utilization, including fertilizer and household labor.

Keywords: Agricultural Research, Food Security, Nutrition, Climate Change and Agriculture

Suggested Citation

Dillon, Andrew and Gourlay, Sydney and McGee, Kevin and Oseni, Gbemisola, Land Measurement Bias and its Empirical Implications: Evidence from a Validation Exercise (March 14, 2016). World Bank Policy Research Working Paper No. 7597. Available at SSRN: https://ssrn.com/abstract=2747708

Andrew Dillon (Contact Author)

Michigan State University ( email )

Agriculture Hall
East Lansing, MI 48824-1122
United States

Sydney Gourlay

World Bank - Development Data Group ( email )

1818 H Street, NW
Washington, DC 20433
United States

Kevin McGee

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

Gbemisola Oseni

World Bank ( email )

1818 H Street, NW
Washington, DC 20433
United States

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