Land Measurement Bias and Its Empirical Implications

Land Measurement Bias and Its Empirical Implications

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.

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Bibliographic Details
Main Authors: Dillon, Andrew, Gourlay, Sydney, Mcgee, Kevin, Oseni, Gbemisola
Format: Working Paper biblioteca
Language:English
en_US
Published: World Bank, Washington, DC 2016-03
Subjects:METHODS, TECHNOLOGY, TRANSACTION, RELIABILITY, EQUIPMENT, CALIBRATION, INTERVIEWS, PRODUCTION, TIME, RESULTS, RESEARCH WORKING PAPERS, VALIDITY, FAMILY, AGE, AGRICULTURAL PRODUCTION, GPS, DATA COLLECTION, INFORMATION, EXAMINATIONS, STANDARD MEASUREMENT, SCALE OF PRODUCTION, AGRICULTURAL INNOVATION, MONITORING, RESEARCHERS, AGRICULTURE, EFFECTS, MEASUREMENT ERRORS, NATURAL RESOURCES MANAGEMENT, SAMPLES, AGRICULTURAL ECONOMICS, SIZE, MEASUREMENT, MEASUREMENTS, PRICE, HUMAN ERROR, SURVEYS, ECONOMICS, MEASURES, MANAGEMENT, REGRESSION ANALYSIS, OPEN ACCESS, SATELLITE, RESULT, WEIGHT, ECONOMIC DEVELOPMENT, KNOWLEDGE, EMPIRICAL ANALYSIS, LAND, STANDARD UNITS, ESTIMATING, SPACE, EDUCATION, MEASURING, METHODOLOGIES, METERS, TESTS, SAMPLING, EXPERIMENTS, LENGTH, GLOBAL POSITIONING SYSTEM, INNOVATION, SURVEY DESIGN, SURVEY DATA, PRODUCTIVITY, ECONOMETRICS, PRECISION, OBSERVATION, ESTIMATES, MAGNITUDE, INDICATORS, RESEARCH, AGRICULTURAL, UNITS, METHODOLOGY, STANDARDS, TECHNOLOGIES, FARMERS, NATURAL RESOURCES, WEIGHTS, CROPS, TESTING, ACCURACY,
Online Access:http://documents.worldbank.org/curated/en/2016/03/26067878/land-measurement-bias-empirical-implications-evidence-validation-exercise
https://hdl.handle.net/10986/24141
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Summary: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.

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