From Guesstimates to GPStimates : Land Area Measurement and Implications for Agricultural Analysis
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...
| Main Authors: | , , |
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| Format: | Policy Research Working Paper |
| Language: | English en_US |
| Published: |
World Bank, Washington, DC
2013
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/2013/07/18055670/guesstimates-gpstimates-land-area-measurement-implications-agricultural-analysis http://hdl.handle.net/10986/15910 |
| Summary: | 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. |
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