From Guesstimates to GPStimates: Land Area Measurement and Implications for Agricultural Analysis

Abstract

Development goals and poverty-reduction policies are often focused on raising agricultural productivity and dependent on farm household level data. Historically, household surveys commonly employed self-reported land area measurements for cost-effectiveness and convenience. However, as we illustrate here, these self-reported estimates may measure land with systematic error resulting in sizable biases. This has led to the increased use of Global Positioning Systems (GPS) and other modern technologies to measure land size. In this article, we compare self-reported (SR) and GPS land measurement to assess the differences between the measures, to identify the sources of differences, and to determine the implications of the different measures on agricultural analysis. The results from the analysis of data from four African countries indicate that SR land areas systematically differ from GPS land measures and that this difference leads to biased estimates of the relationship between land and productivity and consistently low estimates of land inequality. Through the evidence and analysis presented here, we conclude that the more systematic use of GPS-measured land area will result in improved agricultural statistics and more accurate analysis of agricultural relationships, which will better inform future policy.