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Beyond the "Inverse Relationship": Area Mismeasurement Affects Actual Productivity, Not Just How We Understand It

William Burke (), Stephen Morgan, Thelma Namonje-Kapembwa, Milu Muyanga and Nicole M. Mason

No 305180, 2020 Annual Meeting, July 26-28, Kansas City, Missouri from Agricultural and Applied Economics Association

Abstract: Although measurement error in agricultural field area and productivity data for developing countries is widely acknowledged, there is still a shortage of evidence on what the errors imply for researchers, and even less evidence on what the implications may be for farmers. In this study we investigate field size measurement errors on Zambian maize fields to examine the nature of these errors and the implications they have for: 1) our ability to understand productivity, 2) actual productivity, and 3) our broader understanding of total land use. Using a nationally representative dataset on Zambian smallholder maize plots, we compare self-reported (SR) and global positioning system (GPS) measures of land area on a farm’s largest maize plot to assess how measurement error might affect productivity estimates and farmer input use. Consistent with other studies, we find strong evidence that the land area of relatively smaller fields is overstated, and relatively larger fields is understated. However, correcting for this measurement error using GPS measurements appears to strengthen the evidence of an inverse relationship between field size and productivity. Additionally, we find strong evidence to suggest farmers themselves believe the area figures they report to enumerators and that their input use is more closely aligned with the reported field sizes than actual field sizes. Based on these results and insights from semi-structured interviews with farmers and extension agents, we argue that measurement error may affect real productivity in addition to productivity estimates. Strengthening extension efforts to improve farmer understanding of land area measurements may be an important and affordable way to improve productivity. Moreover, improving the accuracy of datacollection for area seems feasible and will improve researchers’ understanding of productivity.

Keywords: Food Security and Poverty; International Development (search for similar items in EconPapers)
Pages: 39
Date: 2020-08
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