Recall length and measurement error in agricultural surveys

Philip Randolph Wollburg, World Bank Development Data Group

This paper assesses the relationship between the length of the recall period and nonrandom error in agricultural survey data. Using data from the Living Standards Measurement Study – Integrated Survey on Agriculture in Malawi and Tanzania, we show that key input and output variables are systematically related to the length of the recall period, indicating the presence of nonrandom measurement error. With longer recall periods, farmers report higher quantities of harvest, labor and fertilizer inputs. At the same time, farmers list fewer plots as the recall period increases. We find evidence for the same kind of error in common measures of agricultural productivity. We argue that it is plausible that farmers over-estimate plotlevel outcomes – harvest, labor and fertilizer inputs – while it is also plausible that they forget some of their more marginal plots, as their memory decays due to longer recall periods. The size of the recall effect typically varies between 2 and 5 percent per additional month of recall length, making its impact on the reliability of key agricultural indicators economically significant. Policy and investment priorities based on these indicators, for example as part of the SDG and CAADP frameworks, risk being ineffective or misguided. The results show that improving data quality remains an important concern and lend support to ongoing efforts to mainstream more objective ‘gold standard’ measures of key variables in agricultural surveys. Moreover, survey design can reduce the risk of recall error through shorter recall periods and decreased variation in recall length within the sample.

About the speaker

Philip Wollburg is a Survey Specialist at the World Bank Development Data Group, based in Rome, Italy. His research interests are in the areas of poverty, agriculture, and migration, as well as methodological and technological innovation in measurement and data collection of key development indicators. While at the World Bank’s Poverty & Equity Global Practice, he worked on implementing a nationally-representative household survey in Somalia. Prior to joining the World Bank, he worked with the Food and Agriculture Organization of the UN (FAO) and led a project aimed at delivering innovative renewable energy solutions to smallholder agricultural and fisheries communities in East Africa. He holds a MSc degree in development economics from the University of Oxford.

Venue: 1.23/1.24

Date: 11 November 2019

Time: 15:00 - 16:00