asymmetric and incomplete updating of existing beliefs among smallholders in Africa (Lybbert et al., 2007) and households and firms (Kohlhas and Walther, 2021).

# **5. Spillover Effects on Farmer Self-Reporting on Non-Land Inputs**

If farmers exhibit misperceptions of plot sizes that vary little over time and adjust only incompletely to corrective information, one might then likewise expect inattention to inputs that vary more over time, and are often worth less, such as fertilizer applications or agricultural labor time allocation. One economical way for people to conserve on attention to details would be to hold a single belief about a central value – e.g., plot size – and then estimate other variables' values based on a simple, stable prediction rule that takes the single belief as its argument – e.g., a seeding or fertilizer application density or a rate of labor use per unit land cultivated – consistent with the notion of optimal prediction error (Hyslop and Imbens, 2001).<sup>19</sup> For example, fertilizer applications are usually recommended per unit of land, farmers may easily use that information to predict their applications.<sup>20</sup> Our experimental design allows us to test whether the randomized provision of plot size information indeed propagates to farmers' self-reports of other input application rates – that could not have actually changed – thereby signaling information spillovers because the new information on one production input (land) affects respondents' reporting of other production inputs (e.g., fertilizer, labor).<sup>21</sup> This would also signal that NCME in such variables are likewise correlated.

We focus on farmers' reported use of labor and fertilizer prior to and during planting, information that was collected from treatment group farmers immediately after they received the corrective information of the GPS plot size measure. Behavioral adjustments could cause real adjustment in later season input application rates in response to corrective plot size information, hence our focus on input application that would have all occurred prior to the pre-treatment survey data collection. We focus on labor and fertilizer because they are the most widely used non-land

> 19 Other types of measurement error models may also generate similar spillover effects (e.g., <mark>Schennacha, 2020).</mark> 20 Similarly, measuring labor application in a specific plot can be difficult because of the (staggered) nature of farming activities. In this case, farmers may use the size of the plot to get a sense of the labor needed for some of these farm activities (e.g., land preparation, weeding and harvest).

> 21 An alternative mechanism could be that information that reveals to a respondent that he mis-estimated plot size may cause him to adjust all self-reports, regardless of whether they relate to plot size or not. Because the plot size information experiment and subsequent questions about input application on the plot were the last module of the postplanting questionnaire, we unfortunately have no variables clearly unrelated to plot size on which to test this alternative hypothesis about the mechanism behind the information spillover effect.

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