simulation to capture the potential economic gains that can be achieved by operating within a hypothetical, high input use scenario, as depicted in the geospatial data on potential agricultural yields that are disseminated by the Global Agro-Ecological Zone (GAEZ) initiative. The geospatial, modeled GAEZ data on potential crop yields factor in crop growth cycles, climate factors such as rainfall and temperature, soil moisture levels, geospatially-derived soil properties, among other factors. For each MAPS plot, the GAEZ potential maize yield under the high-input scenario was extracted based on the GPS coordinates of the plot centroid.<sup>21</sup> If the GAEZ highinput potential (as estimated for S1 plots) yields were to be attained on the sampled plots, the economic gains would increase dramatically, with households producing up to USD 880 per season on average. In this scenario, those in the richest tercile would enjoy greater gains over their current production levels than those in the poorest tercile. Female-headed households, on average, if operating at GAEZ high-input potential and irrespective of factors other than land quality and climatic covariates, still suffer from lower gains than male-headed households, with potential gains capped at USD 729 per agricultural season compared to USD 918.

# **6. Conclusions**

In this paper we estimate a multi-dimensional measure of maize-specific soil suitability based on existing standards, across a sample of approximately 900 households, spanning 4 districts in Eastern Uganda, the leading maize-producing region in the country. This is made possible by collecting and laboratory-testing plot-level soil samples following international best practices in the context of a methodological household survey experiment. In addition to the plot-level soil data, analysis of maize-specific soil suitability is replicated using publicly available geospatial soil data. This research provides a greater understanding of both the heterogeneous productivity constraints and the potential maize-based production and income gains, across crop-specific soil suitability profiles.

Classifying the sampled plots into three suitability classes, namely highly-suitable, moderatelysuitable, and marginally-suitable, and leveraging plot-level crop-cutting-based maize yields allows for comparison of the distributions of observed maize yields by suitability class. We then extend this analysis by estimating stochastic frontier models of maize yield separately for each suitability class, using both the MAPS-based and AFSIS-based suitability classifications, to understand differences in (i) returns to factors of production, (ii) technical efficiency, and (iii) potential yield measures. Compared to observed yields, the potential yield estimation provides a unique overview of maximum yield gains that can be achieved in each suitability class by increasing the efficiency with which the current set of inputs into agricultural production are utilized. Pairing the household

> 21 Note that the GAEZ data is spatially derived, and therefore does not possess the same level of granularity as the MAPS-based data. For example, the GAEZ potential yields under the high input regime are not statistically different across any of the MAPS-based soil suitability classifications.

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