10 model correlates district-level yields from government statistics with a satellite-derived vegetation index (green chlorophyll index) known to be sensitive to rice yields for pixels identified as ricegrowing areas. A random forest-based machine learning model is added to incorporate additional environmental variables known to affect rice yields, resulting in pixel-level rice yield estimates across two decades (2000-2022).<sup>23</sup> For tea, district-level yield data is regressed on a district-level vegetation index derived from satellite data for pixels deemed to be tea plantations.<sup>24</sup>

**Fertilizer subsidies** . Crop-level fertilizer subsidy rates are defined as the “nominal rate of protection at farm gate”, which is computed by comparing the actual (farm-gate) fertilizer price to the price that would be expected given international fertilizer prices and the cost of bringing fertilizer from port to farm. The fertilizer subsidy rate is 81% for rice and 45%-54% for four other crops of interest (potato, maize, tea, and onions).<sup>25</sup>

**Potential agricultural yields** . Our use of FAO-GAEZ data for crop-district-level potential attainable yields follows the literature on agriculture and trade (Bustos et al., 2016; Costinot et al., 2016; Farrokhi and Pellegrina, 2023; Sotelo, 2020).

**Wages and household characteristics** . Three types of information in our survey data are particularly valuable: (i) on estate workers who live and work in Sri Lanka’s tea plantations, for whom changing jobs is nearly impossible in the short run as their housing is tied to the tea estate where they work (Chandrabose, 2015); (ii) on the fraction of income households spend on food; and (iii) on income earned “by chance”, including lottery gains and disaster/relief payments.

**Summary Statistics.** Fertilizer and non-fertilizer products whose imports were banned accounted for 15%-19% of total imports in 2017-2019 (Appendix Table A4). This share declined to 12% in 2020 and 10% in 2021, suggesting the bans were at least partially effective. Summary statistics for some key variables of interest, shown in Appendix A.L, provide evidence of the ban’s effects: the average value of fertilizer imports per firm-year plummeted from 2 million USD to only 491 thousand USD from the pre-ban to the post-ban period, while the average value of agricultural exports per firm-year fell from 1.62 million USD to 1.53 million USD. Remotely sensed crop yields decrease substantially from the pre-ban (2021) to the post-ban (2022) period: average rice yields across divisional secretariats (DSs) fall from more than 4,000 kg/ha to less than 3,000 kg/ha, while average tea yields fall from 1,644 kg/ha to 1,404 kg/ha.

and water management from space and distinguishes it from other land use types using spectral (color) and temporal information included in the satellite signal. Because water and vegetation indexes are more visible for rice than for other crops, crop type mapping and yield are better predicted for rice than for other crops using remote sensing tools (Dong et al., 2016).

> 23These remote sensing estimates aggregated to the DS level are highly consistent with government-reported measures of rice area (from survey-based crop-cutting experiments) and rice yields (from production statistics).

> 24Since tea is a multiyear permanent crop, planted areas do not change annually. Thus, we fix tea-growing areas to the 2021 tea map.

> 25High fertilizer subsidy rates, in the 40-50% range, are also reported in the World Food Programme’s analyses of food security in Sri Lanka (FAO and WFP, 2022, 2023).