# **3.6 Correlation of crop and livestock production with urban expansion**

For each SSP scenario, we estimate grid level regressions to estimate the correlation between crop and livestock production at baseline in 2015 with projected urban expansion (both in 2040 and 2100). These correlations indicate, for each of the SSP scenarios, to what extent grids that are more likely to become more urban in the future are those that have higher (or lower) crop and livestock production today. It sheds light on whether urban expansion will occur into higher production grids, but not on whether urban expansion occurs in more grids.

_Table 4. Grid level regressions of crop production on urban expansion rates for five SSP scenarios_

|_Outcome:_|(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|Crop production(2010, mt)|SSP 1|SSP 2|SSP 3|SSP 4|SSP 5|
|_Panel A: Urban expansion to 2040_||||||
|Urban expansion rate in 2040|67,040.29***|67,547.62***|98,514.26***|70,278.82***|50,550.85***|
||(998.5)|(1055.5)|(1357.25)|(1053.61)|(859.41)|
|Observations|832,827|832,827|832,827|832,827|832,827|
|R squared|0.0054|0.0049|0.0063|0.0053|0.0041|
|Mean crop production(2010,mt)|9,243.5|9,243.5|9,243.5|9,243.5|9,243.5|
||(6)|(7)|(8)|(9)|(10)|
||SSP 1|SSP 2|SSP 3|SSP 4|SSP 5|
|_Panel B: Urban expansion to 2100_||||||
|Urban expansion rate in 2100|32,773.24***|33,660.66***|56,730.6***|37,474.94 ***|16,547.64***|
||(582.03)|(567.5)|(648.1)|(564.4)|(368.67)|
|Observations|832,827|832,827|832,827|832,827|832,827|
|R squared|0.0038|0.0042|0.0091|0.0053|0.0024|
|Mean crop production (2010, mt)|9,243.5|9,243.5|9,243.5|9,243.5|9,243.5|

Robust SE in parentheses. *** p<0.01, ** p<0.05, * p<0.1. Grid-level OLS estimation, where one grid has a spatial resolution of 1/12 degree - about 9 to 10 sq km. Urban expansion rate is the percentage of newly urban areas in a given grid cell for a given SSP scenario (ranging from 0 to 1). Crop production for each grid cell is defined as the yield multiplied by harvested area in metric tons. We include seven food group: cereals, fruits, vegetables, oils, pulses, roots, and sugar. We exclude non-food groups from the database (Cotton, other fibre crops, arabica coffee, robusta coffee, cocoa, tea, tobacco, rest of crops). Here, the urbanization rate is defined as the percentage of urban population to total population, and ranges from the value of 0 to 1. The urban expansion projection data (Chen et al. 2020) are calculated using panel data regression based on historical population, urbanization rate, and gross domestic product (GDP) data.

Table 4 presents results for crop production for both 2040 (Panel A) and 2100 (Panel B). First, we find that across all SSP scenarios and in both 2040 and 2100, grids that are expected to have higher urban expansion rates are grids which have higher levels of crop production today. This indicates that in the future, cities are likely to grow into areas with more crop production, regardless of SSP scenario. Second, in both 2040 and 2100, the positive correlation between projected urban expansion and current crop production is highest under SSP3 and lowest under SSP5. Third, the positive correlation between projected urban expansion and current crop production is large in both 2040 and 2100, but the magnitude dampens over time. This means that the cumulative 22