To study cropland dynamics, we also mobilize a set of biophysical variables at the same pixel level. As a measure of climate stress, we use the annual number of drought months reconstructed from the Palmer Drought Severity Index (PDSI) developed by TerraClimate (https://www.climatologylab.org/terraclimate.html), where drought months are defined as periods for which the index was below -3. We calculated the distance to rivers and coast using the shapefile from Natural Earth (https://www.naturalearthdata.com/).<sup>1</sup> We also calculated the distance to the nearest city using the UrbanPop dataset (Blankespoor et al., 2017). Land suitability for cultivation was obtained from the FAO Global Agro-Ecological Zones (GAEZ) v4 product (https://gaez.fao.org/). We constructed an aggregate index comprised between 0 and 100 that measures how suitable the pixel is for rainfed cultivation of an umbrella crop of seven major crops under a high input scenario (i.e., taking the maximum individual suitability index over these seven crops).<sup>2</sup> We also use measures of institutional quality. This includes measures of land governance from two different datasets. The first is the Quality of Land Administration index (denoted QLA hereafter) from the World Bank Doing Business 2020 database.<sup>3</sup> QLA is a composite of five subsidiary indexes measuring the reliability of land administration infrastructure, the transparency of information, the geographic coverage of registries, the legal framework for land dispute resolution, and whether men and women have equal access to property rights. Alternatively, we use the Institutional Profile Database (CEPII, Agence Française Développement, and Ministère de l’Économie et des Finances: <u>http://www.cepii.fr/institutions/en/ipd.asp) for 2012. The database provides several country-level</u> measures of land governance, which we summarize as an index measuring “land tenure insecurity of rural populations”.<sup>4</sup> Finally, we use the 2017 overall indicator in the Enabling Business of Agriculture dataset (https://eba.worldbank.org/en/eba), which captures the ease for farmers to operate their businesses. We use the overall score that aggregates the following sub-indicators supplying seed, registering fertilizer, securing water, registering machinery, sustaining livestock, protecting plant health, trading food, and accessing finance.

# **Section 2.  The global distribution of cropland and its dynamics**

The MODIS product allows us to assess patterns of geographic cropland distribution and its evolution over time. Table 1 below provides a breakdown of global cropland by region (using the World Bank definition) at the beginning and the end of our study period, showing that 65 percent of global cropland is located in the Europe and Central Asia region and Asia. North America has over 15 percent of the stock of cropland.

> 1 The data contains 1,455 global lakes and rivers which total 870,000 km2

> 2 The seven crops are cassava, maize, oil palm, sorghum, soybean, sugarcane, and wheat.

> 3 World Bank, Doing Business 2004–2020 (database), https://archive.doingbusiness.org/en/doingbusiness. Doing Business was discontinued by the World Bank in September 2021 due to certain irregularities which do not affect the data used in this paper.

> 4 The index is given by the first axis in a principal component analysis summarizing the information from the land governance variables in the Institutional Profile Database: b6030 “diversity of land tenure regimes”, b6050 “recognition of land tenure regimes”, b6070 “existence of formalization processes”, and b6071 “existence of policies favorable to vulnerable groups”.  The axis correlates positively with b6030 and b6050 and negatively with b6070 and b6071, hence the interpretation in terms of land tenure insecurity (results available upon request).

4