or uncultivated), distance to key infrastructure, and soil quality; i is a vector of transaction characteristics; is a region fixed effect and i is an error term. ZZ ii Per hectare land prices are and expressed in January 2024 USD by using the monthly Consumer Price Index aa ee (CPI) to adjust for inflation and then convert to USD at the official exchange rate.<sup>19</sup> We eliminate duplicates, defined as the same parcel being transacted multiple times on the same date.<sup>20</sup> Extreme outliers are removed by trimming at the 1<sup>st</sup> and 99<sup>th</sup> percentiles.<sup>21</sup> Parcel characteristics include the Euclidean distance from parcels’ centroid to the nearest road, railway access point, port, grain elevator, or city from Open Street Map (OSM) data provides data on infrastructure access.<sup>22</sup> We also compute the share of parcel area covered by built area, crops, forest or grassland using crop classification data for the year prior to the transaction.<sup>23</sup> Finally, as we did not have access to nation-wide data on the soil quality index discussed earlier, we use publicly available SoilGrids data (Poggio _et al._ 2021) to obtain measures of soil quality, in particular pH, soil density, nitrogen and organic matter in the 0-60 cm horizon at the centroid of each parcel.<sup>24</sup> The vector i includes variables to capture transaction timing and adherence to legal requirements, and other characteristics. Specifically, we include (i) a war dummy that takes the value of one if the transaction ZZ happened after February 2022 when war conditions are likely to have significantly altered agricultural land supply and demand; (ii) the number of buyers if a parcel was acquired in joint ownership; (iii) a variable capturing the order of transactions (from 1 to 5) in case a parcel has been transacted multiple times; and (iv) dummy variables for prices below NMV and for missing NMV to capture non-compliance with legal provision prohibiting transactions below the NMV.

Use of fixed effects at the level of 355,663 cadastral blocks, delineated to contain homogenous patterns of land use, is the most appropriate way to control for unobserved heterogeneity in local conditions. However, as agricultural land sales started only in 2021, there may be no or only a limited number of sales transactions at this level, especially in agriculturally marginal areas. Appendix figures A4, A5, A6, A7, A8, and A9, illustrate this graphically by showing that, there were no or only few land sales transactions for many cadastral blocks, zones, villages (KOATUU), communities ( _hromadas_ ), or districts ( _rayons_ ). If there are only few non-representative observations, estimation of fixed effects at any given level may result in biased and misleading prediction of land values.

> 19 Both the CPI and UAH to USD exchange rates are taken from the data of the National Bank of Ukraine <u>https://bank.gov.ua/ua/statistic.</u> 20 As such repetitions are due to a parcel being purchased by multiple owners and the value of each owner’s share is recorded separately, we aggregate the land value over every owner, while keeping other parcel characteristics constant. By contrast, cases where the same parcel is sold multiple times during the period under concern are retained as different observations.

> 21 Extreme values due to very small plot size that result in very high per-ha prices are likely due to data entry error and removed via trimming.

> 22 OSM data was downloaded from <u>https://www.openstreetmap.org. Equivalent and possibly richer data on access to infrastructure could in principle</u> be obtained from official topographic maps that were not accessible to us.

> 23 Downloaded from https://ukraine-cropmaps.com.

> 24 Downloaded from <u>https://files.isric.org/soilgrids/latest/data. Systematically comparing</u> _bonitet_ to these publicly available data would be one area for improving the data base used for estimation.

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