medium-scale farms for 2021, 2022, and 2023. Drops in output prices together with higher input costs more than halved farm profitability in 2022. In 2023, most output prices continued to decline, so lower input costs brought only limited respite. Price changes affect all farm sizes equally, suggesting that diversification into higher value crops that are less sensitive to transport cost remained limited.

# **4.1 Descriptive evidence**

To complement image-based data on crop cover and conflict incidence, we use data on prices of key inputs and outputs that were collected in a consistent format every year from 2021 to 2023 for the country’s main farming areas. In line with the literature that highlights the disruption caused by the loss of links to export markets through Ukraine’s major Black Sea ports (Wilson _et al._ 2024), three trends can be discerned from panel A in table 6. First, output prices for the main crops almost halved in 2022 due to higher export costs, which can be attributed to the lower capacity at Ukraine’s main ports and higher cost of alternative access points to global markets through Poland or Romania. Second, with unit transport cost increasing by 48% over pre-war levels in 2022, prices for imported fertilizers more than doubled and those for other inputs also increased markedly directly after the invasion. Prices for locally produced services or inputs, although less affected, also increased markedly. Third, while most input prices returned to within 10% of their prewar levels by 2023, output prices for all crops except soybean declined further from their 2022 levels.

Although micro-data on agricultural profitability as used, for example, by Deininger et al. (2018), would be ideal for making inferences on the effects of the conflict, the State Statistics Service of Ukraine (SSSU) stopped making such data available in 2019. To assess the impact of the conflict on changes in farm profitability, we thus resorted to conducting our own survey of small and medium-scale farmers in areas not affected by the conflict. Annex A explains the sample, for which we used Ukraine’s State Agrarian Register (SAR) as a sample frame, in more detail and compares it to the sample used by the SSSU. The data were collected by phone in two waves in winter 2022/23 (collecting data for the 2021 and 2022 agricultural seasons), and in winter 2023/24 (collecting data for the 2023 agricultural season). This provides a three-year panel with data from before and during the war for the same farms.

As might be expected in an environment with an active conflict, the levels of nonresponse and attrition were high: of 2,500 respondents in the 2022 round, only about 1,200 could be traced and provided answers in 2023. Further, as the SAR was a main vehicle for disbursing emergency assistance to registered farmers in cash or in kind, receipt of support or the expectation of future support seems to have increased the likelihood of farmers’ response. Appendix table A7 suggests that those who benefited from the producer support grant (PSG) were10% more likely to respond, and application to another program increased the likelihood of response by 17%. Interpretation of the farm-level figures needs to account for the limitations of the sample and the potential selection effects they imply.

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