Soy is the most important agricultural commodity in Argentina, with relevance in public revenues and international reserves accumulation. However, a proper impact evaluation of future losses in the context of climate change has not yet been developed. Therefore, the aim of this paper is to provide future estimates of impact evaluation for macroeconomic adaptation policies. By means of a multiple partial regression, the relation between total country soybean yields and different combinations of 28 territorial weather stations was estimated for the period 2001–2021. With the optimal model, the output was projected using future rainfall and temperature data from 150 climate models from 4 different climate change scenarios from the Copernicus database during 2022–2042. Results show a strong statistical relationship between rainfall levels and maximum temperature and total soybean yields, explaining on average 91.2% of the yield variation. The future projections showed that the general average of the four climate change scenarios projected future output at 3.8% higher than the current levels, with 30% of projections with lower and 70% with higher output values than the current production. Variability analysis showed an increase in the frequency and intensity of extreme negative events and higher aggregate than in the past: relative loss is on average 3.6% of production (USD million $13,000) compared to 2.3% of production in the historical data (USD million $7,492). The main application is the estimation of macro-fiscal impact for long-term budgetary and fiscal planning, with a parsimonious approach and open-access data that allows permanent actualization.
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