Does the distribution of government transfers affect elections? We analyze a natural experiment in the 2019 wave of the US Department of Agriculture's Market Facilitation Program (MFP). The 2019 MFP allocated \$14.5 billion via a formula combining historical production data and commodity-specific trade damages. We show how a methodological quirk resulted in arbitrary variation in these damages that propagated through the formula into excessive county-level compensation rates. We estimate the effects of this payment shock using a novel, design-based, randomization inference approach to account for complex dependencies across US counties. Adjusting for demographics and political trends, we find that counties receiving greater compensation rates, on average, have higher Republican presidential vote shares in the 2020 election. Instrumenting for actual 2019 MFP disbursements, we find an additional \$10 million in payments to a county increased that county's 2020 two-party Trump vote share by about 1.8 percentage points on average.
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Gulotty et al. (2024) studied this question.
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