Input subsidy schemes may also be responsible for unintended consequences over and above their distributional impacts. While not usually directed at a specific crop, such schemes encourage the production of crops that benefit most from the subsidized inputs. They also incentivize increased input use. This means that, as with output subsidies, regions that are suited to crops that benefit most from the subsidized inputs will gain the most from these subsidies. Second, the increased use of nitrogen fertilizer— a common target of input subsidy programs in many countries<sup>2</sup> —leads to important environmental spillovers. Exceptionally low prices encourage farmers to overuse fertilizers beyond optimal levels (Huang, Gulati and Gregory 2017; Cassou et al. 2017), which can cause nutrient imbalances in soils (Gautam 2015; Kurdi et al. 2020; Basu et al. 2022). This reduces soil fertility and increases nitrogen runoff into waterways, with potentially disastrous impacts on local ecosystems including algal blooms, hypoxia, and contaminated drinking water (James et al. 2005; Damania et al. 2019). According to the Food and Agriculture Organization of the United Nations (FAO), the most common chemical contaminant found in groundwater aquifers is nitrate from farming (Mateo-Sagasta et al. 2017).

This paper presents a new global analysis that examines these unintentional distributional and environmental impacts of output and input subsidies, with estimates of their spatial distribution in 16 and 23 countries, respectively. Despite the lack of comprehensive microdata on the spatial distribution of output and input subsidies, we are able to assess—through the creative use of crop production data and crop-level national statistics on subsidies—the broad contours of the spatial distribution of these subsidies, even if these are not precise estimates.

Next, we examine the spatial progressiveness or regressiveness of both types of subsidy within countries by overlaying our spatial subsidy maps with spatially disaggregated data on gross domestic product (GDP). We use Lorenz curves to quantify the spatial relationship between subsidies and incomes and determine the spatial progressiveness or regressiveness of subsidies. For output subsidies, we distinguish between _fiscal subsidies_ —direct government payments to farmers—and _market price support_ (MPS), where consumers largely pay for subsidies to farmers through higher prices.

Untargeted input and output subsidies will naturally be regressive. These are linked to production amounts, and since richer farmers always produce more output and use more inputs than poorer farmers, they will consequently receive a larger share of the subsidy. This analysis therefore focuses on the _relative_ spatial progressiveness of subsidies. Here, a subsidy is considered spatially progressive (spatially regressive) if poorer regions in each country receive a _relatively larger (relatively smaller)_ share of subsidies than their share of agricultural production value. For example, if the poorer half of a country produces 20 percent of total agricultural production, but receives 40 percent of the subsidy, the subsidy can be said to be spatially progressive. This is analogous to examining the progressiveness of income taxes, and testing whether richer households pay a larger share of their income in taxes than poorer households, instead of simply comparing the total amounts paid by rich versus poor households. Such examinations

> 2 Studies find that subsidy regimes in Bangladesh, India, Nepal, and Sri Lanka incentivize excessive urea application and the underapplication of phosphorus and potassium fertilizers, micronutrients, and organic inputs (Islam and Beg, 2021; Kishore et al. 2021; Gulati and Banerjee 2015; Huang et al. 2017). Cassou et al. (2017) note that in China, maintaining low and stable fertilizer prices contributes to its overuse to a “moderate” or a “significant” extent.

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