Panagos et al. (2018) used a general equilibrium model to estimate the cost of soil erosion by water on EU GDP in 2010. According to their estimates, while erosion prevented roughly £1.3 bn worth of crop production, the GDP impact was much smaller at around £155 mn. This reflected a supply response from non-affected farms and a substitution effect towards capital and labour.
Picture by Dylan de Jonge, Unsplash
What is soil erosion?
According to the United Nations Convention to Combat Desertification (2017) Article 1, soil erosion is among the main processes contributing to land degradation globally. In terms of the specifics, it refers to the process by which water or wind gradually remove organic matter and nutrients from the top layer of the soil, which decreases the soil’s fertility. It can also have broader negative effects such as the siltation of reservoirs and sediment impact on fisheries.
How did previous studies try to estimate its economic impact?
Access to food lies at the centre of any society’s survival and, as a result, there are a number of studies which have attempted to estimate the economic cost of one of its threats: soil erosion. According to Panagos et al. (2018), other research had generally used one of the following approaches:
Cost-benefit method: which equates the cost of soil erosion to the cost of its prevention through methods such as buffer strips and residue management (eg see Kuhlman et al., 2010)
Market price method: which uses the market price of fertile soil as a proxy to the damage made by erosion (eg see Robinson et al., 2014)
Replacement cost method: which associates the loss by erosion the price of the nutrients needed to supplement it (e.g. see Martinez-Casasnovas et al., 2006)
Crop productivity loss method: which quantifies the economic loss by taking into account the crop yield loss and the price of crops (e.g. see Evans, 1996)
While the above methods may arguably provide a reasonable estimate of the cost of soil erosion on a specific farm, they can also potentially misrepresent the aggregate impact to the economy. This is because they ignore complex market dimensions such as the possibility of increasing crop production elsewhere. They also ignore negative externalities by soil erosion such as a higher risk of flooding.
How is the Panagos et al. (2018) paper different?
Panagos et al. (2018) started from a similar place as method 4 above, as they assumed a crop yield loss for severely eroded land, which they monetised by applying the market price for different crops. Their data on the state of soil erosion in the EU came from the RUSLE2015 model, which provides data on the state of European soil back in 2010. Out of the main crops, wheat production was found to be the most affected (see Figure 1, left-hand side), and at the country-level, Italy was by far the most affected out of the major producers (see Figure 2, right-hand side).
Figure 1: Over a third of Italy’s agricultural land was severely eroded by water in 2010
Source: Panagos et al. (2018), Bonsai Economics
The authors move one step further however, by subsequently using a general equilibrium model to estimate the impact of this lower land endowment on the agriculture sector as a whole, and GDP. In doing so, they found that the total economic cost might be much smaller both at the sectoral and the GDP level (see Figure 2, below). This was primarily because their model included a supply response from areas where the land was not eroded, as well as a substitution effect away from land and towards capital and labour. The paper concludes that the cost of soil erosion may be much smaller than it is implied by directly inferring from the previous direct cost methodologies.
Figure 2: The GDP impact of soil erosion is almost 10 times smaller than its direct cost
Source: Panagos et al. (2018), Bonsai Economics
Conclusion
While the Panagos et al. (2018) paper offers a good reminder of the dangers of directly inferring from direct cost estimations to economy-level losses, it is important to highlight that their methodology was in no way perfect. In fact the authors themselves acknowledge that their estimates should be treated as a lower bound for the cost of erosion, due to their model’s assumption of perfect markets. Moreover, it is unclear whether a supply response from non-eroded land would remain possible if much more soil got eroded.
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