Our benchmark estimates indicated that higher AI values are positively associated with GDP per capita. Moreover, the effects are more significant in less developed areas of the world. To confirm our estimates, we explored the sensitivity of our estimates to several models, aridity classes, and income groups.
This result contrasts a recent study that found that the relationship among temperature, precipitation, and economic growth was globally generalisable to agricultural and non-agricultural activity in rich and developing countries .
Our results showed that grid-level income per capita was non-linear and concave according to the AI. This finding indicates that income increases with higher water availability of the soil, whereas it decreases with excessive precipitation or too little soil transpiration caused by extreme heat and humidity. This non-linear effect of aridity on income per capita is in line with the estimates shown for temperature shocks (Fig. 3) . In particular, we find that above a threshold of approximately 0.65, a marginal variation in AI did not have economic effects.
However, our estimates show that the areas most affected by soil aridification are located on the African and Asian continents. As a result, these continents will pay the highest price in terms of GDP loss.
This finding is consistent with the “opportunity cost” mechanism related to local agricultural production. We argue that the adverse economic effects of soil aridification are partly due to less efficient crops. For example, if a particular area experiences substantially less precipitation in a given year (or a higher PET), the crop yield could be negatively affected, which would lead to economic losses. Several theoretical and empirical studies have offered insights relevant to our proposed interpretation [23, 24, 25, 26].
Based on the results in Appendix B and shown in Fig. 3, it is possible to evaluate the average annual economic impact of desertification from 1990 to 2015. Figure 4 shows the average annual GDP per capita loss in Africa (Panel A) and Asia (Panel B). We estimate that during the last 25 years, in some areas on the African continent, climate-induced soil aridification had decreased the GDP per capita by more than 12%.
Our results show a slight but significant positive relationship between AI and GDP per capita worldwide. However, the economic effects of the decreased AI were more pronounced in Asia and Africa. We estimate that the cumulative reduction in AI between
1990 and 2015 has negatively affected the Asian GDP per capita by between one and six percentage points, and the African GDP per capita between 9 and 16%.
The results of the association between AI and GDP were used to project the costs of future desertification patterns. We first computed the future grid-cell projections of the AI by using annual precipitation and potential evapotranspiration data drawn from the most recent CMCC-BioClimInd . These projections are obtained from a variety of earth system models and two representative concentration pathways (i.e., RCP 4.5 and RCP 8.5), which are part of the World Climate Research Programme’s Coupled Model Intercomparison Project phase 5 (CMIP5). In particular, we considered the RCP 4.5 emissions scenario. RCP 4.5 assumes a peak in greenhouse gas emissions between 2010 and 2030, followed by a decline throughout the 21st century. For the period 2021–2040, the WorldClim 2.1 database forecasts an increase in temperature between 0.93 and 1.27°C, with precipitation predicted to increase between 10 and 30 percentage points in the northern hemisphere while decreasing between 10 to 40% in the southern hemisphere, depending on the Shared Socioeconomic Pathway (SSP) considered . Conversely, the evapotranspiration is estimated to increase between 0.4 and 3.8% for 2021–2040 compared to the present-day mean (2011–2020) .
In our historical sample (1900–1980), the average AI was 0.489, which declined to 0.479 during the present day (1990–2015). It is predicted to be 0.438 in the projected period from 2040–2079. This result indicates that the average cell would experience rainfall shortages comparable to the present-day mean. Specifically, 17,926 grid cells were arid or hyper-arid (i.e., AI < 0.2) during the historical period. However, this number was projected to increase to 20,998 in the period from 2040–2079. Based on this projection, more than 2,000 grid cells will become arid in the future (i.e., approximately 5 million km2 or 3% of the world’s land surface). Figure 5 shows the grid-cell differences in percentages between the projected AI and the present-day mean for the world, Africa, and Asia.
In Fig. 7 (right), panel B presents the estimation of the effects of future AI variations on GDP per capita growth between the present day and 2079 under the baseline RCP 4.5 scenario. The patterns are similar to those in recent decades. Future variations in the AI resulted in a total cost of 6.7% in GDP per capita growth in Asia and about 15% in Africa.