# **Figure 8: The Feasibility–Ambitiousness (FAB) matrix**

The FAB shows that setting promising targets requires the consideration of both ambitiousness and feasibility. Neither low-hanging fruits nor long shots are desirable as they may lead to greenwashing allegations (see Section 5.1) The ideal targets are both feasible and ambitious but require additional SLB funding to become realizable.

<!-- Start of picture text --> forward-looking<br>extrapolates business-as-usual<br>Ambitiousness trends with no policy changes<br>Feasibility Low High Very high<br>Highly ambitious<br>backward-looking but low chance<br>based on historical Low Long Shots of success<br>precedents of Target unlikely to<br>relevant peers be achieved given<br>High lack of historical<br>precedence<br>Reachable<br>Low-Hanging Targets<br>Very high Fruits<br>Highly feasible but unambitious<br>Target requires little to no effort and Source: Wang, Gurhy,<br>may have been reached in any case Hanusch, Kollenda (2023)<br><!-- End of picture text --> Source: Authors.

The first type stems from funding unrealistic projects whose targets may never be reached. This is compounded by the second risk, namely that they will need to justify benefiting from a stepup when the issuer fails to meet an unrealistic SPT – especially, if it was known that the SPT’s feasibility was low.

We illustrate how SPTs for reduced deforestation in Brazil’s Legal Amazon could be set using the FAB matrix. The methodology to evaluate feasibility relies on a peer country comparison with other tropical forest countries. For these countries, we use country-level primary forest loss data from the Global Forest Watch rather than INPE’s data, which is only available for Brazil’s Legal Amazon. We set the SPT horizon to four years for this application. From a collection of all tropical forest countries, we selected 19 comparable peer countries with non-negligible deforestation rates in the past.15 Because of the disproportional size of Brazil’s forest area, our deforestation indicator is standardized to represent annual forest loss relative to the forest area in the year 2000. Figure 9 shows the selected countries and annual relative forest losses since 2000. In the two decades until 2021, Brazil’s Legal Amazon has lost 7 percent of its primary forest area – a loss of 261,567 square kilometers, almost the total land area of Ecuador.

# **5.2 Ambitiousness**

Ambitiousness is a _forward-looking_ concept based on projecting a business-as-usual (BAU) scenario. Given the discussion on macroeconomic drivers of deforestation in Section 4 we construct a BAU scenario by applying equation (7) to predict deforestation with forecasted macroeconomic conditions from 2022-2025 from the World Bank’s Macro-Fiscal Model (Burns et al., 2019).16 Figure 10 shows that given forecasted macroeconomic conditions, deforestation in Brazil’s Legal Amazon

> 15Angola, Argentina, Bolivia, Brazil, Cameroon, Republic of Congo, Colombia, Ecuador, Gabon, Guyana, Indonesia, India, Mexico, Peru, Suriname, Tanzania, Uganda, República Bolivariano de Venezuela, and Zambia.

> 16Alternative modeling choices for BAU scenarios could be based on computable general equilibrium models, time series econometrics or dynamic factor models. The best choice will depend on the indicator of interest.

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