How Forest Area Data Reliability May Influences Tropical Deforestation Drivers Identification?”

Abstract

The Copenhagen Accord and Cancun Adaptation Framework have been assigned a pivotal
role in achieving the GHG emissions stabilization in sustainable forest management. The medium
and long-term goal of the international community is the containment of deforestation, particularly
in developing countries, by identifying the drivers that affect the sustainability of land use choices.
A wide existing literature has focused on this topic relying on forest area time series provided by
FAO in the Forest Resource Assessments (FRA), but undervaluing the effects of weak data
reliability on estimated outcomes. Comparing cross-country panel regression models, we show how
the impact of deforestation drivers may be affected by the data source and the density level of
analysis both on a global and regional scale. It follows that any research that aims to set the reasons
of deforestation should take into account potential data reliability bias.