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

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.