A Spatial Regression Analysis of Colombia’s Narcodeforestation with Factor Decomposition of Multiple Predictors

In the current accelerated process of global warming, forest conservation is becoming more difficult to address in developing countries, where woodlands are often fueling the illegal economy. In Colombia, the issue of narcodeforestation is of great concern, because of the ramification of narco-activities that are affecting forests, such as agribusinesses and cattle ranching for money laundering. In this study, we use spatially explicit regressions incorporating a factor decomposition of predictors through principal component analysis to understand the impact of coca plantations on local-scale deforestation in Colombia. At a national level there is a positive and statistically significant relationship between coca crops and deforestation. We found out that in 2 out of 4 regions, coca is causing deforestation in the country, especially in the Department of Northern Santander and on the Pacific coast