Deforestation Analysis

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To analyze the relationship between agricultural commodity prices, conservation policies and deforestation in Colombia, a multiple regression model will be constructed to relate the changes in forest cover (variable pending) by established period of time, tipping points in the policies (independent variable ) and variation in the agricultural prices (control variable) (Assuncao et al., 2015, Reyes-Hernández et al., 2003). The following describes each of the variables to be analyzed in the study:

Deforestation data will be collected from the platform Terra-i. This is a near real time monitoring system of land use and land cover change in Latin America and the Caribbean; it uses rainfall and vegetation satellite data to
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In this sense, the report mentions that the departments with highest deforestation rates are: Caquetá (20577 ha), Guaviare (5447 ha), Meta (4099 ha), Putumayo (3757 ha) and Norte de Santander (3441 ha). The Figure 1 shows the deforestation areas preliminary selected in red. The Caquetá, Guaviare and Putumayo areas selected are located in the border of the Amazon region of Colombia, which is part of one of the most important rain forest in the world. Meanwhile, the deforestation area selected in Meta correspond at the border area of the national park Serranía de la Macarena. Finally, the Norte de Santander area has cocoa, cassava, corn and palm oil crops.


For the measurement of the independent variable, forestry and conservation policies established in Colombia in the last 20 years will be compiled. Policies that have implemented plans for reforestation and control of deforestation will be selected. Subsequently, with the deforestation data obtained, tipping points will be identified, between the establishment of the policy and the increase or decrease of the deforestation rates of the country. These tipping points will allow to establish the specific periods of time for the analysis.

Additionally, and considering that agricultural and livestock
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