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 ====== Projecting deforestation rates based on socioeconomic variables and developing a carbon bookkeeping model ======
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 In this example, an econometric model is coupled to a spatially-explicit simulation model of deforestation. The econometric projection model predicts deforestation rates based on changes in the socioeconomic context of municipalities [[http://www.csr.ufmg.br/dinamica/publications/cap6.pdf|(Soares-Filho et. al, 2008]][[http://www.pnas.org/cgi/doi/10.1073/pnas.0913048107|,Soares-Filho et. al, 2010)]]. A spatial lag regression is applied to compute the influence of five variables on the deforestation trajectory:  Crop area expansion, cattle herd growth, percent of protected areas, proximity to paved roads, and migration rates. A spatial neighborhood matrix allows the model to incorporate the influence of the socioeconomic context of neighboring municipalities in the prediction of deforestation rates within a certain municipality.
-Load the model ''simulate_deforestation_under_socioeconomic_scenarios.egoml'' from ''\Examples\REDD_case_study''. This model is composed of three main parts: the input data, pre-calculation, and the simulation model itself.
+Load the model ''simulate_deforestation_under_socioeconomic_scenarios.egoml'' from ''\Guidebook_Dinamica_5\Models\REDD_case_study''. This model is composed of three main parts: the input data, pre-calculation, and the simulation model itself.
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