AidData Working Paper

Titling Community Land to Prevent Deforestation: No Reduction in Forest Loss in Morona-Santiago, Ecuador

Date Published

Oct 1, 2014

Authors

Mark T. Buntaine, Stuart E. Hamilton, Marco Millones

Publisher

Citation

Buntaine, Mark T., Stuart E. Hamilton, and Marco Millones. 2014. Titling Community Land to Prevent Deforestation: No Reduction in Forest Loss in Morona-Santiago, Ecuador. AidData Working Paper #2. Williamsburg, VA: AidData. Accessed at http://aiddata.org/working-papers.

AidData Working Paper

Titling Community Land to Prevent Deforestation: No Reduction in Forest Loss in Morona-Santiago, Ecuador

Date Published

Oct 1, 2014

Authors

Mark T. Buntaine, Stuart E. Hamilton, Marco Millones

Citation

Buntaine, Mark T., Stuart E. Hamilton, and Marco Millones. 2014. Titling Community Land to Prevent Deforestation: No Reduction in Forest Loss in Morona-Santiago, Ecuador. AidData Working Paper #2. Williamsburg, VA: AidData. Accessed at http://aiddata.org/working-papers.

Land tenure and land titling programs for forests have become a mainstay of conservation and resource management policy worldwide. They are thought to reduce deforestation by lengthening the time horizon of landholders and improving the ability of landholders to legally exclude competing users. Despite these expectations, reliable evidence about how land titling programs affect forest cover is limited because programs are targeted according to other factors that themselves influence the conversion of forests, such as indigenous status or low population density. We investigate the effect of a donor-funded land titling and management program on forest cover in Morona-Santiago, Ecuador. To estimate the impact of community land titles and management plans, we match plots in program areas with similar plots outside program areas on a variety of covariates that influence forest conversion. Based on matched comparisons, we do not find evidence that land titling or the creation of community management plans reduced forest loss in the first five years after the program. Our results are some of the first evidence about the effects of land titling programs on forests that account for spatial assignment and interactions with other institutions. More broadly, our analysis demonstrates the promise of using remotely sensed data to evaluate the effects of policies beyond normal cycles of policy and program evaluation.