I am a Ph.D. Candidate in Economics at the University of California, Santa Barbara. My research interests lie at the intersection of environmental, development, and labor economics.
I use geospatial data and new difference-in-differences estimators to estimate the effects forest policies on deforestation in the Peruvian Amazon.
Here you can see how I apply
de Chaisemartin & D’Haultfoeuille’s did_multiplegt
estimator in Stata.
Prior to joining UCSB, I worked at the Economic Research Division of Mexico’s central bank (Banco de México) doing research on labor markets, monetary policy, inequality, and deforestation. I was also a consultant for the World Wildlife Fund-US and an analyst at Mexico’s National Institute of Ecology and Climate Change.
Ph.D. in Economics, (In Progress)
University of California, Santa Barbara
M.A. in Economics, 2020
University of California, Santa Barbara
Master of Public Policy, 2015
Duke University
B.A. in Economics, 2011
Instituto Tecnológico Autónomo de México
Concessions that grant logging rights to firms support economic development based on forest resources. Eco-certifications put sustainability restrictions on the operations of those concessions. For spatially detailed data, including many pre-treatment years, we use new difference-in-differences estimators to estimate 2002–2018 impacts upon Peruvian Amazon forests from both logging concessions and their eco-certifications. We find that the concessions − which in theory could raise or reduce forest loss − did not raise loss, if anything reducing it slightly by warding off spikes in deforestation pressure. Eco-certifications could reduce or raise forest loss, yet we find no significant impacts.
Deforestation and forest fragmentation are leading drivers of biodiversity loss. Protected areas have been the leading conservation policy response, yet their scale and scope remain inadequate to meet biodiversity conservation targets. Managed forest concessions increasingly have been recognized as a complement to protected areas in meeting conservation targets. Similarly, programs for voluntary third-party certification of concession management aim to create incentives for logging companies to manage forests more sustainably. Rigorous evidence on the impacts from large-scale certification programs is thereby critical, yet detailed field observations are limited, temporally and spatially. Remotely-sensed data, in contrast, can provide repeated observations over time and at a fine spatial scale, albeit with less detail. Using the Global Forest Change dataset, we examine annual forest loss in Cameroon during 2000–2013 to assess the impact of Forest Stewardship Council certification, as well as uncertified logging concessions and national parks. We use panel regressions that control for the effects of unobserved factors that vary across space or time. We find low forest loss inside the boundaries of each management intervention, with <1% lost over the study period. Yet those low levels of loss appear to be influenced more by a site’s proximity to drivers of deforestation, such as distances to population centers or roads, than by national parks, uncertified concessions, or certification. The exception is that if a site faces high deforestation pressure, uncertified logging concessions appear to reduce forest loss. This may reflect private companies’ incentives to protect rights to forest use. Such an influence of private logging companies could provide a foundation for future impacts from certification upon rates of forest loss, at least within areas that are facing elevated deforestation pressures.
Protected areas (PAs), which restrict economic activities, are the leading land and marine policy for ecosystem conservation. Most contexts feature different types of protection that vary in their stringency of management. Using spatially detailed panel data for 1986-2018, we estimate PAs’ impacts upon forests in the Peruvian Amazon. Which type of protection has greater impacts on the forest is ambiguous, theoretically, given potential for significant differences by type in siting and enforcement. We find that the less strict multiple-use PAs, that allow local livelihoods, do no worse for forests than strict PAs. Each PA type holds off small loss spikes seen in unprotected forests; and multiple-use, if anything, do a bit better. This adds to evidence on the coexistence of private activities with conservation objectives.
Head Teaching Assistant (TA): Winter 2023, Fall 2022.
TA: Spring 2022, Fall 2021, Winter 2020, Fall 2019.
TA: Winter- Summer 2021
TA: Spring and Fall 2021
TA: Spring 2015
Outstanding Undergraduate Teaching Assistant Award
Department of Economics, UC Santa Barbara
“Jimena does a great job going through practice problems and thoroughly explaining the material with the class while still giving us many opportunities to ask questions.” - Econ 101 student
“Jimena writes her notes amazingly well and can teach the material very effectively and succintly. I really appreciate how all the sections are directly applicable to the weekly quizzes. She is also incredibly friendly and genuinely cares about her students.” - Econ 101 student