Essays in Development Economics and Education
Open AccessThis dissertation is divided into three papers where I study the relationship between violence, poverty, and education. In 2016, the Colombian government ended a 50-year-old war with the largest guerrilla group in Latin America. Due to a power vacuum left in conflict zones after the peace agreement, large spikes in violence were reported in municipalities of the country dominated by the former rebel group. Using a difference-in-difference design, I study the effect of this violence increase on students' achievement. My first paper focuses on high school education, where I find that a 10 percent increase in the homicide rate reduces average high school test scores by approximately 0.03 standard deviations. This impact is greater in the case of poor students who experience a decrease of about 0.1 standard deviations per subject area — equivalent to 3.3 percentage points out of the final score. My second paper focuses on higher education, where I find that the same increase in the homicide rate reduces average college test scores by approximately 0.07 standard deviations in the English section of the test. Poor students suffer a larger negative impact equivalent to 0.16 standard deviations — equivalent to 3.4 percentage points out of the final score. In both cases, I find a slightly larger negative effect on female students attending high school and college. My third paper proposes a methodological framework for complex causal inference in development economics. This framework combines machine learning and econometrics to study the relationship between multidimensional poverty components and how they are affected by violence. Using Bayesian networks (BN), I find that minimum living standards—measured in terms of access to water, connection to the sewage system, and the quality of walls and floors—are strong predictors of the education and health dimensions of poverty. With the BN output, I design an Instrumental variables (IV) approach according to which, having an illiterate person within a household increases by 0.4 percentage points the household's likelihood to be a victim of violence. Even though a small effect, it provides an example of how to integrate machine learning and econometrics for the purpose of complex causal inference. This dissertation improves our understanding of the ways in which violence helps to perpetuate poverty and provides new insights on how to design cost-effective interventions to improve the livelihoods of the least advantaged.
- All rights reserved
Notice to Authors
If you are the author of this work and you have any questions about the information on this page, please use the Contact form to get in touch with us.
| Thumbnail | Title | Date Uploaded | Visibility | Actions |
|---|---|---|---|---|
|
|
GruesoHurtado_gwu_0075A_15860.pdf | 2022-10-04 | Open Access |
|