Pre-Doc Research Experience
UC Berkeley’s Center for Effective Global Action
I worked as a research associate for Professor Edward (Ted) Miguel at Berkeley’s Center for Effective Global Action on the Syrian Refugee Life Study. In this project, we experimentally analyzed the impact of housing assistance on life outcomes of Syrian refugees in Jordan in partnership with the Norwegian Refugee Council. We also conducted a longitudinal panel survey among a representative sample of Syrian refugees in Jordan. This research is also led by Sandra Rozo (World Bank) and Emma Smith (Harvard).

The World Bank, Poverty and Equity Global Practice
I was a consultant for the Kenya Analytical Program on Forced Displacement, a project which is led by Edward Miguel (Berkeley), Nistha Sinha (World Bank), Utz Pape (World Bank), and Theresa Beltramo (UNHCR). In this research, we assess the livelihoods of refugees and hosts in Kenya on the levels of employment, education, mental health, and resilience to shocks. The team is working on collecting longitudinal data and conducting novel randomized interventions that focus on economic and psychological wellbeing and social cohesion.

UC Berkeley's Haas School of Business
I also assisted Professor Nick Tsivanidis at the Haas School of Business, Berkeley, on a project that aims to assess how the influx of Syrian migrants shapes the structure of urban areas in Jordan using a set of welfare measures. We use multiple data sources including administrative data from Jordan’s Department of Statistics, primary data we collected, and millions of call data records to define social networks. Michael Gechter (Penn State) and Nathaniel Young (EBRD) also lead this research.

More about the researchers leading these exciting projects









Coding
Python, ArcGIS, Algorithms, and Maps
I am lucky to learn how to use Python and ArcGIS through many of my tasks with Professor Nick Tsivanidis. I create maps, run algorithms and loops, and perform matrix algebra operations. As an aspiring economist, it seems to me that Python is a very powerful tool that I am getting to learn more about.
Below is an algorithm that I wrote to calculate a commute matrix to measure predicted change in residential populations and employment.

Stata, Stata, and Stata!
Economists use Stata a lot. Although I thought that what I learned about Stata during my master’s was enough, my work experience has shown me that there is a lot more to do. I use Stata to store descriptives in matrices, create loops for many outcomes from various surveys, and create sophisticated graphs.
Below is a screenshot from some programs that I wrote to create binscatter plots for our RCT and another to compare SRLS and JLMPS (2016) panel data.
