For this assignment, I was assigned to work as a research assistant for Professor Arenberg in the Hobby School of Public Affairs here at UH. I was tasked with helping him develop code to automate tasks needed to carry out his research. I assisted in developing Python code that utilizes OpenAI’s API to integrate their AI models into our script as a way to automate the extraction of data from images of graphs.

This was my first time using Python or any programming language for that matter. Although it was intimidating at first, the hands-on experience I got from carrying out this econ related programming project, allowed me to quickly develop and sharpen my once nonexistent programming skills. I conducted this project using Python which expanded my limited knowledge on the vast capabilities of this a versatile programming language and the demand for those skills. During this short three week assignment I derived a versatile set of skills that can be utilized in many different industries. Aside from the new skill set I gained, this assignment provided a novel experience that not many students get the chance to have during undergrad.

Akeh Vesoh (2023)

My job was to first search relevant papers that might have had the dataset my professor was looking for. After not finding the dataset, I instead had to create one manually. The dataset needed to be created was the years of significant policy changes in school funding equalization per state since post Brown v Board of Education, the state governments realized that certain schools/districts were not getting enough funding, so they typically created certain tax/bonds and different funding laws to redistribute funding to create more equitable school environments. My job was to find the years of initial/significant policy changes to state school funding programs geared towards school funding equalization.

Jusvin Charles (2023)

During my three-week tenure as a research assistant, my primary responsibility was to explore potential variables and gather data specific to Africa at a subnational level. This task required me to search through established databases to identify the variables and data each dataset encompassed. Additionally, I was assigned to retrieve and closely examine data from the Nigeria Data Portal. My experience in this role was positive. While the tasks at hand were not exceptionally challenging, they were instrumental in highlighting the extensive amount of time and effort that goes into preliminary research. This experience significantly enhanced my appreciation for the detailed data presented in research studies, underscoring the value of even the smallest data fragments in contributing to a larger body of work.

Richard Guo (2023)

For my assignment, I was given a paper titled “The Missing Benefits of Clean Water and the Role of Mismeasured Pollution” by David A. Keiser. This paper describes data about recreational use of natural resources and talks about “recreational demand modelling”. I was then asked to find papers in popular economic journals that focused on recreation of any type that were connected to the economy. I was told to have papers that discussed recreational use of natural resources on the top of the priority list but still include other recreational papers. After finding a couple of papers, I was told to find data on outdoor recreation in the US across many states. Datasets that included a smaller area of interest were still included but were noted to be less important than the datasets that included wider ranges. The way I found the datasets was through the papers I found earlier in the assignment process and once the datasets were singled out, they needed to be described in a brief but precise way. In the folders I placed the papers that were found, there was also a note for each one describing the importance of them and if they included data worth looking at. The descriptions for the data included the source, a brief description, what level of observation, and what years the data covered.

Sarfaraz Sayed (2023)