Jameson A
- Research Program Mentor
PhD candidate at University of Georgia
Expertise
Economics and Statistics
Bio
I am a first-generation student who is fascinated by causal inference, time series analysis, and machine learning. I am pursuing a Master's degree in Statistics and a Ph.D. in Econometrics and Quantitative Economics, aiming to apply my skills to data science, risk analysis, and applied economics. I love to explore new methods and techniques to solve real-life problems using data and models. I have completed internships with several U.S. government agencies and leading financial institutions, gaining diverse experience in both the public and private sectors. I enjoy creating digital art and playing soccer video games in my spare time. I find these activities relaxing and fun, and they also help me express my creativity and passion. Sometimes I also visit the local parks for a walk, where I can appreciate the beauty of nature and clear my mind. I am always eager to learn new things and challenge myself academically and personally.Project ideas
Assessing the impact of climate change on drought risk using machine learning and meteorological models.
This project aims to use historical data on precipitation, temperature, soil moisture, drought indicators, and meteorological models that simulate the atmospheric conditions to train a machine learning model that can assess the likelihood and intensity of droughts in different regions under different climate scenarios. The project will also explore the assessments' potential adaptation strategies and policy implications. The project will require skills in data processing, machine learning, and meteorological modeling. The project will be relevant for students who are interested in environmental economics, risk analysis, or water resource economics.
Measuring the income inequality and social mobility using Gini coefficient and intergenerational elasticity
This project aims to use data from the World Bank, the OECD, and other sources to calculate the Gini coefficient and the intergenerational elasticity of income for different countries and regions over time. The project will also explore the factors that influence these measures and their implications for economic development and social justice. The project will require skills in data collection, analysis, and visualization. The project will be relevant for students who are interested in comparative economics, development economics, or public policy.
Measuring the impact of online reviews on customer satisfaction and loyalty for a hotel booking platform.
This project aims to design and conduct a survey to measure how online reviews influence customer satisfaction and loyalty for a hotel booking platform. The project will use a mixed-methods approach, combining quantitative and qualitative data from online surveys, interviews, and focus groups. The project will also analyze the relationship between online reviews, customer satisfaction, loyalty, and behavioral outcomes, such as repeat purchases, referrals, and complaints. The project will require skills in survey design, data collection, data analysis, and report writing. The project will be relevant for students who are interested in marketing, consumer behavior, or hospitality management.
Analyzing the economic impacts of COVID-19 pandemic using machine learning and macroeconomic models.
This project aims to use historical data on various economic indicators, such as GDP, unemployment, inflation, etc., and macroeconomic models that capture the interactions between different sectors and agents in the economy to train a machine learning model that can analyze the effects of COVID-19 pandemic on different countries and regions under different policy scenarios. The project will also explore the implications of the analysis for economic recovery and resilience. The project will require skills in data analysis, machine learning, and macroeconomic modeling. The project will be relevant for students who are interested in applied economics, policy evaluation, or development economics.
Analyzing the impact of climate change on food security using machine learning and crop models.
This project aims to use historical data on crop yields, weather, soil quality, irrigation, and crop models that simulate the potential effects of climate change on agricultural productivity to train a machine learning model that can analyze the vulnerability and resilience of food systems in different regions under different climate scenarios. The project will also explore the possible adaptation strategies and policy implications of the analysis. The project will require skills in data processing, machine learning, and crop modeling. The project will be relevant for students who are interested in development economics, food policy, or agricultural economics.