Hailing from the vibrant city of Lusaka, Zambia, I envisioned a future where I could be a positive force for global change. Opting for a career in economics, I strategically navigate challenges with a skill set that encompasses strategic planning, networking finesse, cooperative spirit, and analytical prowess. Currently pursuing a PhD in Economics with a focus on experimental and monetary policy at George Mason University, my focus on environmental economics and data science reflects my commitment to making a lasting impact. I consider it my life's purpose to empower individuals with knowledge, unlocking a diversity within them that extends far beyond conventional boundaries. With an unwavering belief in resilience and the transformative power of education, I aim to bridge the gap between economic theory and real-world solutions, contributing to a more sustainable and equitable world for all.
Current Projects
Potential Impact of Health Campaigns on Maternal Mortality Rates Among Women of Color
Pregnancy is a critical period with increased health risks for women, such as hypertension and diabetes. This study examines racial disparities in maternal mortality, particularly among Black women, who experience rates twice as high as other racial groups according to the CDC. Using economic tools, machine learning, and geospatial analysis, we analyze state-level data from the CDC and The World Bank through linear regression and random forests. An event study assesses the impact of the 2020 "Hear Her" campaign aimed at reducing maternal mortality among women of color. Preliminary results indicate a potential causal link between the campaign and decreased mortality rates, highlighting the effectiveness of targeted health initiatives in reducing racial disparities. The findings support continued efforts to improve health outcomes for pregnant women of color, leading to broader societal health improvements.
Flushed Away: Assessing the Economic Consequences of Sewage Overflows on California Housing Values
Sewage overflows (SSOs) represent a critical environmental challenge in California, and the impact of SSOs on housing prices is a vital issue. The study aims to determine how the frequency of sewage overflow events affects housing price fluctuations and conduct an event study. Employing linear, lasso, ridge, and random forest regression analyses, the study predicts the severity of overflow. Notably, lasso regression emerges as the most effective model for predicting housing prices in the event of an SSO occurrence. Additionally, the event study analysis provides insights into the factors influencing housing prices.
Test your knowledge with this map quiz! Learn more about my background, research focus, and economic topics through a fun and educational interactive experience.(It was fun coding it feel free to give feedback)
