In introductory economics classes, we are first taught about the tradeoff between equity and efficiency—how can we navigate the delicate balance between maximizing economic performance and ensuring a fair distribution of resources? This issue is the heart of major news headlines, as the new administration has signaled a clear shift in priorities. Look at the language: We've seen the rise of DOGE (The Department of Government Efficiency), followed by significant cuts to DEI programs (diversity, equity, and inclusion).

With the Trump administration in power, we are witnessing significant policy shifts—these actions fall under a broader agenda of aggressive cost-cutting. Targeting essential services like Medicaid and SNAP, these cuts dismantle the social safety net and disproportionately impact low-income families. The extremity of Trump's executive orders has spurred discourse and drawn overwhelming attention to the broader idea of "fiscal responsibility": How is this used to frame policies as necessary, masking their impact on communities' well-being?

The US's evolving domestic policy is a microcosm of austerity measures imposed by the Global North on the Global South through international institutions. The World Bank and International Monetary Fund (IMF) pride themselves on providing financial support for emerging economies, ranging from India to Brazil, measuring success through macroeconomic indicators (GDP, inflation, debt levels). By viewing the economy through a singular lens, they overlook the disconnect between fiscal goals and social well-being.

I believe research needs to focus more on the Global South, which is why my analysis centers on how austerity policies impact different states in varied ways. My project is broadly framed around the question: How do baseline structural vulnerabilities shape the long-term social and economic effects of austerity?

Within this question, I'm particularly interested in examining which indicators tend to "improve" under austerity (e.g., fiscal deficit) and which tend to deteriorate (e.g., public health or inequality). From there, I want to investigate how baseline development conditions shape the tradeoffs between fiscal and social outcomes post-IMF intervention. By tracing how a policy shock flows through existing systems and affects outcomes, I hope to highlight the importance of baseline development in determining long-term effects.

As the idea continues to evolve, I'm exploring different methods. Like other researchers, I want to start with a basic regression to simulate austerity and reflect on how structural disadvantages compound the effects. Later, I want to design a multilayer network model using differential equations and Monte Carlo simulations to quantify the cascading impact of social spending cuts on employment, income, and community stability. 

I want to pursue a project that capitalizes on current discussions around equity and efficiency, designing a mathematical model that captures the complexity of this tradeoff. The model aims to describe the cascading effects of policy interventions on communities, disaggregating social systems into interconnected components to reveal the hidden consequences of economic decisions. 

If a job training program is cut, several impacts occur: People lose jobs, families have less income, and children may receive less education. I want to leverage predictive mathematical frameworks to understand the long-term social and economic domino effects of efficiency-driven policy interventions, answering questions like 'What happens if food programs are cut by 5 percent?'

Although it is a hefty project, I'm excited to continue revising it to create an outcome that drives meaningful insights into the real-world impact of policy interventions. This will contribute to evidence-based policymaking that considers both economic performance and social resilience.