Nency Dhameja
Hi, I’m Nency Dhameja (pronounced “Nancy”), a 5th-year Ph.D. candidate in Econometrics and Quantitative Economics at Binghamton University, State University of New York (SUNY).
My research is centered on causal inference and policy evaluation in applied microeconomics. I study how institutions and local environments shape economic, labor-market, and health outcomes, using modern quasi-experimental methods including difference-in-differences, reweighting and confounding adjustment, and machine learning–augmented causal designs.
Prior to my Ph.D., I pursued an Executive MBA in Singapore and earned a Bachelor of Technology in India. This technical background informs my research through an emphasis on reproducible workflows, large-scale administrative data, and computational modeling, including LLM-based agent simulations, for studying economic behavior and policy interventions.
Fields: Applied Microeconomics, Urban & Spatial Economics, Labor Economics, Computational Economics
- Causal Inference: Staggered Difference-in-Differences, Event Studies, Synthetic Control Methods
- Confounding Adjustment: Inverse Probability Weighting (IPW), Entropy Balancing, Double Machine Learning
- Spatial Analysis: Neighborhood Exposure Designs, Salience and Attention Kernels
- Computational Economics: Agent-Based Models, LLM-Based Economic Agents