About

About Steven VanOmmeren

I am an applied economist and data scientist with a passion for using quantitative methods to solve complex real-world problems. My research and professional work focuses on the intersection of economics, statistics, and data science.

Education

I graduated from the University of Chicago in 2020 with a BA in Economics and a BS in Mathematics.

I am currently pursuing an MS in Applied Economics at Boston College, expecting to graduate by the end of 2025.

Professional Experience

Since graduating college in 2020, I have spent 5 years working in economic consulting, with most of my projects involving antitrust litigation, regression analysis, and damages estimation. I worked at Charles River Associates from 2020-2021, and have worked at BRG since 2021, both in the Washington, DC area.

Research Interests

Microeconometric Methods

My economic research employs modern econometric techniques including:

• Difference-in-differences estimation
• Causal inference methods
• Policy evaluation and impact assessment

  Predictive Analytics

  I develop and apply machine learning models for economic and financial forecasting, with particular expertise in:

• Time series analysis and forecasting
• Real-time sentiment analysis using news data
• Stock market prediction and financial modeling

  Odds and Ends

  Some of my spare time is spent on personal projects, with a particular interest in natural language processing and large language models:

• Building a local search engine complete with a PDF processing pipeline and semantic search
• Experimenting with local speech-to-text and text-to-speech models for computer accessibility
• Miscellaneous productivity-enhancing apps and workflows to help me work faster

Publications & Projects

Publications

• Staggered Difference-in-Differences Estimation for Antitrust Analysis: A Review of Literature and Recommendations for Practitioners
• The Difference-In-Differences Antitrust Analysis Is Evolving

I have assisted on a variety of other publications:

• A Detailed Study of Court Decisions on Admissibility of Intellectual Property Damages Experts
• Competition, privacy, and big data
• Pooling or fooling? An experiment on signaling

School Projects

• Predicting Intraday Trading Volume with News Sentiment: An Analysis of U.S. Airline Stocks
• Correcting Multiple Forms of Bias in the Wage Equation of Women Using Conditional Mixed Processes
• Exploring Heterogeneous Responses to Text Message Development Programs: An Application of Machine Learning to Fabregas et al. (2025)
• Modern Child Labor Abuse in the United States - is it Right to Work
• Forecasting the Post-COVID Recovery of Washington DC Public Transportation Usage

Programming Languages

• Stata: Data manipulation and advanced econometric analysis. Most of my professional experience is in Stata.
• Python: Advanced proficiency with extensive use in research and education data projects
• R: Statistical analysis, econometric modeling, and data visualization
• LaTeX: Academic writing and document preparation
• SQL: Database management and data extraction