Description
Design, estimate, and validate econometric models to analyze economic data, forecast outcomes, and evaluate policies affecting markets, firms, and consumers. Collect, clean, and integrate datasets; apply sampling and statistical techniques; and communicate findings through reproducible reports and visualizations.
- • Build and implement econometric models for forecasting and causal inference using time-series, cross-section, and panel data.
- • Design identification strategies (e.g., instrumental variables, difference-in-differences, regression discontinuity) to estimate policy and treatment effects.
- • Clean, transform, and integrate survey, administrative, and transactional datasets for analysis.
- • Select and apply estimation techniques (OLS, MLE, GMM, Bayesian) and appropriate inference procedures.
- • Conduct model diagnostics, robustness checks, and out-of-sample validation.
- • Quantify uncertainty and communicate confidence intervals, prediction intervals, and effect sizes.
- • Develop forecasting systems and nowcasts for key economic indicators and markets.
- • Automate reproducible analytics pipelines and version-controlled code in R, Python, or Stata.
- • Translate model results into actionable recommendations for business leaders and policymakers.
- • Prepare technical reports, visualizations, and presentations that summarize methods, assumptions, and findings.
- • Advise on survey design, sampling, and experimental and A/B test protocols.
- • Perform cost-benefit and counterfactual analyses using econometric estimates.
- • Collaborate with legal, regulatory, or policy teams, including providing expert testimony when required.
- • Review and peer-check models, data sources, and documentation produced by others.
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Last reviewed: Jan 2026