Tao Wang
Senior Economist at Bank of Canada
Ottawa, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolTao Wang is a senior economist and PhD candidate who blends macroeconomic and behavioral research with 10 years of quantitative experience, now working at the Bank of Canada. He specializes in household expectations and heterogeneous-agent models, pairing novel microdata with machine learning and NLP applied to millions of news articles to uncover behavioral drivers of macro outcomes. A prolific computational economist, he contributes to the widely used HARK toolkit and develops reproducible scientific workflows in Python (8+ years), with code and tutorials public on GitHub. His background spans policy institutions and media—IMF, Brookings, Caixin and The New York Times—giving him a rare mix of policy intuition, empirical rigor, and storytelling. He is equally obsessed with languages, both human and programming, which informs creative uses of nontraditional data in empirical macroeconomics.
10 years of coding experience
2 years of employment as a software developer
Johns Hopkins UniversityMaster of Public Administration (MPA), Economic Policy and Finance, Master of Public Administration (MPA), Economic Policy and Finance at Cornell UniversityBachelor degree of Economics, Bachelor degree of Economics at Renmin University of China
English, Chinese, Spanish
Github Skills (9)
model-building10
refactoring10
modeling10
model-driven10
refactor10
model-driven-development10
economics10
code-completion9
codecomplete9
Programming languages (4)
Github contributions (5)
econ-ark/HARK
May 2019 - Jul 2019
Heterogenous Agents Resources & toolKit
Role in this project:
Back-end Developer
Back-end DeveloperContributions:42 commits, 16 PRs, 4 comments in 2 months
Contributions summary:Tao's commits primarily focused on refactoring code within the `HARK/BayerLuetticke/TwoAsset.ipynb` notebook. The code changes involve replacing variable names, and commenting out sections, primarily to improve code clarity. The edits suggest a focus on the logic and underlying equations used in the model, likely to enable easier comprehension, maintenance, and collaboration. The code also involves replacing text string 'Q' with question string 'Question', which also helps improve code clarity.
satagentseconomicsagent-based-modeling
iworld1991/HARK
Jun 2019 - Aug 2023
Heterogenous Agents Resources & toolKit
Contributions:48 pushes, 3 branches in 4 years 2 months
handlersesmodulesagentstoolkithydra
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