CV

Education, experience, publications, and skills.

Contact Information

Name Jack Mulqueeney
Professional Title Pre-Doctoral Researcher
Email jack.mulq@icloud.com
Location Chicago, Illinois
Website https://jkmulq.github.io

Professional Summary

Pre-doctoral researcher at the University of Chicago, specialising in applied econometrics and causal inference, with three years of research experience at the Reserve Bank of Australia.

Experience

  • 2025 - Present

    Chicago, USA

    Research Professional
    Becker Friedman Institute at the University of Chicago
    Supervisor - Prof. Evan Rose
    • Empirical research: cleaned and managed cross-country individual-level longitudinal datasets; analysed industry welfare premia and cyclicality of job quality using rank-order logit/probit models, event studies, errors-in-variables methods, and instrumental variables.
    • Methods: ran Monte Carlo simulations of variance estimators and Empirical Bayes methods using parallel processing and high-performance computing clusters.
    • Simulated statistical power for a proposed large-scale experimental design.
  • 2022 - 2025

    Sydney, Australia

    Senior Analyst
    Reserve Bank of Australia
    • Macroeconomic modelling: developed and maintained MARTIN, the RBA’s main macroeconometric model, for monetary policy analysis and forecasting.
    • Produced analysis that informed quarterly forecasts and monetary policy board decisions.
    • Helped lead analysis and drafting for an Assistant Governor speech at the Australian Financial Review Banking Summit.
    • Banknote analysis and policy: conducted a discrete choice experiment in a nationally representative survey to estimate households’ willingness to pay for Central Bank Digital Currency and cash access.
    • Contributed policy analysis on the redesign of banknote distribution arrangements.
  • 2020 - 2021

    Australia

    Summer Research Associate
    Australian Institute of Mathematical Sciences
    • Used Kramers-Moyal expansion to model deterministic systems in Python.
  • 2019 - 2019

    Australia

    Research Assistant
    Research Assistant
    • Assisted with research involving the mathematics of networks and graphs using Python.

Education

  • 2018 - 2021

    Perth, Australia

    Bachelor of Philosophy, First Class Honours
    University of Western Australia
    Mathematics and Economics
    • GPA: 7.0/7.0; WAM: 92.
    • Honours thesis: Econometric inference in weakly identified models. Supervised by Dr. Leandro Magnusson.
    • Relevant coursework: econometrics, time series, statistical learning, stochastic processes, optimisation techniques, and microeconomics.
  • 2019 - 2019

    Philadelphia, USA

    Exchange Student
    University of Pennsylvania
    University exchange program
    • GPA: 3.83/4.
    • Relevant coursework: econometrics, microeconomics, probability theory.

Awards

  • 2021
    Economic Society of Australia (WA Branch) Honours Prize
    Economic Society of Australia, WA Branch

    Awarded to the best B.Phil student in Economics, based on the highest overall mark in Economics Honours.

  • 2020
    Australian Mathematical Sciences Institute Summer Research Scholar
    Australian Mathematical Sciences Institute

    Independent research into stochastic modelling of non-linear dynamical systems, using Python to model systems ranging from simple SDEs to electrical circuits.

Publications

Skills

Programming and Data: R, Python, pandas, NumPy, matplotlib, statsmodels, SQL, Stata
Research Computing: LaTeX, parallel processing, high-performance computing, PBS scripting
Methods: applied econometrics, causal inference, time series, statistical learning, Monte Carlo simulation