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Nathan M. Palmer

Education

  • Ph.D., Computational Social Science, George Mason University, 2015
  • M.A., Economics, Boston University, 2011
  • B.S., Computer Science, Trinity University, 2005
Current Research Topics
  • Machine learning and AI
  • Agent-based models: agent behavior & estimation
  • Senior Economist

    Board of Governors of the Federal Reserve System

    2021 - present
  • Economist

    Board of Governors of the Federal Reserve System

    2018 - 2021
  • Researcher: Economist

    Office of Financial Research, U.S. Treasury

    2016 - 2018
  • PhD Intern

    Consumer Financial Protection Bureau

    2014 - 2015
  • PhD Intern

    Office of Financial Research, U.S. Treasury

    2012 - 2016
  • PhD Intern: Artificial Intelligence Engineer

    MITRE Corporation

    2011
  • The Econ-ARK and HARK: Open Source Tools for Computational Economics
    Christopher D. Carroll, Alexander M. Kaufman, Jacqueline L. Kazil, Nathan M. Palmer, and Matthew N. White
    Proceedings of the 17th Python in Science Conference (SciPy 2018) (2018)
    https://doi.org/10.25080/Majora-4af1f417-004
  • The OFR Financial System Vulnerabilities Monitor
    Joe McLaughlin, Adam Minson, Nathan Palmer, and Eric Parolin
    OFR working paper (2018)
  • Getting at Systemic Risk via an Agent-Based Model of the Housing Market
    John Geanakoplos, Robert Axtell, J. Doyne Farmer, Peter Howitt, Benjamin Conlee, Jonathan Goldstein, Matthew Hendrey, Nathan M. Palmer, and Chun-Yi Yang
    American Economic Review: Papers and Proceedings (2012)
    https://doi.org/10.1257/aer.102.3.53
  • conference

    2021

    Computing in Economics and Finance

    Visual Regression Tables for Machine Learning and Artificial Intelligence

  • discussion

    2020

    Nontraditional Data & Statistical Learning with Applications to Macroeconomics, Federal Reserve Board & Bank of Italy

    Discussion: Forecasting UK inflation, Macroeconomy as a Random Forest, & Consequences of the Covid-19 Job Losses

  • seminar

    2020

    Federal Reserve Board

    Understanding Interpretable Machine Learning

  • seminar

    2019

    Johns Hopkins University Department of Economics

    A Direct Estimate of Rule-of-Thumb Consumption using the Method of Simulated Quantiles and Cross Validation

  • conference

    2019

    Computing in Economics and Finance

    A Direct Estimate of Rule of Thumb Behavior using the Method of Simulated Quantiles and Cross Validation

  • seminar

    2019

    Federal Reserve Board

    Dynamic Limit Order Dispersion and Volatility Persistence in a Simple Limit Order Book Model

  • conference

    2019

    Eastern Economic Association

    Dynamic Limit Order Dispersion and Volatility Persistence in a Simple Limit Order Book Model

  • conference

    2018

    PhD Symposium on Financial Stability, Office of Financial Research

    Discussion: Accounting for Strategic Response in an Agent-Based Model of Financial Regulation

  • seminar

    2018

    Federal Reserve Board

    A Simple Direct Estimate of Rule-of-Thumb Consumption using the Method of Simulated Quantiles and Cross-Validation

  • conference

    2018

    Eastern Economic Association

    A Simple Direct Estimate of Rule-of-Thumb Consumption using the Method of Simulated Quantiles and Cross-Validation

  • conference

    2017

    Heterogeneous Agents and Agent-Based Modeling: The Intersection of Policy and Research

    Heterogeneous-Agent Resources & Toolkit (HARK)

  • conference

    2017

    Computing in Economics and Finance

    A Simple Direct Estimate of Rule-of-Thumb Consumption using the Method of Simulated Quantiles and Cross-Validation

  • seminar

    2017

    American University Department of Economics

    Learning to Dynamically Optimize from Individual Experience

  • seminar

    2016

    Federal Reserve Board

    Heterogeneous-agent modeling, tools, and incentives

  • conference

    2016

    Computing in Economics and Finance

    Regret Learning: Learning to Optimize from Individual Experience

  • conference

    2016

    International Congress on Agent Computing, George Mason University

    Regret Learning: Learning to Optimize from Individual Experience

  • conference

    2015

    Open Computational Economics Workshop, IMF &CFPB

    Heterogeneous-agent modeling, tools, and incentives

  • conference

    2015

    Computing in Economics and Finance

    The Heterogeneous-Agent Computational toolKit: An Extensible Framework for Solving and Estimating Heterogeneous-Agent Models

  • conference

    2015

    M3C3 Workshop, University of Maryland & George Mason University

    Learning to Consume: Individual versus Social Learning

  • discussion

    2015

    Zurich Initiative on Computational Economics (ZICE)

    Learning to Consume: Individual versus Social Learning

  • conference

    2014

    Heterogeneous Agents Working Group Workshop, IMF &CFPB

    Heterogeneous-agent modeling, tools, and incentives

  • conference

    2014

    NSF IPAM Workshop: Mathematics of Social Learning

    Learning to Consume: Individual versus Social Learning

  • conference

    2012

    Computing in Economics and Finance

    Learning to Consume: Individual versus Social Learning

  • seminar

    2011

    Santa Fe Institute

    Getting at Systemic Risk via an Agent-Based Model of the Housing Market: Empirical and Theoretical Details

Awards
  • 2016

    Office of Financial Research

    Leadership Award

Conference Organization
  • September 2017 | Washington, DC

    Heterogeneous Agents and Agent-Based Modeling: The Intersection of Policy and Research

    Organizer

Referee
  • Computational Economics
  • Journal of Economic Behavior & Organization
  • Macroeconomic Dynamics
  • National Science Foundation
  • PLOS One
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Last Update: August 2, 2024