Photo of Nathan M. Palmer

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
  • Carroll, Christopher D., Alexander M. Kaufman, Jacqueline L. Kazil, Nathan M. Palmer, and Matthew N. White (2018). "The Econ-ARK and HARK: Open Source Tools for Computational Economics," Proceedings of the 17th Python in Science (SciPy) Conference 2018.
  • McLaughlin, Joe, Adam Minson, Nathan Palmer, and Eric Parolin (2018). "The OFR Financial System Vulnerabilities Monitor," Working Paper, no. 18-01. Office of Financial Research.
  • Geanakoplos, John, Robert Axtell, J. Doyne Farmer, Peter Howitt, Benjamin Conlee, Jonathan Goldstein, Matthew Hendrey, Nathan M. Palmer, and Chun-Yi Yang (2012). "Getting at Systemic Risk via an Agent-Based Model of the Housing Market," American Economic Review: Papers and Proceedings, vol. 102, no. 3, pp. 53-58.
  • 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
Last update: June 30, 2022