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tylerJPike/README.md

Tyler J. Pike

Research Interests

  1. Macroeconomics: Macro-Finance, Monetary Policy, Firm Dynamics
  2. Econometrics: Non-linear statistics and machine learning, time series analysis and macroeconometrics

Research Background

  1. University of Maryland
    current position
    • PhD student in economics
    • Research Assistant to John Haltiwanger
  2. Federal Reserve Board
    • Research Assistant to Vice Chair Clarida
    • Research Assistant to Macro-Financial Anlaysis Section
  3. University of Richmond
    • BS in Mathematical Economics
    • Economics Research Assistant and Research Fellow

Selected Research Code

  1. "Combining forecasts: Can machines beat the average?"
    with Francisco Vazquez-Grande, September 2020
    Github | Working Paper

  2. "Bottom-up leading macroeconomic indicators: An application to non-financial corporate defaults using machine learning"
    with Horacio Sapriza, and Tom Zimmermann, September 2019
    Github | Working Paper

Statistical Software Packages

  1. OOS for out-of-sample time series forecasting
    Github | Website | CRAN

  2. sovereign for state-dependent empirical analysis
    Github | Website | CRAN

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Pinned

  1. OOS OOS Public

    Out-Of-Sample Time Series Forecasting: OOS introduces a comprehensive framework for time series forecasting with traditional econometric and modern machine learning techniques.

    R 8 2

  2. CanMachinesBeatTheAverage CanMachinesBeatTheAverage Public

    Replication files for "Combining forecasts: Can machines beat the average?" by Tyler Pike and Francisco Vazquez-Grande.

    R 2 2

  3. sovereign sovereign Public

    State-Dependent Empirical Analysis: tools for state-dependent forecasts, impulse response functions, historical decomposition, and forecast error variance decomposition.

    R 11 3

  4. BottomUpMacroIndicators BottomUpMacroIndicators Public

    Replication files for "Bottom-Up Leading Macroeconomic Indicators: An Application to Non-Financial Corporate Defaults Using Machine Learning" by Tyler Pike, Horacio Sapriza, and Tom Zimmermann.

    R 2 2