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Photo of Leland D. Crane

Leland D. Crane

Principal Economist Industrial Output Section Research and Statistics
202-475-7649
[email protected]

Education

  • Ph.D., Economics, University of Maryland, 2014
Current Research Topics
  • Machine Learning and Natural Language Processing
  • Forecasting, Labor Markets
  • Economist

    Board of Governors of the Federal Reserve System

    2014 - present
  • Economist

    US Census Bureau

    2009 - 2014
  • Manufacturing Sentiment: Forecasting Industrial Production with Text Analysis
    Tomaz Cajner, Leland D. Crane, Christopher Kurz, Norman Morin, Paul E. Soto, and Betsy Vrankovich
    Finance and Economics Discussion Series (2024)
    https://doi.org/10.17016/FEDS.2024.026
  • Tracking Real Time Layoffs with SEC Filings: A Preliminary Investigation
    Leland D. Crane, Emily Green, Molly Harnish, Will McClennan, Paul E. Soto, Betsy Vrankovich, and Jacob Williams
    Finance and Economics Discussion Series (2024)
    https://doi.org/10.17016/FEDS.2024.020
  • Payroll Employment at the Weekly Frequency
    Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz
    American Economic Review: Papers and Proceedings (2023)
    https://doi.org/10.1257/pandp.20231052
  • Cyclical labor market sorting
    Leland D. Crane, Henry R. Hyatt, and Seth M. Murray
    Journal of Econometrics (2023)
    https://doi.org/10.1016/j.jeconom.2021.12.015
  • An evaluation of the Paycheck Protection Program using administrative payroll microdata
    David Autor, David Cho, Leland D. Crane, Mita Goldar, Byron Lutz, Joshua Montes, William B. Peterman, David Ratner, Daniel Villar, and Ahu Yildirmaz
    Journal of Public Economics (2022)
    https://doi.org/10.1016/j.jpubeco.2022.104664
  • Business exit during the COVID-19 pandemic: Non-traditional measures in historical context
    Leland D. Crane, Ryan A. Decker, Aaron Flaaen, Adrian Hamins-Puertolas, and Christopher Kurz
    Journal of Macroeconomics (2022)
    https://doi.org/10.1016/j.jmacro.2022.103419
    See also » FRB Working Paper (2021)
  • Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data
    Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz
    National Bureau of Economic Research Studies in Income and Wealth (2022)
    See also » FRB Working Paper (2019)
  • The $800 Billion Paycheck Protection Program: Where Did the Money Go and Why Did It Go There?
    David Autor, David Cho, Leland D. Crane, Mita Goldar, Byron Lutz, Joshua Montes, William B. Peterman, David Ratner, Daniel Villar, and Ahu Yildirmaz
    Journal of Economic Perspectives (2022)
    https://doi.org/10.1257/jep.36.2.55
  • Business Exit During the COVID-19 Pandemic: Non-Traditional Measures in Historical Context
    Leland D. Crane, Ryan A. Decker, Aaron Flaaen, Adrian Hamins-Puertolas, and Christopher Kurz
    Finance and Economics Discussion Series (2021)
    https://doi.org/10.17016/FEDS.2020.089r1
  • Tracking Labor Market Developments during the COVID-19 Pandemic: A Preliminary Assessment
    Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz
    Finance and Economics Discussion Series (2020)
    https://doi.org/10.17016/FEDS.2020.030
  • Dynamic Beveridge Curve Accounting
    Hie Joo Ahn and Leland D. Crane
    Finance and Economics Discussion Series (2020)
    https://doi.org/10.17016/FEDS.2020.027
  • The US Labor Market during the Beginning of the Pandemic Recession
    Tomaz Cajner, Leland D. Crane, Ryan A. Decker, John Grigsby, Adrian Hamins-Puertolas, Erik Hurst, Christopher Kurz, and Ahu Yildirmaz
    Brookings Papers on Economic Activity (2020)
    https://doi.org/10.1353/eca.2020.0005
  • Tracking the Labor Market with "Big Data"
    Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz
    FEDS Notes (2019)
    https://doi.org/10.17016/2380-7172.2441
  • Business Dynamics in the National Establishment Time Series (NETS)
    Leland D. Crane and Ryan A. Decker
    Finance and Economics Discussion Series (2019)
    https://doi.org/10.17016/FEDS.2019.034
  • Using Payroll Processor Microdata to Measure Aggregate Labor Market Activity
    Tomaz Cajner, Leland Crane, Ryan Decker, Adrian Hamins-Puertolas, Christopher Kurz, and Tyler Radler
    Finance and Economics Discussion Series (2018)
    https://doi.org/10.17016/FEDS.2018.005
  • An Assessment of the National Establishment Time Series (NETS) Database
    Keith Barnatchez, Leland D. Crane, and Ryan A. Decker
    Finance and Economics Discussion Series (2017)
    https://doi.org/10.17016/FEDS.2017.110
  • Essays on Search and Matching in the Labor Market
    Leland Crane
    Dissertations (University of Maryland, College Park) (2014)
    https://doi.org/10.13016/M2S015
  • Firm Dynamics and Assortative Matching
    Leland Crane
    Center for Economic Studies (CES) Working Paper Series (2014)
  • Understanding the Evolution of Trade Deficits: Trade Elasticities of Industrialized Countries
    Leland Crane, Meredith A. Crowley, and Saad Quayyum
    Economic Perspectives (2007)

  • conference

    2018

    ESCoE Conference on Economic Measurement

    Using Payroll Processor Microdata to Predict Employment

  • conference

    2018

    Econometric Society Asian Summer Meeting

    Cyclical Labor Market Sorting

  • conference

    2018

    NBER Summer Institute

    Improving the Accuracy of Economic Measurement with Multiple Sources: The Case of Payroll Employment Data

  • discussion

    2018

    Chicago Fed-Upjohn 2018 Conference on Vacancies and Job Search

    Discussion of "Wages, Workers and Vacancy Durations: Evidence from Linked Data"

  • conference

    2017

    Comparative Analysis of Enterprise Data Conference

    Using Payroll Processor Microdata to Predict Employment

  • conference

    2017

    Midwest Macro

    Cyclical Labor Market Sorting

  • conference

    2017

    Econometric Society North American Summer Meeting

    Cyclical Labor Market Sorting

  • conference

    2016

    Society for the Advancement of Economic Theory Conference

    Supermodularity and Search

Conference Organization

  • 2023 | Washington D.C.

    Conference on Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics

    Co-organizer

  • 2019 | Washington D.C.

    Conference on Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics

    Co-organizer

Referee
  • Journal of Econometrics
Professional Affiliation
  • American Economic Association
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Last Update: August 2, 2024