Data and Code for: "Temporary Layoffs, Loss-of-Recall, and Cyclical Unemployment Dynamics"

Principal Investigator(s): View help for Principal Investigator(s) Mark Gertler, New York University and NBER; Christopher Huckfeldt, Board of Governors of the Federal Reserve System; Antonella Trigari, Bocconi University, CEPR and IGIER

Version: View help for Version V1

Name	File Type	Size	Last Modified
Figures			12/13/2025 12:36:PM
aim			07/31/2025 03:06:PM
data			07/31/2025 03:06:PM
estimates			07/31/2025 03:06:PM
logfiles			07/31/2025 03:06:PM
FUN_GHT2_MEASUREMENT_EQS_ss.m	text/x-matlab	392 bytes	07/31/2025 11:06:AM
FUN_GHT2_TARGET1_ss.m	text/x-matlab	405 bytes	07/31/2025 11:06:AM
FUN_GHT2_TARGET1_ss_PLD.m	text/x-matlab	270 bytes	07/31/2025 11:06:AM
FUN_GHT2_TARGET2_ss.m	text/x-matlab	570 bytes	07/31/2025 11:06:AM
FUN_GHT2_TARGET2_ss_PLD.m	text/x-matlab	492 bytes	07/31/2025 11:06:AM

Project Description

Summary: We revisit the role of temporary layoffs in the business cycle. While some have emphasized a stabilizing effect due to recall hiring, we quantify from the data an important countercyclical destabilizing effect due to "loss-of-recall'', whereby workers in temporary-layoff unemployment lose their job permanently. We develop a quantitative model allowing for endogenous flows of workers across employment and both temporary-layoff and jobless unemployment. The model captures both pre- and post-pandemic unemployment dynamics, including the recessionary role of loss-of-recall. We use our structural model to show that the Paycheck Protection program generated sizable employment gains, in part by significantly reducing loss-of-recall.

Scope of Project

Subject Terms: Unemployment; Cycles; Recessions; Recall; Layoff

JEL Classification:
E24 Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity

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Published Versions

V1 [2026-02-04]

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Dublin Core

DDI 2.5

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