JobKeeper: An Initial Assessment

Abstract

We present details of the design and implementation of the 2020-2021 JobKeeper program and review the literature on its impacts. JobKeeper stimulated the macroeconomy and restrained job loss in the downturn. But because the program was not narrowly targeted, the cost per job saved was high and the impact most likely regressive. However, it would not have been possible to devise and implement a more targeted program in the available time, and as it was, JobKeeper was arguably implemented later than needed for maximum effectiveness. We therefore recommend that Australia consider establishing a short-time work program for use in future recessions.

Introduction

“…The impact of the JobKeeper wage subsidy program is reviewed in an article by Borland and Hunt (2023). With a price tag of $88 billion, it was the most expensive policy implemented to deal with COVID-19.…”

Fiscal Policy in the COVID‐19 Era1

“…Borland and Hunt (2023) consider that the Bishop and Day estimate of 700,000 persons likely represents an upper bound on the employment impact of JobKeeper. The estimate extrapolates employment effects for casual employees to permanent employees whereas ‘the relative instability of casual employment suggests it would be more affected by JobKeeper’.…”

“…As set out in Section 2.2, compensating for COVID income losses was one of the three objectives of the JobKeeper program. For discussion of how JobKeeper performed in achieving its other two objectives, see Treasury (2020), Treasury (2021) and Borland and Hunt (2023).…”

“…This simulated estimate may seem low compared to the Bishop and Day (2020) estimate that JobKeeper alone added 700,000 to employment. However, as discussed in Section 2.2, Borland and Hunt (2023) point out that Bishop and Day (2020) count the large number of workers who were stood down and receiving JobKeeper as employed. In contrast, our estimate does not because the simulated employment effects depend on labour demand.…”

“…In contrast, our estimate does not because the simulated employment effects depend on labour demand. Borland and Hunt (2023) also point out that the Bishop and Day (2020) estimate extrapolates percentage employment effects for casual workers to permanent workers whereas historically employment of permanent workers is less variable. After taking into account these major influences on the Bishop and Day (2020) estimate, our results do not seem inconsistent with their study.…”