RDP 2020-07: How Many Jobs Did JobKeeper Keep? 8. Assessment

8.1 Aggregate Effects

Our baseline estimate is that receiving JobKeeper increased an employee's probability of remaining employed by about 20 percentage points. We can, thus, estimate the aggregate effect of the wage subsidy on employment by multiplying this estimate (0.2) by the number of people on JobKeeper during our period of analysis (around 3.5 million). This back-of-the-envelope calculation suggests that JobKeeper reduced the aggregate fall in employment over the first half of 2020 by at least 700,000.

To put this estimate into perspective, the actual fall in employment over the first half of 2020 was 650,000. As such, our estimates imply that overall employment losses would have been twice as large over this period without JobKeeper. Our estimate of the no-JobKeeper counterfactual – which subtracts our estimates of the employment saved by JobKeeper from the actual level of employment – was shown in Figure 1, along with its 95 per cent confidence interval.[40]

Our estimate is similar to Treasury's initial estimate that the unemployment rate would be around 5 percentage points higher in the absence of JobKeeper.[41] A 5 percentage point reduction in the unemployment rate equates to at least 700,000 fewer people leaving employment.[42] Our estimate is a little larger than Treasury's more recent estimate in the July Economic and Fiscal Update that all of the fiscal stimulus has prevented the loss of around 700,000 jobs (Australian Government 2020b, p 38). The latter estimate also includes support measures other than JobKeeper, such as cash payments to households, income support and investment incentives for businesses, loan guarantees and regulatory measures, so it could be interpreted as an upper bound estimate of JobKeeper's effect.

We have characterised our estimate of the aggregate effect as being ‘at least 700,000’, rather than ‘around 700,000’ for a few reasons. First, our baseline estimates for May, June and July are 696,000, 1,002,000 and 839,000, respectively. Second, JobKeeper is likely to have had positive second-round effects on employment, by supporting incomes. Our approach does not capture these general equilibrium effects. In saying that, we cannot rule out the possibility that we have overstated the aggregate effects of JobKeeper on employment; for instance, if the employment effects were smaller for permanent employees than for casuals (see Section 8.3 below) or if our estimates are biased upwards for reasons discussed in Section 7.2.

8.2 Cost per Relationship Saved

The first phase of JobKeeper provided $70 billion in support over a six-month period (30 March to 27 September). If we combine this with our estimate of the effect of the program on employment – and if we assume that the effects we estimated for April to July were similar in August and September – it suggests each employee-employer relationship saved by JobKeeper cost $100,000 (= $70b ÷ 700,000) over the six-month period. This simple measure of the cost-effectiveness of JobKeeper appears to compare favourably to similar programs in other countries, such as the PPP in the United States which has an estimated cost-per-job saved of US$224,000 (Autor et al 2020). This may reflect that the JobKeeper scheme was more tightly targeted than the PPP (Hamilton 2020).

However, there are several differences between JobKeeper and the PPP that make comparisons difficult (see Table A1 and Hamilton (2020) for a summary of these differences). In particular, the JobKeeper funds were dispensed to firms reasonably uniformly over a six-month period. In contrast, PPP funds were provided to firms upfront (as a forgivable loan) and firms had some discretion over how quickly to dispense those funds to payrolls over time, which means the duration of the PPP is less clear.[43] While this makes it hard to adjust the cost-per-job-saved metrics for differences in program duration (e.g. by comparing the monthly-cost-per-job saved of the programs), this adjustment would likely tilt the comparison more strongly in favour of JobKeeper. This is because funds appear to be less frontloaded under JobKeeper than under the PPP.

However, any cost-benefit analysis of JobKeeper is well beyond the scope of our paper. We leave that analysis for researchers and analysts with expertise in that area.

8.3 Casual versus Permanent Workers

A key assumption behind our estimates of the aggregate effects of JobKeeper is that the treatment effects we estimate for casuals with 6–23 months tenure can generalise to other JobKeeper recipients.

Our treatment effect estimates represent local treatment effects around the tenure-eligibility threshold. It is possible that JobKeeper had a different effect on casuals away from the tenure threshold. For example, longer-tenured casuals (with, say, more than two years of tenure) are likely to have accumulated more firm-specific human capital on average than their shorter-tenure colleagues and thus may have been less likely to lose their job in the absence of JobKeeper. In this case, our estimates of the aggregate effect of JobKeeper would be overstated, all else being equal.

Whether our treatment effect estimates can generalise to permanent employees is even more uncertain. In a casual employment relationship, an employee does not have guaranteed hours of work, and the relationship can be ended without notice (FWO 2020a). In a permanent relationship, an employee has an advance commitment from their employer about hours of work and length of service, and are generally entitled to notice before termination. Unlike permanent employees, casual employees are also generally not entitled to paid annual and sick leave from their employer.[44]

Whether the employment outcomes of permanent employees responded differently to casual employees to receiving JobKeeper is a priori unclear. On the one hand, the higher firing costs associated with permanent employment (relative to casual work) may have meant that permanent employees on JobKeeper were less likely to be dismissed in the absence of the program.[45] In that case, our estimates would overstate the effects of JobKeeper on aggregate employment. However, we provide evidence in Appendix D suggesting that firing costs (specifically, redundancy payments) had no discernible effect on employment outcomes during the initial months of the COVID-19 crisis. Employment of permanent workers may also have responded less than casuals to JobKeeper in view of the fact that the $1,500 fortnightly payment represented a larger fraction of average pre-scheme earnings for casual workers than for permanent workers (i.e. a higher replacement rate), reflecting the lower average pre-scheme earnings of casual employees.[46]

On the other hand, the temporary changes to the Fair Work Act 2009 to provide firms with more flexibility to modify employees' working arrangements may have had a larger employment-preserving effect on permanent staff than casuals. As discussed earlier, these changes meant that an employee covered by JobKeeper could have their hours reduced, or be redeployed, at their employer's discretion. This flexibility was already a feature of most casual arrangements, but not permanent ones. As such, the JobKeeper Payment program – broadly defined to include both the subsidy and the flexibility provisions – may have had a larger effect on employment of permanent workers than casuals.[47] Teasing out the separate effects of the wage subsidy and the flexibility provisions is an avenue for future work.

While our main identification strategy is restricted to casual employees, our alternative strategy based on the residency requirement captures the effects of JobKeeper on both casual and permanent employees. Using this alternative approach, we can perform a test of the hypothesis of constant treatment effects across casual and permanent employees (see Appendix E for details). We do not reject the hypothesis of equal treatment effects across groups at conventional levels of significance. While this suggests that the assumption of equal treatment effects across casual and permanent employees may be reasonable, this test suffered from low power due to small sample sizes.

Our approach to inferring aggregate effects also generalises our treatment effect estimates to non-employees. Under JobKeeper, self-employed people could receive the $1,500 payment as a ‘business participant’ if they were an eligible sole trader, partner, beneficiary of a trust, or were actively engaged in an eligible entity as a shareholder or director. In this situation eligibility was based on the firm-eligibility test and some other criteria. Non-employing businesses made up around 11 per cent of all individual JobKeeper recipients in April (Treasury 2020b). By extrapolating our treatment effect estimates from Section 6.2 to the self-employed, we are implicitly assuming that one-fifth of all self-employed JobKeeper recipients would have exited employment in the absence of JobKeeper. We cannot test this assumption directly, so we leave it as a caveat and avenue for future research.


The confidence intervals in Figure 1 reflect the confidence intervals on our estimates of the effect of worker eligibility and do not account for the uncertainty related to our estimate of the take-up rate discussed in Section 6.2. [40]

Treasury estimated the unemployment rate would peak at 10 per cent with JobKeeper and 15 per cent without JobKeeper (Frydenberg 2020). This ex ante estimate was not affected by the revelation of a reporting error in estimates of the number of employees likely to access the program (and associated budget costing revisions) announced in May (Treasury and ATO 2020). [41]

The implied amount of employment saved by Treasury's estimate will be larger than 700,000 if some of those who exit employment are assumed to leave the labour force rather than becoming unemployed. [42]

The PPP funds could fully cover a firm's pre-COVID payroll expenses for 10 weeks, or one-quarter of their pre-COVID payroll expenses for 24 weeks (or anywhere in between). [43]

In most awards, casual employees are required to be paid an hourly wage premium, which helps to at least partly compensate for the loss of other benefits. [44]

The choice of employment relationship is also endogenous to the value of the worker-firm match. Casual and permanent employees may also have different levels of productivity, firm-specific human capital and wages. [45]

Data from the HILDA Survey suggests that 83 per cent of casuals with at least 12 months of job tenure who were working in the industries most adversely affected by COVID-19 (namely store-based retailing excluding food & fuel, arts & recreation, accommodation & food services, and other services) would have had their pre-scheme earnings more than fully covered by JobKeeper (i.e. a replacement ratio equal to 1 or more), compared to only 31 per cent of non-casual employees. This calculation assumes all employees received wage increases of 3 per cent per year between late 2017 and late 2019. [46]

For a discussion of the role of workplace-level flexibility in how the labour market adjusts to shocks, see Bishop et al (2016). [47]