5 unemployment but, rather, dropped out of the labour force, or delayed their entry into it.” These numbers suggest that young workers were at least twice as much impacted as adult workers. However, the ILO only includes unemployment and inactivity for this analysis, not reduced hours which account for about half of the total employment loss (Fig. 7). Since the employment loss for young workers is twice the average loss in the society (8.7/4.3 = 2.0), and since the average total employment loss for the society (including reduced hours) is 8.8% globally (Fig. 5), we obtain 8.8 x 2 = 17.6% for the youth. Since we obtained 9.5% for pre-college workers, the loss for the youth is about twice the loss for the latter (17.6/9.5 = 1.9). Therefore, we assume that if unemployment among adults without college rises by _x_ youth unemployment rises by 2 _x_ .

**Duration.** Hall and Kudlyak (2021) find that recoveries from unemployment shocks tend to happen at a proportional rate. Using data from across the OECD on the rate of recovery in employment, we calculate a proportional factor such that, given an initial employment shock _x_ 0, thereafter _xt_ +1 = _xt ×_ 0 _._ 7143. We arrive at this factor by looking at data on employment to population ratios from the _OECD.Stat_ database. The employment to population ratio of the OECD, i.e. developed countries, deviated on average during 2020 from its value in the last quarter of 2019 by 2 _._ 8 percent. The average deviation over 2021 compared to the last quarter of 2019 was 2 _._ 0 a year later. Thus, we set our recovery factor equal to _xt/xt−_ 1 = 2 _._ 0 _/_ 2 _._ 8 = 0 _._ 7143.

Of course such an economy would never fully recover: even though lim _t→∞ xt_ , we would still have that _xt >_ 0 _∀t_ , so we could not speak of a date at which the recovery is complete. Having a date at which the recovery is complete is necessary to distinguish cleanly between the direct impact of the shock through loss of employment and the long run impact through lost human capital. As discussed in the text, we make an adjustment to ensure that the recovery is complete after 10 years. We choose 10 years because 0 _._ 7143<sup>10</sup> = 0 _._ 346 is very small compared to whatever the initial shock was.

We also note that Web Appx. Fig. 4(a) shows that, after the Great Recession that began in 2008, U.S. unemployment did not recover to pre-2008 levels for 10 years, whereas the employment to population ratio was still not back to its pre-2008 level even by January 2020. The Great Recession was a significant employment shock, albeit of lesser magnitude than the COVID-19 shock, so 10 years again seems reasonable.

The procedure to compute _xt_ using the recovery factor 0 _._ 7143 with a complete recovery after 10 years is as follows. First, we compute _xt_ assuming a particular initial shock and the recovery factor. Then, subtract from all the _xt_ the number 0 _._ 7143<sup>10</sup> _xt_ . <u>1</u> Finally, we multiply all the _xt_ for _t <_ 9 by 1 _−_ 0 _._ 7143<sup>10to obtain an initial shock of the original</sup> size, and set _xt_ = 0 for _t ≥_ 10. Web Appx. Fig. 4(b) shows the resulting deviations from steady state unemployment, assuming an initial shock of 10 percentage points.