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Last month, we did some work at @DPRU_UCT on the economics of #COVID19 in SA. We focused on several areas of concern, incl. the grants system, expected impacts on growth + employment, gov relief measures, and a tool to guide lockdown transition policy. Link below!
Grateful to be involved. Link to full WP here: http://www.dpru.uct.ac.za/sites/default/files/image_tool/images/36/Publications/Working_Papers/DPRU%20WP202004.pdf
As promised to a few friends, here are some highlights:
We begin with the macroeconomy. SA entered the COVID-19 period on the back of a recession in the last half of 2019. April forecasts suggest GDP in 2020 will
by 5.8-9.5%: much larger than the 2009 GFC of 1.5%. (1/n)
We begin with the macroeconomy. SA entered the COVID-19 period on the back of a recession in the last half of 2019. April forecasts suggest GDP in 2020 will
by 5.8-9.5%: much larger than the 2009 GFC of 1.5%. (1/n)
Considering such large growth effects, how might employment respond? We'll have a better idea with the NIDS-CRAM data coming soon, but preliminary (unweighted) data suggest expected reductions in every industry. Forecasts vary: HSBC suggest U% rising to 33%, IMF to 35%...(2/n)
growth effects, how might employment respond? We'll have a better idea with the NIDS-CRAM data coming soon, but preliminary (unweighted) data suggest expected reductions in every industry. Forecasts vary: HSBC suggest U% rising to 33%, IMF to 35%...(2/n)
We consider the gov's fiscal response. At the time of writing, SA's fiscal stimulus package was higher than the COVID-related spending of any other developing country, and even exceeds the spending of some advanced economies. Much is preliminary however (eg COVID grant)... (3/n)
Next, we provide an overview of gov interventions to examine coverage. Additional measures announced in the last few weeks are not included, but the story remains: broad range for the formal sector, some relief for vulnerable HH's; we're concerned about the informal sector. (4/n)
Unweighted survey data suggests TERS is the most utilised intervention by formal sector firms, no matter the industry (but still significant variation). (5/n)
We examine changes to social grants. The disparity between the proposed CSG top-up (great work by @ihsaanbassier et al) & the DSD's policy was unexpected: explained by the intro of the COVID grant? Not means-tested, so coverage is relatively even across the income dist... (6/n)
... with over 3mil eligible for this grant in deciles 8, 9 and 10 (note however that per capita HH income for D8 is only +- R4 100). Assuming the eligibility criteria and 60% uptake, there are over 12mil eligible individuals. How does this compare to previous proposals? (7/n)
We compare 3 diff scenarios: (1) the current policy ("Grants plus") (2) CSG+R500 proposal ("CSG boost") & (3) the current policy if the COVID grant is excl ("Grants only").
(1) Slightly less progressive than (2) but # HH's = larger
(2) Most spending goes to poorest HHs... (8/n)
(1) Slightly less progressive than (2) but # HH's = larger
(2) Most spending goes to poorest HHs... (8/n)
... (3) Least progressive, largely due to OAP reaching middle deciles. So the current policy is less progressive than the CSG+R500 proposal AND it costs more. The benefit, however, is that it reaches more households that do not have a CSG recipient, analysed more in the WP (9/n)
Finally, using data from O*NET, PALMS + more we develop a physical interaction index which measures one key aspect of COVID transmission risk which might help guide lockdown policy. We then analyse how industries vary by index score, work-from-home ability, and more... (10/n)
Most SA employment (58.6%) is in quadrant 4, i.e. low ability to work-from-home + high physical interaction at work. Most of this is also not considered 'essential'. Geographically, risk is unevenly distributed: highest in EC and KZN. More work needed on this however... (11/n)
How might lockdown affect workers across the wage distribution? Below reveals an interesting, non-linear inverse-U relation between our index + wages (turning point around R100 p/hr), at least on the industry-level. Low + high wage earners have levels of risk < median. (12/n)
(N/n) There's a bit more to it, and more work needs to be done, but I'm stopping now because this thread has reached quite a length. Thanks for coming to my TEDtalk!
