Table 7.

Protest effect on post-protest death growth.

	Death Growtht = 1 + Death Growtht = 2 (per 00,000′) (6/16–7/27, 2020)
	Reduced Form	2SLS	2SLS	2SLS
	(1)	(2)	(3)	(4)
log(Protest Turnout per 00,000′)		2.41**
		(2.04)
log(Protest Turnout)			1.21**
			(2.14)
BLM Protest				0.05***
				(2.97)
log(RainfallBLM)	−0.28**
	(-2.10)
Control variables:
Lagged Case Growth	✓	✓	✓	✓
Median outdoor minutes	✓	✓	✓	✓
Reopening Phase (standard)	✓	✓	✓	✓
Demographics	✓	✓	✓	✓
Weather Condition	✓	✓	✓	✓
State FE	✓	✓	✓	✓
First Stage Diagnostics:
Cragg-Donald Wald F		31.85	69.88	622.39
Kleibergen-Paap Wald Rk F		15.01	34.08	12.64
R2	0.65
Obs.	3101	3101	3101	3101

Note: The table shows the Instrumental Variable (IV) regression results on COVID-19 death growth per 100,000 population in the six-week window post BLM protests (6/16–7/27, 2020). Column (1) is the reduced form regression, which shows the effect of rainfall on case growth. Columns (2)–(4) report the results of two-stage-least-squares (2SLS) regressions of case growth on the three different BLM protest measures. We winsorize i) death growth per 100,000 population, ii) BLM protest turnouts per 100,000 population, and iii) rainfall level at 5% to limit the influence from extreme values. All regressions are weighted by county population, and control for state fixed effects. Standard errors are clustered at the state level. t-stats are shown in parentheses. ∗, ∗∗, ∗∗∗ indicates the observed coefficient is statistically significant at the 90%, 95%, and 99% confidence intervals, respectively.