Table 6.

Effect of neighboring new COVID-19 cases on domestic new COVID-19 cases

	OLS	OLS	IV	IV
	(1)	(2)	(3)	(4)
	New COVID-19 Cases	New COVID-19 Cases	New COVID-19 Cases	New COVID-19 Cases
Vaccinated persons, 1 dose	− 0.000973***	− 0.000866***	− 0.000325	− 0.000183
	(0.000)	(0.000)	(0.000)	(0.000)
Vaccinated persons, 2 doses		− 0.000285		− 0.000199
		(0.000)		(0.000)
Neighbor cases (7 days lag)	0.566195***	0.572086***	0.638675*	0.680740**
	(0.204)	(0.203)	(0.364)	(0.325)
Containment measures index (lag)	− 0.010388	− 0.011402	− 0.001193	− 0.001202
	(0.008)	(0.008)	(0.002)	(0.003)
COVID-19 cases (lag)	− 0.000113	0.000155	0.000579	− 0.000085
	(0.003)	(0.003)	(0.006)	(0.005)
Mobility (lag)	0.000098***	0.000103***	0.000018	0.000022
	(0.000)	(0.000)	(0.000)	(0.000)
Observations	13,241	13,154	13,241	13,154
R-squared	0.639	0.640	0.136	0.138
Health Policy Controls	Yes	Yes	Yes	Yes
Country FE	Yes	Yes	Yes	Yes
Time FE	Yes	Yes	Yes	Yes
Kleibergen-Paap rk Wald F statistic			45.025	11.175
No. of countries	123	123	123	123
Vaccination 1 Lags	21 days	21 days	21 days	21 days
Vaccination 2 Lags	7 days	7 days	7 days	7 days

Table reports results for Eq. (7). The dependent variable is new COVID-19 cases. A spillover term “Neighbor cases” (lag 7 days) is introduced to the equation to capture the effects of neighboring COVID-19 new cases on a country’s own caseload using bilateral distance weights (Eq. 6). The regressions control for stringency of containment measures, other non-pharmaceutical interventions and health policy controls (21 lags), lags of mobility (21 lags), lagged new cases, country-specific time trends, as well as country and time fixed-effects. Standard errors are clustered at the country level

***, **, and * represent statistical significance at 1%, 5%, and 10%, respectively