Table D.2.

Difference-in-differences regression for U.K. and U.S. ETFs (narrowing on March 17, 2020) .

	Quoted spread	Effective spread	Realized spread	Price impact
U.K.	40.82${}^{\mathrm{\ast \ast \ast }}$	12.98${}^{\mathrm{\ast \ast \ast }}$	8.24${}^{\mathrm{\ast \ast \ast }}$	4.30${}^{\mathrm{\ast \ast \ast }}$
	(9.67)	(2.67)	(1.94)	(1.09)
Margin narrowing	−2.08	0.03	0.18	−0.13
	(7.34)	(2.03)	(1.47)	(0.83)
U.K. × Margin narrowing	−27.66${}^{\mathrm{\ast \ast }}$	−7.54${}^{\mathrm{\ast \ast }}$	−5.67${}^{\mathrm{\ast \ast \ast }}$	−1.48
	(9.72)	(2.69)	(1.95)	(1.09)
Volatility	−251.67	22.29	−26.64	51.31
	(377.95)	(104.51)	(75.69)	(42.53)
Return	−122.17	−21.80	−12.09	−7.71
	(161.29)	(44.60)	(32.30)	(18.15)
Constant	9.95	−0.20	0.59	−0.79
	(14.11)	(3.90)	(2.83)	(1.59)
Observations	24	24	24	24
${\overline{\text{R}}}^2$	0.65	0.67	0.62	0.56

The table reports the changes to liquidity measures around the narrowing of the margin differential for the CSPX.L (U.K.) and SPY (U.S.), which are ETFs that track the performance of the S&P 500, traded on the LSE and NYSE, respectively. Specifically, we report the results for the following difference-in-differences regression:

${Liquidity}_{i,t}={\alpha }_0+{\beta }_1{UK}_{i,t}+{\beta }_2{Marginnarrowing}_t+{\beta }_3{UK}_{i,t}\times {Marginnarrowing}_t+{Volatility}_{i,t}+{Return}_{i,t}+{\varepsilon }_{i,t}$,

where ${Liquidity}_{i,t}$ is one of the following liquidity variables: Quoted spread, Effective spread, Realized spread or Price impact for the U.S. or U.K. ETF, $i$. The dependent variables are calculated over one hour intervals, and are expressed in basis points. ${UK}_{i,t}$ is an indicator variable equal to 1 if the ETF trades in the U.K., and 0 otherwise. Margin narrowing is an indicator variable equal to 1 for the period March 17 to March 18, 2020 and 0 for the period March 15 to March 16, 2020. $Volatilit{y}_{i,t}$ and $Retur{n}_{i,t}$ are based on the FTSE 100 and S&P 500 index levels for the U.K. and U.S. markets, respectively. $Volatilit{y}_{i,t}$ and $Retur{n}_{i,t}$ are calculated over one-hour intervals as $log({HighPrice}_{i,t}/{LowPrice}_{i,t})$ and $log({ClosePrice}_{i,t}/{OpenPrice}_{i,t})$, respectively. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively.