. 2023 Jan 10;81:102330. doi: 10.1016/j.labeco.2023.102330

Table 2.

Unemployment, mobility and IT: Individual-level regressions.

	Dependent variable: Unemployed
	(1)	(2)	(3)	(4)
$Δ$ Mobility	–0.181***	–0.239***	–0.742	0.0236
	(0.031)	(0.037)	(1.559)	(1.358)
IT	–0.00697	0.0187***	0.0193**	0.0292***
	(0.005)	(0.007)	(0.009)	(0.011)
$Δ$ Mobility $\times$ IT		0.0699***	0.0656**	0.0677***
		(0.023)	(0.032)	(0.025)

R-squared	0.00346	0.00418	0.0293	0.0384
N	71,812	71,812	71,812	71,812
Controls	No	No	Yes	Yes
State FEs	No	No	No	Yes

Results of estimating Eq. 4:

$\begin{matrix} U n e m p l o y e d_{i, t} = α + β_{1} Δ M o b i l i t y_{m s a (i), t} + β_{2} I T_{m s a (i)} + β_{3} Δ M o b i l i t y_{m s a (i, t)} * I T_{m s a (i)} \\ + Z_{i}^{'} δ + X_{m s a (i)}^{'} σ + {(X_{m s a (i)} * M o b i l i t y_{m s a (i), t})}^{'} γ + + α_{s (i)} + ϵ_{i, t} \end{matrix}$

where $U n e m p l o y e d_{i, t}$ is a dummy that equals one if the individual is unemployed in month $t$ , where t (April/May 2020) and zero otherwise. $Δ M o b i l i t y_{m s a (i), t}$ is the change in mobility in the MSA where the individual lives and $I T_{m s a (i)}$ is the level of IT adoption in the MSA where individual i lives. $Z_{i}$ are individual level controls. $X_{m s a (i)}$ are MSA-level controls, including the level and the interaction between mobility and GDP per capita, the share of minorities, the share of people with a three year Bachelor’s degree, and the unemployment rate in February 2020. $α_{s (i)}$ are state fixed effects. Standard errors are clustered at the MSA level. The regressions are weighted by the assigned weight of the respondent. * $p < 0.1$ , ** $p < 0.05$ , *** $p < 0.01$ . See Section 3 and Section 5 for more details.