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Table 12 Result of spatial panel data analysis for the association between emergency statement and mobility for the prefectures in Japan, using divided emergency statement for 2020 and 2021

From: COVID-19, stigma, and habituation: evidence from mobility data

dependent

explanatory

estimate

s.e.

p

covariates

retail

emergency_1st

-0.0078

0.0011

<0.0001

Yes

emergency_2nd

-0.0051

0.0010

<0.0001

emergency_3rd

-0.0058

0.0013

<0.0001

emergency_4th

-0.0013

0.0021

0.5480

\(\rho\)

0.9951

0.0005

<0.0001

\(\psi\)

0.8740

0.0021

<0.0001

grocery

emergency_1st

-0.0040

0.0009

<0.0001

Yes

emergency_2nd

-0.0011

0.0008

0.1612

emergency_3rd

0.0001

0.0010

0.8886

emergency_4th

-0.0004

0.0017

0.8341

\(\rho\)

0.9900

0.0008

<0.0001

\(\psi\)

0.8440

0.0025

<0.0001

workplaces

emergency_1st

-0.0057

0.0008

<0.0001

Yes

emergency_2nd

-0.0038

0.0006

<0.0001

emergency_3rd

-0.0012

0.0008

0.1518

emergency_4th

-0.0039

0.0014

0.0048

\(\rho\)

0.9943

0.0006

<0.0001

\(\psi\)

0.9630

0.0007

<0.0001

residential

emergency_1st

0.0025

0.0004

<0.0001

Yes

emergency_2nd

0.0017

0.0003

<0.0001

emergency_3rd

0.0007

0.0004

0.0516

emergency_4th

0.0019

0.0006

0.0025

\(\rho\)

0.9930

0.0007

<0.0001

\(\psi\)

0.9344

0.0012

<0.0001

  1. Notes: The sample size is \(N = nT = 47 \times 518 = 24,346\). The estimation results for each row show the coefficients estimated using model (17). s.e. stands for cluster robust standard errors. The values corresponding to \(\rho\) and \(\psi\) represent the spatial and temporal autocorrelation coefficients, respectively