Table 8 Heterogeneity analysis.

From: Leaving messages as coproduction: impact of government COVID-19 non-pharmaceutical interventions on citizens’ online participation in China

 

Online participation

 

Number of messages

Logarithm of the number of messages

Economic conditions (High)

(Obs. = 46,848)

0.467**

0.327**

0.115**

0.102**

(0.196)

(0.164)

(0.046)

(0.046)

Economic conditions (Low)

(Obs. = 71,370)

0.040

−0.028

0.017

0.005

(0.124)

(0.108)

(0.035)

(0.032)

Telecommunication foundation (High)

(Obs. = 47,946)

0.294*

0.144

0.072**

0.055*

(0.174)

(0.121)

(0.034)

(0.032)

Telecommunication foundation (Low)

(Obs. = 67,344)

0.134

0.005

0.037

0.013

(0.141)

(0.125)

(0.040)

(0.038)

Education level of residents (High)

(Obs. = 43,554)

0.563***

0.409***

0.131***

0.115***

(0.190)

(0.145)

(0.040)

(0.039)

Education level of residents (Low)

(Obs. = 66,978)

−0.034

−0.132

−0.007

−0.025

(0.130)

(0.114)

(0.037)

(0.034)

Local Covid-19 severity variables

N

Y

N

Y

City-fixed effects

Y

Y

Y

Y

Date-fixed effects

Y

Y

Y

Y

  1. Each cell represents one separate regression using the corresponding subsample. Standard errors are clustered at the city level and are reported below the coefficients.
  2. ***p < 0.01; **p < 0.05; *p < 0.1.
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