Table 2 Fractional response model—Probit.

From: On the determinants of anti-COVID restriction and anti-vaccine movements: the case of IoApro in Italy

 

(2.1)

(2.2)

(2.3)

Businesses pc

Businesses pc

Businesses pc

ShPop 20–30

 − 2.271

 − 0.814

1.178

(− 0.74)

(− 0.26)

(0.35)

ShPop 30–40

 − 5.098

 − 5.194

 − 3.467

(− 1.37)

(− 1.41)

(− 0.83)

ShPop 40–50

6.957**

7.337**

5.941*

(2.33)

(2.45)

(1.78)

ShPop 50–60

3.554

4.119

6.833*

(1.02)

(1.11)

(1.67)

Income

 −1.846***

 − 2.006***

 − 2.509***

(− 2.67)

(− 2.72)

(− 2.82)

Income sqr

0.426**

0.493***

0.601***

(2.44)

(2.65)

(2.66)

Rel.Inc.Dec

 − 0.0204***

 − 0.0229***

 − 0.0185***

(− 3.45)

(− 3.69)

(− 2.74)

Sh.Under30k

 

 − 0.0279

 − 0.0121

 

(− 0.39)

(− 0.13)

PopDens

 

 − 0.0000712*

 − 0.0000232

 

(− 1.84)

(− 0.38)

Tot.Cases ph

 

 − 0.00000997

 − 0.0000117

 

(− 1.29)

(− 1.40)

Corr-IQI

  

0.482**

  

(2.51)

Gov-IQI

  

0.0679

  

(0.62)

RQ-IQI

  

0.121

  

(1.32)

RoL-IQI

  

0.0277

  

(0.23)

Voice-IQI

  

 − 0.243

  

(− 1.19)

Constant

 − 2.981***

 − 3.083***

 − 3.549***

(− 2.75)

(− 2.87)

(− 2.76)

Observations

107

107

106

Ps.R sqr

0.00400

0.00438

0.00591

Log-likelihood

 − 0.0173

 − 0.0173

 − 0.0171

Akaike’s criterion

16.03

22.03

32.03

Schwarz’s Bayesian information

37.42

51.44

74.65

  1. t statistics in parentheses.
  2. *p < 0.1, **p < 0.05, ***p < 0.01.