Table 1.

Effect of violation of lockdown norms on daily positive cases.

Italy, 17 March 2020- 20 April 2020.

(a) OLS Log(p)(b) NBR p
Sanction_rate(-6)0.046*** (0.016)0.045*** (0.013)
time0.021** (0.009)0.021*** (0.008)
time2-0.001*** (0.000)-0.001*** (0.000)
Day of the week  
Monday-0.045 (0.060)-0.044 (0.049)
Tuesday-0.176** (0.070)-0.176*** (0.058)
Wednesday-0.211*** (0.066)-0.205*** (0.055)
Thursday-0.146** (0.053)-0.141*** (0.044)
FridayRefref
Saturday-0.041 (0.053)-0.040 (0.044)
Sunday-0.034 (0.065)-0.032 (0.053)
n_test0.000 (0.000)0.000* (0.000)
_cons8.228*** (0.126)8.232*** (0.106)
Over-dispersion parameter -5.451*** (0.253)
N3535
R2/ McFadden’s Pseudo R20.900.156
Breusch Godfrey 1° order autocorrelation testChi2: 0.616;p-value: 0.43
Breusch Pagan testChi2: 1.43;p-value: 0.23
Shapiro-Wilk Normality testW: 0.958;p-value: 0.207
Over dispersion testChi2: 649.83;p-value: 0.000
OLS - ordinary least squares, NBR - negative binomial regression
Standard errors in parentheses
* p < 0.10, ** p < 0.05, *** p < 0.01
Note: n_test is the number of COVID-19 tests carried out each day._const is the constant of the linear model. time and time2 capture the quadratic trend in the evolution of contagions. Sanction_rate(-6) is the the ratio between the daily number of fines for the violation of lockdown norms and the number of checks carried out by the Italian Police. This variable is measured six days before the number of contagions.

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