Table 4.

Robustness check: respondents’ self-selection

	(1)	(2)
	OLS	OLS weighted
C1: Dig. increases the time pressure at work	$-$ 0.0776***	$-$ 0.0735***
	(0.0139)	(0.0152)
C2: Dig. puts my job at risk	$-$ 0.0343**	$-$ 0.0202
	(0.0148)	(0.0161)
C3: Dig. worsens the work–life balance	$-$ 0.102***	$-$ 0.114***
	(0.0148)	(0.0163)
C4: Dig. leads to a smooth transition between working hours and leisure time	0.00174	0.00265
	(0.0137)	(0.0150)
C5: Dig. makes my work more interesting	0.155***	0.159***
	(0.0171)	(0.0189)
C6: Dig. reduces the proportion of repetitive tasks	0.0193	0.0173
	(0.0136)	(0.0145)
C7: Dig. increases my productivity	0.255***	0.243***
	(0.0179)	(0.0193)
C8: Dig. increases my autonomy at work	0.0380**	0.0424**
	(0.0164)	(0.0178)
C9: Dig. enables more flexible forms of working time	0.0269**	0.0319**
	(0.0122)	(0.0130)
C10: Dig. simplifies interaction with colleagues and superiors	0.0548***	0.0621***
	(0.0148)	(0.0156)
How strongly Dig. affect the work over the last year?	0.112***	0.113***
	(0.0134)	(0.0146)
Controls	Yes	Yes
(N )	3089	3089
($R^2$)	0.379	0.378

This table reports the results of the OLS regression having as dependent variable the effect of digitalization on job satisfaction, which is measured on a five point Likert scale (1 = “less satisfied”, 3 = “no change”, 5 = “more satisfied”). Robust standard errors in parentheses. *$p<0.10$, **$p<0.05$, ***$p<0.01$. Worker characteristics is a vector of control variables as described in Table 1. Column (1) reports the baseline estimation as in Table 2, while column (2) reports a weighted estimation that accounts for the distribution of gender and field in the population of PET graduates