Table 5.

Effect of heterogeneity in firms for general health screening

	(1)	(2)
Panel A: gender
	Women	Men
Female peers	0.049*** (0.011)	0.004 (0.006)
Male peers	0.017 (0.010)	0.023* (0.010)
Panel B: job type
	Blue-collar workers	White-collar workers
Blue-collar peers	0.035** (0.011)	0.007 (0.010)
White-collar peers	0.013 (0.007)	0.043** (0.013)
Panel C: age
	Young workers	Old workers
Young peers	0.028** (0.009)	0.039** (0.014)
Old peers	0.026*** (0.007)	0.035** (0.012)

This table summarizes the effect heterogeneity in firms according to worker characteristics. Panel A shows the effect of female and male peers on women and men, panel B differentiates between blue-collar and white-collar jobs, and panel C separates the young and old workers (below and above 40 years of age). All regressions control for past healthcare utilization (screening participation, outpatient expenditure, days in hospital), wage, age, place of residence, job type, business sector, firm location, firm size, and year of job move. Standard errors clustered at the firm level are shown in parentheses, *$p<0.05$, **$p<0.01$, and ***$p<0.001$