The distribution of the gender wage gap in Austria: evidence from matched employer-employee data and tax records

Journal for Labour Market Research

Table 3 Decompositions of the wage differences

	(1)	(2)	(3)	(4)
Reimers (1983) decomposition
Differences in returns, \(\Delta\hat{\beta}\) in % of the raw gap (19.0 %)	0.211	0.181	0.169	0.121
		85.8	80.1	57.3
Differences in observed characteristics, ΔX in % of the raw gap (19.0 %)		0.030	0.042	0.109
		14.2	19.9	42.7
Cotton (1988) decomposition
Differences in returns, \(\Delta\hat{\beta}\) in % of the raw gap (19.0 %)	0.211	0.176	0.158	0.111
		83.4	74.9	52.6
Differences in observed characteristics, ΔX in % of the raw gap (19.0 %)		0.035	0.053	0.100
		16.6	25.1	47.4
Education, experience, interruptions, family status, citizenship, region, density		x	x	x
Worker status, occupation, industry			x	x
Establishment size, firm characteristics, hierarchy				x
Number of observations	17,762	17,762	17,762	17,762

Note: Blinder-Oaxaca decompositions. 6,064 women and 11,698 men in private and public sector employment. Full-time employees only. For the decomposition three specifications based on specification 1 as depicted in Table 2 are used: In column (2), the independent variables are education, experience, experience squared, tenure, tenure squared, interruptions, interruptions squared, family status, citizenship, dummy variables for regions and population density. In column (3), we add dummy variables for worker status, occupation and industry and in column (4), we add dummy variables for establishment size, logarithm of firm size, average age of workers in the firm, ratio female to male workers in the firm, worker turnover in the firm and a dummy variable for a leading position