Is innovative firm behavior correlated with age and gender composition of the workforce? Evidence from a new type of data for German enterprises

Journal for Labour Market Research

Table 2 Fractional logit regressions for the proportion of R&D outlays in total revenues

Explanatory variables	(1) Coefficient	(2) Standard error	(3) p-value	(4) Average marginal effect	(5) Marginal effect at means	(6) Elasticity at means
Employees 30–49 years (%)	−0.001691	0.005566	0.7610	−0.000018	−0.000009	−0.0968
Employees 50 years or older (%)	−0.019652	0.004867	<0.0001	−0.000210	−0.000101	−0.4937
Female employees (%)	0.009466	0.001966	<0.0001	0.000101	0.000049	0.2837
Medium qualified employees (%)	0.006972	0.001974	<0.0001	0.000074	0.000036	0.4267
Highly qualified employees (%)	0.052009	0.003691	<0.0001	0.000555	0.000267	0.3118
Part-time employees (%)	−0.014284	0.003293	<0.0001	−0.000152	−0.000073	−0.2584
Firm size (number of employees)	0.000051	0.000020	0.0110	5.42e-07	2.61e-07	0.0217
Firm size (squared)	−3.74e-10	2.17e-10	0.0850	−3.99e-12	−1.92e-12	−0.0050
Constant	−8.205332	0.942781	<0.0001
Pseudo R ² (McFadden)	0.1403

Note: Fractional logit regressions for proportion of R&D outlays in total revenues. All models include dummy variables for years and 2digit-level industries. Robust standard errors for coefficients clustered at the firm level. The data are from a balanced panel (4 years from 2003 to 2006) with a total of 16,900 yearly observations for 4,225 enterprises