On the measurement of tasks: does expert data get it right?

Journal for Labour Market Research

Table 10 Task regressions: robustness

Dependent Variable: \(T_{ij}\)	(1)	(2)	(3)	(4)	(5)	(6)	(7)
Abstract (Exp., Occ.)	0.35***	0.36***	0.37***	0.19***	0.38***	0.22***	0.39***
Abstract (Exp., Occ.)	(0.01)	(0.01)	(0.01)	(0.00)	(0.01)	(0.00)	(0.01)
Routine (Exp., Occ.)	0.30***	0.32***	0.29***	0.16***	0.31***	0.21***	0.33***
Routine (Exp., Occ.)	(0.01)	(0.01)	(0.01)	(0.00)	(0.01)	(0.01)	(0.01)
Manual (Exp.)	0.37***	0.41***	0.39***	0.26***	0.40***	0.33***	0.42***
Manual (Exp.)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)	(0.01)
Wage/hr ≥ 5 & Empl. Hours ≥15	\(\checkmark\)
Observations per Occupation \(\ge 100\)		\(\checkmark\)
Occupational Classification: 2-digit			\(\checkmark\)
Activities performed “often” OR “sometimes”				\(\checkmark\)
Task Construction: Exclude competencies					\(\checkmark\)
Task Normalization a la Alda (2013)						\(\checkmark\)
2012 Sample Only							\(\checkmark\)
Expert tasks (Occupational)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)	\(\checkmark\)
Adj. \(R^{2}\)	0.25	0.34	0.30	0.35	0.30	0.39	0.24
Observations	26641	25468	27777	28026	27069	28015	13756

Robust standard errors in parentheses
* \(p<0.10\), ** \(p<0.05\), *** \(p<0.01\)
This output displays robustness estimates on the task pass-through, conceptually derived from (5) and estimated via (9). Recall that this model regresses individual-level tasks on occupation-level tasks. The first two rows display coefficients based on occupational averages derived from individual responses in the employment surveys (“(Occ.)”). Point estimates corresponding to those individual responses are displayed in the third and fourth row (“(Ind.)”). Lastly, the last two rows display coefficients based on occupational averages derived from the Expert database (“(Exp.)”). All specifications include controls for gender, age, age squared, a dummy for living in an urban area, education dummies, occupational tenure, firm tenure, squared tenure for each dimension of experience, and a categorical variable reflecting firm size. Each regression is weighted by the product of sample weight and occupation-specific workforce to account for size effects. The omitted task category is “Manual”. I use BIBB/BAuA data that has been collected in 2011–12 and 2017–18, and data from BERUFENET, covering the years 2011–13. For the BIBB/BAuA data, see Hall et al. (2020b) and (Hall et al. (2020a), respectively. For the BERUFENET data, see Dengler et al. (2014)