Table 5 OLS estimates of labour market...

Table 5

OLS estimates of labour market concentration on No. skills, experience and education, separated by occupation-skill level

	No competencies per ad		Experience		Graduate
	Low	High	Low	High	Low	High
log(HHI)	−0.0118	0.1214***	−0.0414***	−0.0601***	0.0047***	0.0076***
	(0.0078)	(0.0193)	(0.0093)	(0.0114)	(0.0008)	(0.0013)
Year FE	✓	✓	✓	✓	✓	✓
Prov. FE	✓	✓	✓	✓	✓	✓
Ind. FE	✓	✓	✓	✓	✓	✓
ISCO4 FE	✓	✓	✓	✓	✓	✓
MDV	3.409	9.643	2.655	3.287	0.111	0.378
mean(HHI*10k)	1,298	1,340	1,177	1,249	1,298	1,340
R²	0.311	0.409	0.114	0.064	0.115	0.183
N	273,788	279,239	187,282	187,839	273,788	279,239

	No competencies per ad		Experience		Graduate
	Low	High	Low	High	Low	High
log(HHI)	−0.0118	0.1214***	−0.0414***	−0.0601***	0.0047***	0.0076***
	(0.0078)	(0.0193)	(0.0093)	(0.0114)	(0.0008)	(0.0013)
Year FE	✓	✓	✓	✓	✓	✓
Prov. FE	✓	✓	✓	✓	✓	✓
Ind. FE	✓	✓	✓	✓	✓	✓
ISCO4 FE	✓	✓	✓	✓	✓	✓
MDV	3.409	9.643	2.655	3.287	0.111	0.378
mean(HHI*10k)	1,298	1,340	1,177	1,249	1,298	1,340
R²	0.311	0.409	0.114	0.064	0.115	0.183
N	273,788	279,239	187,282	187,839	273,788	279,239

Note(s): Each observation consists in a vacancy. This table reports the OLS regression outputs separated fr high and low skill occupations using as dependent variables (1) No. competencies per ad, (2) Experience and (3) Graduate which define (1) the number of competencies demanded in the vacancy, (2) the midpoint-approximation years of experience demanded and if the vacancy demands (3) at least a bachelor's degree. The independent variable is the log of the employment HHI, measured at the industry (2-digit ATECO code), province (NUTS-3) and year level. All the regressions also include occupation (ISCO 4-dig) fixed effects. Robust standard errors in parentheses ***p < 0.01, **p < 0.05, *p < 0.1

Source(s): Authors' calculation on AIDA and Wollybi data in 2015–2018 period

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