Table 5.

Marginal effects of each equation of (5) for the sample of unemployed individuals with previous job experience

Variables	Channels of job search— unemployed with previous job experience
	Newspapers	Informal network	Direct contact	Internet	Agency (public or private)
Socio-demographic characteristics
Female	–	–	–	–	–
	–	–	–	–	–
Male	$0.{03}^{\ast \ast \ast }$	$0.{01}^{\ast \ast \ast }$	$0.{07}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$
	[0.02; 0.04]	[0.00; 0.02]	[0.06; 0.07]	[0.02; 0.04]	[0.02; 0.04]
Age
15–24	$-0.{03}^{\ast \ast \ast }$	$-0.{06}^{}$	$0.{06}^{\ast \ast \ast }$	$0.{13}^{\ast \ast \ast }$	$0.{00}^{}$
	$[-0.04;-0.01]$	$[-0.01;0.07]$	[0.04; 0.07]	[0.11; 0.15]	$[-0.01;0.02]$
25–34	$0.{01}^{}$	$-0.{01}^{\ast \ast \ast }$	$0.{05}^{\ast \ast \ast }$	$0.{11}^{\ast \ast \ast }$	$0.{01}^{}$
	$[-0.00;0.02]$	$[-0.02;-0.00]$	[0.04; 0.06]	[0.09; 0.12]	$[-0.01;0.02]$
35–44	–	–	–	–	–
	–	–	–	–	–
45–54	$-0.{04}^{\ast \ast \ast }$	$0.{00}^{}$	$-0.{06}^{\ast \ast \ast }$	$-0.{09}^{\ast \ast \ast }$	$-0.{01}^{}$
	$[-0.05;-0.03]$	$[-0.00;0.01]$	$[-0.07;-0.05]$	$[-0.10;-0.08]$	$[-0.02;0.00]$
55–64	$-0.{07}^{\ast \ast \ast }$	$0.{00}^{}$	$-0.{13}^{\ast \ast \ast }$	$-0.{21}^{\ast \ast \ast }$	$-0.{02}^{\ast \ast \ast }$
	$[-0.09;-0.06]$	$[-0.00;0.01]$	$[-0.14;-0.11]$	$[-0.22;-0.19]$	$[-0.04;-0.01]$
65–74	$-0.{05}^{}$	$0.{01}^{}$	$-0.{26}^{\ast \ast \ast }$	$-0.{38}^{\ast \ast \ast }$	$-0.{16}^{\ast \ast \ast }$
	$[-0.11;0.01]$	$[-0.03;0.04]$	$[-0.32;-0.20]$	$[-0.43;-0.33]$	$[-0.21;-0.11]$
Education
Primary education	$-0.{09}^{\ast \ast \ast }$	$0.{05}^{\ast \ast \ast }$	$-0.{18}^{\ast \ast \ast }$	$-0.{36}^{\ast \ast \ast }$	$-0.{08}^{\ast \ast \ast }$
	$[-0.11;-0.08]$	[0.04; 0.06]	$[-0.20;-0.17]$	$[-0.37;-0.34]$	$[-0.10;-0.06]$
Lower secondary education	$-0.{03}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$	$-0.{09}^{\ast \ast \ast }$	$-0.{18}^{\ast \ast \ast }$	$-0.{03}^{\ast \ast \ast }$
	$[-0.04;-0.02]$	[0.02; 0.03]	$[-0.10;-0.08]$	$[-0.19;-0.16]$	$[-0.04;-0.02]$
Upper secondary education	–	–	–	–	–
	–	–	–	–	–
Tertiary education	$-0.{01}^{\ast \ast }$	$-0.{06}^{\ast \ast \ast }$	$0.{07}^{\ast \ast \ast }$	$0.{11}^{\ast \ast \ast }$	$0.{00}^{}$
	$[-0.03;0.00]$	$[-0.07;-0.05]$	[0.06; 0.08]	[0.09; 0.13]	$[-0.02;0.02]$
Citizenship
Italian	–	–	–	–	–
	–	–	–	–	–
From European Union	$0.{01}^{}$	$0.{05}^{\ast \ast \ast }$	$-0.{10}^{\ast \ast \ast }$	$-0.{22}^{\ast \ast \ast }$	$-0.{08}^{\ast \ast \ast }$
	$[-0.01;0.03]$	[0.04; 0.06]	$[-0.12;-0.08]$	$[-0.24;-0.20]$	$[-0.10;-0.06]$
Extra-European Union	$0.{02}^{\ast \ast \ast }$	$0.{04}^{\ast \ast \ast }$	$-0.{10}^{\ast \ast \ast }$	$-0.{19}^{\ast \ast \ast }$	$-0.{02}^{\ast \ast \ast }$
	[0.00; 0.03]	[0.03; 0.05]	$[-0.12;-0.09]$	$[-0.20;-0.17]$	$[-0.03;-0.01]$
Marital status
Single	$0.{01}^{\ast \ast }$	$-0.{01}^{\ast }$	$0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$-0.{00}^{}$
	[0.00; 0.02]	$[-0.01;0.00]$	[0.01; 0.03]	[0.01; 0.03]	$[-0.02;0.00]$
Married	–	–	–	–	–
	–	–	–	–	–
Separated or divorced	$0.{03}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$	$0.{01}^{}$	$-0.{00}^{}$
	[0.02; 0.04]	[0.01; 0.03]	[0.02; 0.04]	$[-0.00;0.02]$	$[-0.02;0.01]$
Widowed	$0.{02}^{}$	$0.{04}^{\ast \ast \ast }$	$-0.{02}^{}$	$-0.{04}^{\ast \ast \ast }$	$-0.{03}^{}$
	$[-0.01;0.06]$	[0.02; 0.05]	$[-0.05;0.01]$	$[-0.08;-0.01]$	$[-0.06;0.01]$
Main characteristics of previous job
Sector of employment
Agriculture	$-0.{11}^{\ast \ast \ast }$	$0.{01}^{\ast }$	$-0.{03}^{\ast \ast \ast }$	$-0.{13}^{\ast \ast \ast }$	$-0.{03}^{\ast \ast \ast }$
	$[-0.14;-0.09]$	$[-0.00;0.03]$	$[-0.06;-0.01]$	$[-0.16;-0.10]$	$[-0.06;-0.01]$
Manufacturing	$0.{02}^{\ast \ast \ast }$	$-0.{02}^{\ast \ast \ast }$	$0.{06}^{\ast \ast \ast }$	$0.{06}^{\ast \ast \ast }$	$0.{08}^{\ast \ast \ast }$
	[0.01; 0.04]	$[-0.03;-0.01]$	[0.04; 0.07]	[0.05; 0.08]	[0.07; 0.10]
Construction	$-0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$	$-0.{03}^{\ast \ast \ast }$	$0.{01}^{}$
	$[-0.04;-0.00]$	[0.01; 0.03]	[0.01; 0.04]	$[-0.05;-0.01]$	$[-0.01;0.02]$
Trade	$0.{01}^{}$	$-0.{00}^{}$	$0.{04}^{\ast \ast \ast }$	$0.{06}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$
	$[-0.00;0.02]$	$[-0.01;0.01]$	[0.03; 0.06]	[0.04; 0.07]	[0.01; 0.04]
Service	–	–	–	–	–
	–	–	–	–	–
Type of employment
Employee	–	–	–	–	–
	–	–	–	–	–
Collaboration agreement	$-0.{00}^{}$	$-0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{03}^{\ast \ast }$	$-0.{03}^{\ast \ast \ast }$
	$[-0.02;0.02]$	$[-0.03;-0.01]$	[0.00; 0.04]	[0.00; 0.05]	$[-0.04;-0.01]$
Self-employed	$-0.{03}^{\ast \ast \ast }$	$0.{01}^{}$	$-0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast }$	$-0.{11}^{\ast \ast \ast }$
	$[-0.04;-0.01]$	$[-0.01;0.02]$	$[-0.04;-0.01]$	$[0.00;0.03]$	$[-0.12;-0.09]$
Occupation
Legislator, entrepreneur, manager	$-0.{04}^{}$	$0.{01}^{}$	$-0.{03}^{}$	$0.{03}^{}$	$-0.{15}^{\ast \ast \ast }$
	$[-0.08;0.01]$	$[-0.02;0.03]$	$[-0.07;0.01]$	$[-0.02;0.08]$	$[-0.19;-0.11]$
Intellectual, scientific, and high-specialisation professions	$-0.{01}^{}$	$-0.{04}^{\ast \ast \ast }$	$-0.{04}^{\ast \ast \ast }$	$0.{04}^{\ast \ast \ast }$	$-0.{10}^{\ast \ast \ast }$
	$[-0.03;0.01]$	$[-0.06;-0.03]$	$[-0.05;-0.02]$	[0.02; 0.06]	$[-0.12;-0.09]$
Technical professions	$-0.{00}^{}$	$-0.{02}^{\ast \ast \ast }$	$-0.{01}^{}$	$0.{05}^{\ast \ast \ast }$	$-0.{03}^{\ast \ast \ast }$
	$[-0.02;0.01]$	$[-0.03;-0.01]$	$[-0.03;0.00]$	[0.03; 0.06]	$[-0.04;-0.01]$
Qualified professions in commercial activities and services	–	–	–	–	–
	–	–	–	–	–
Office worker	$0.{02}^{\ast \ast \ast }$	$-0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{08}^{\ast \ast \ast }$	$0.{03}^{\ast \ast \ast }$
	[0.00; 0.03]	$[-0.03;-0.01]$	[0.00; 0.03]	[0.06; 0.10]	[0.01; 0.05]
Craftsmen, specialised workers, and farmers	$-0.{01}^{}$	$-0.{00}^{}$	$-0.{05}^{\ast \ast \ast }$	$-0.{07}^{\ast \ast \ast }$	$-0.{00}^{}$
	$[-0.03;0.01]$	$[-0.01;0.01]$	$[-0.07;-0.03]$	$[-0.08;-0.05]$	$[-0.02;0.01]$
Fixed and mobile machinery workers and vehicle drivers	$0.{00}^{}$	$0.{00}^{}$	$0.{00}^{}$	$-0.{00}^{}$	$0.{06}^{\ast \ast \ast }$
	$[-0.02;0.02]$	$[-0.01;0.02]$	$[-0.02;0.02]$	$[-0.02;0.02]$	[0.04; 0.08]
Non-qualified professions	$-0.{01}^{\ast \ast }$	$0.{00}^{}$	$-0.{06}^{\ast \ast \ast }$	$-0.{06}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$
	$[-0.03;-0.00]$	$[-0.00;0.01]$	$[-0.07;-0.05]$	$[-0.07;-0.04]$	[0.00; 0.03]
Armed forces	$-0.{01}^{}$	$-0.{15}^{\ast \ast \ast }$	$0.{05}^{}$	$0.{11}^{}$	$-0.{03}^{}$
	$[-0.13;0.13]$	$[-0.26;-0.05]$	$[-0.08;0.14]$	$[-0.03;0.23]$	$[-0.15;0.09]$
Duration of job search
From 0 to 3 months	$-0.{07}^{\ast \ast \ast }$	$-0.{03}^{\ast \ast \ast }$	$0.{01}^{\ast \ast \ast }$	$-0.{01}^{\ast \ast \ast }$	$0.{12}^{\ast \ast \ast }$
	$[-0.08;-0.05]$	$[-0.04;-0.02]$	[0.00; 0.02]	$[-0.03;-0.00]$	[0.11; 0.13]
From 4 to 6 months	$-0.{01}^{}$	$-0.{01}^{}$	$0.{04}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{07}^{\ast \ast \ast }$
	$[-0.02;0.00]$	$[-0.02;0.00]$	[0.03; 0.05]	[0.00; 0.03]	[0.05; 0.08]
From 7 to 12 months	$-0.{01}^{\ast \ast \ast }$	$-0.{01}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{02}^{\ast \ast \ast }$	$0.{05}^{\ast \ast \ast }$
	$[-0.02;-0.00]$	$[-0.02;-0.01]$	[0.01; 0.03]	[0.01; 0.03]	[0.03; 0.06]
More than 12 months	–	–	–	–	–
	–	–	–	–	–
Spatial variable
Northwest	$0.{15}^{\ast \ast \ast }$	$-0.{02}^{\ast \ast \ast }$	$0.{12}^{\ast \ast \ast }$	$0.{20}^{\ast \ast \ast }$	$0.{22}^{\ast \ast \ast }$
	[0.14; 0.16]	$[-0.03;-0.01]$	[0.11; 0.13]	[0.18; 0.21]	[0.21; 0.24]
Northeast	$0.{21}^{\ast \ast \ast }$	$-0.{04}^{\ast \ast \ast }$	$0.{12}^{\ast \ast \ast }$	$0.{21}^{\ast \ast \ast }$	$0.{29}^{\ast \ast \ast }$
	[0.19; 0.22]	$[-0.05;-0.03]$	[0.12; 0.13]	[0.19; 0.22]	[0.28; 0.30]
Centre	$0.{06}^{\ast \ast \ast }$	$-0.{04}^{\ast \ast \ast }$	$0.{05}^{\ast \ast \ast }$	$0.{09}^{\ast \ast \ast }$	$0.{13}^{\ast \ast \ast }$
	[0.05; 0.07]	$[-0.05;-0.03]$	[0.04; 0.06]	[0.07; 0.10]	[0.12; 0.14]
Southern Italy	–	–	–	–	–
	–	–	–	–	–
Main islands	$-0.{04}^{\ast \ast \ast }$	$-0.{01}^{\ast \ast }$	$0.{01}^{\ast \ast }$	$0.{03}^{\ast \ast \ast }$	$-0.{04}^{\ast \ast \ast }$
	$[-0.05;-0.02]$	$[-0.02;0.00]$	[0.00; 0.02]	[0.01; 0.04]	$[-0.06;-0.03]$
Simulated maximum likelihood—draws	150
Log likelihood	− 146,477.64
Wald ${\chi }^2$	Prob $>{\chi }^2(20,394.19)=0.00$
Observations	55,120
Sample period	2014–2018

The associated 95% CIs were computed using 10,000 coefficient vectors simulated from the posterior distribution of the estimated parameters. The associated 90% CIs are available upon request. Temporal effects (year of the survey) were included in the model but are not reported in the table

${}^{\ast }P\text{value}<0.1$; ${}^{\ast \ast }P\text{value}<0.05$; ${}^{\ast \ast \ast }P\text{value}<0.01$