A new role for the social services: fighting unemployment in the time of Covid-19

Figures & data

Table 1. Distribution of Demographic Characteristics by Eligibility.

Covariates	Non-Eligible [Mean]	Eligible [Mean]
Demographic characteristics
Age (years)	42.2 (2.9) t = 0.844	40.1 (0.8) p -Value = .399
Gender (Female = 1)	0.365 (0.067) t=−1.152	0.450 (0.025) p -Value = .250
Italian	0.275 (0.063) t=−0.274	0.293 (0.023) p -Value = .785
Children (number)	0.308 (0.093) t=−2.755	0.684 (0.048) p -Value = .006
Disabled in family (number)	0 (0.000) t=−1.261	0.051 (0.015) p -Value = .205
Benefit Dependency (Subsidy = 1)	0.250 (0.061) t=−3.661	0.517 (0.025) p -Value = .000
Occupational sector
Hotel industry	0.316 (0.110) t=−0.478	0.371 (0.031) p -Value = .063
Catering services	0.106 (0.072) t = 0.196	0.092 (0.019) p -Value = .845
Theatre and cinema	0.105 (0.072) t = 1.141	0.072 (0.014) p -Value = .255
Restaurant business	0.474 (0.118) t=−0.150	0.492 (0.032) p -Value = .881
Employment status
Unemployed	0.250 (0.112) t=−1.133	0.392 (0.031) p -Value = .259
On-call contract	0.250 (0.112) t = 0.208	0.227 (0.026) p -Value = .836
Seasonal worker	0.000 (0.000) t=−0.996	0.059 (0.015) p -Value = .320
Short-term contract	0.313 (0.120) t = 1.030	0.204 (0.025) p -Value = .303
Long-term contract	0.188 (0.101) t = 0.827	0.118 (0.020) p -Value = .409
Obs.	52	389

Notes: The data are provided by the Directorate of Social Services at the Municipality of Florence, Italy, and refer to individuals registered as unemployed or unable to work due to the pandemic in 2020. In this table, the analysis is done for the demographic characteristics of the individuals; namely, their gender, nationality, age, and household composition. For convenience we show Italy's country dummy. Standard errors are expressed in parentheses. Overall, individuals come from 67 countries. Two-sample t-test statistics (difference) are also showed in the table.

Table 2. Post-Training Employment by Demographic and Occupational Characteristics.

Employment post-training	Not employed	Employed	Obs.
Gender
Female	19 (61.3%)	12 (38.7%)	31
Male	16 (51.6%)	15 (48.4%)	31
Education
None	3 (42.9%)	4 (57.1%)	7
Middle-school diploma	3 (30%)	7 (70%)	10
High-school diploma	16 (55.2%)	33 (44.8%)	49
University degree	11 (91.7%)	1 (8.3%)	12
Missing	.	.	4
Nationality
Albania	3 (50%)	3 (50%)	6
Bangladesh	1 (100%)	0	1
Bosnia	1 (100%)	0	1
Cameroon	1 (50%)	1 (50%)	2
Ecuador	1 (100%)	0	1
Philippines	0	1 (100%)	1
Japan	1 (100%)	0	1
Italy	20 (55.6%)	16 (44.4%)	36
Moldova	0	1 (100%)	1
Peru	0	3 (100%)	3
Romania	1 (100%)	0	1
Senegal	1 (100%)	0	1
Syria	1 (50%)	1 (50%)	2
Spain	1 (100%)	0	1
Togo	1 (100%)	0	1
Tunisia	1 (100%)	0	1
Ukraine	1 (100%)	0	1
Number of children
0	20 (54%)	17 (46%)	37
1	4 (40%)	6 (60%)	10
2	7 (77.8%)	2 (22.2%)	9
3	0	1 (100%)	1
5	0	1 (100%)	1
Missing	.	.	4
Employment history
Long-term contract	4 (44.7%)	2 (33.3%)	8
Short-term contract	15 (53.6%)	13 (46.4%)	28
Missing	.	.	28

Notes: The data are provided by the Directorate of Social Services at the Municipality of Florence, Italy, and refer to individuals registered as unemployed or unable to work due to the pandemic in 2020.