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Genus

Journal of Population Sciences

Table 2 Probit models on the probability of not being a NEET

From: The determinants of Italian NEETs and the effects of the economic crisis

NEETs

All

Area of residence

Field of study

Level of education

Behaviour

Parent’s education level

Gender

South-Isles

North-Centre

Soft sciences

Hard sciences

Not high educated

High educated

Not looking for a job

Looking for a job

No high educated parent

High educated parent

Women

Men

2015

 In education, employment or training

  Gender (male = 1)

.038

.047

.041

.029

.145*

− .007

.071

.119***

− .094

.000

− .122

–

–

  Age

− .035***

− .057***

− .019***

− .047***

.042***

− .032**

.010

− .035***

− .027**

− .049***

− .062*

− .044***

− .029***

  Educational level (ref. low)

   Medium

.239***

.458***

.060

.104***

− .253***

–

–

.294***

.584***

.227***

− .009

.246***

.249***

   High

.567***

.838***

.332***

.269***

–

–

–

.590***

1.06***

.624***

.233

.602***

.556***

  Parents’ educational level (high = 1)

   Father

.201***

.286***

.141*

.235***

.215

.430***

− .079

.148**

.117

–

–

.247***

.172**

   Mother

.204***

.364***

.124*

.281***

− .035

.375***

− .072

.116*

.272

–

–

.247***

.172**

  Civil status(1)

− .479***

− .450***

− .467***

− .479***

− .339***

− .619***

− .143

− .685***

− .385*

− .499***

− 1.171

− .402***

.589***

  Native born(2)

.374***

− .054

.504***

.308***

.424***

.344***

.680***

.364***

.091

.310***

.431**

.504***

.210***

  Area(3)

.622***

–

–

.597***

.727***

.617***

.643***

.663***

.268***

.562***

.219**

.630***

.613***

  Field of study (ref. general programmes)

   Humanities

− .411***

− .540***

− .314***

–

–

− .332***

−.168

− .291***

− .405*

− .522***

− .785***

− .386***

− .527***

   Social

− .285***

− .429***

− .171***

–

–

− .087**

−.117

− .217***

− .357***

− .426***

− .827***

− .249***

− .347***

   Science

− .199***

− .364***

− .078

–

–

− .040

.089

− .132**

− .444***

− .291***

− .431***

− .252***

− .202***

   Agrarian

− .080

− .200

− .019

–

–

.104

.070

− .071

− .245

− .186

− .351

− .046

− .110

   Health

− .121

− .333**

.038

–

–

− .291

.129

.035

− .378

− .483***

− .565**

− .067

− .310*

  Services

− .501***

− .672***

− .371***

–

–

− .341***

− .201

− .392***

− .606***

− .613***

− 1.013***

− .527***

− .474***

  male*civil status

1.154***

1.179***

1.177***

1.148***

.941***

1.258***

.857***

1.417***

.247

1.026***

2.436*

–

–

  Intercept

.751***

1.610***

.925***

1.071***

− 1.187***

.803***

− .529

.965***

− 1.072***

1.177***

2.317***

.804***

.783***

  Prob > chi2

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000***

  Pseudo R2.

.103

.070***

.070

.108

.100

.112

.072

.140

.068

.077

.140

.128***

.069***

  N

106,917

40,706

66,211

88,887

18,030

91,964

14,953

94,646

12,271

67,321

12,530

53,230

53,687

2005

 In education, employment or training

  Gender (male = 1)

.116***

.136***

.103**

.141***

− .043

.105***

.101

.166***

− .099

.060*

.012

–

–

  Age

− .021***

− .036***

− .007*

− .027***

.024***

− .019***

.033***

− .020***

− .029**

− .027***

− .034**

− .029***

− .012***

  Educational level (ref. low)

   Medium

.202***

.176*

.178**

.263***

.743***

–

–

.230***

.291

.088

− .238

.289***

.120

   High

.044

.096

− .024

.086*

.585***

–

–

.131

.433*

− .139

.795

.173*

− .099

  Parents’ educational level (high = 1)

   Father

.234***

.428***

.073

.249***

.261*

.455***

− .043

.145*

.242

–

–

.239**

.256**

   Mother

.208***

.314***

.106

.227***

.200

.403***

−.086

.166*

.162

–

–

.254**

.184*

  Civil status(1)

− .673***

− .703***

− .645***

− .649***

− .741***

− .769***

− .145

− .874***

− .471**

− .726***

− .412

− .604***

.650***

  Native born(2)

.357***

− .057

.449***

.364***

.444***

.341***

.446***

.369***

− .100

.176

− .255

.501***

.108

  Area(3)

.738***

–

–

.755***

.661***

.764***

.594***

.739***

.125

.680***

.243**

.772***

.691***

  Field of study (ref. general programmes)

   Humanities

.136**

.299***

.029

–

–

.318***

.497

.172**

.427*

.132

.198

.135*

.082

   Social

.037

.075

.031

–

–

.251**

.465

.105

.215

− .021

− .163

.078

− .054

   Science

.190***

.280***

.152*

–

–

.337***

.776

.213***

.359

.202***

.318

.284***

.146

   Agrarian

− .079

− .155

.020

–

–

.076

.550

.007

.073

− .066

− .185

− .081

− .062

   Health

.325

.407**

.287*

–

–

.165

.941

.359***

.275

.177

.170

.349***

.194

  Services

− .211***

− .203

− .197*

–

–

− .071

.527

− .092***

− .084

− .280***

− .378

− .156

− .292**

  male*civil status

1.418***

1.485***

1.441***

1.397***

1.424***

1.482***

1.135***

1.658***

.203

1.057***

1.014

 

–

  Intercept

.467***

1.218***

.807***

.606***

− .987***

.477***

− 1.566*

.676***

− .653*

.895***

2.495***

.454***

.700***

  Prob > chi2

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

  Pseudo R2

.143

.113

.094

.143

.107

.160

.082

.190

.073

.071

.131

.156

.082

  N

159,818

71,482

88,336

123,491

36,327

144,280

15,538

146,901

12,917

103,122

12,447

79,204

80,614

  1. Source: Ad hoc elaborations on Labour Force Survey data (2015–2005)
  2. (1)Living with a partner = 1; (2) Native born = 1; (3) Living in the North-Centre of Italy = 1
  3. ***Significance at 1%; **significance at 5%; *significance at 10%
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