Annex B. Regression analysis on the probability of starting a firm for young entrepreneurs
Table A B.1. Probability of starting a firm for young entrepreneurs, 2019 | ||||||||
---|---|---|---|---|---|---|---|---|
| (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) |
Young start-up entrepreneurship | All | All | All | All | All | Cities | Towns and suburbs | Rural |
Towns and suburbs | -0.073*** | -0.055** | -0.048* | -0.049* | -0.038 | |||
[0.025] | [0.025] | [0.026] | [0.026] | [0.025] | ||||
Rural areas | -0.114*** | -0.093*** | -0.091*** | -0.102*** | -0.086*** | |||
[0.026] | [0.027] | [0.028] | [0.030] | [0.030] | ||||
Female | -0.124*** | -0.115*** | -0.081*** | -0.077*** | -0.054* | -0.098*** | -0.099** | |
[0.019] | [0.021] | [0.020] | [0.021] | [0.029] | [0.029] | [0.044] | ||
Unemployed (last year) | 0.774*** | 0.792*** | 0.813*** | 0.808*** | 0.852*** | 0.693*** | 0.867*** | |
[0.046] | [0.045] | [0.045] | [0.045] | [0.059] | [0.062] | [0.096] | ||
In training (last year) | 0.432*** | 0.420*** | 0.428*** | 0.429*** | 0.534*** | 0.310*** | 0.177 | |
[0.050] | [0.052] | [0.052] | [0.051] | [0.059] | [0.080] | [0.109] | ||
Foreigner | -0.071** | -0.077*** | -0.075** | -0.094** | -0.067 | 0.022 | ||
[0.029] | [0.030] | [0.029] | [0.040] | [0.055] | [0.074] | |||
Secondary education | 0.194*** | 0.234*** | 0.238*** | 0.223*** | 0.225*** | 0.133*** | 0.285*** | 0.305*** |
[0.031] | [0.034] | [0.037] | [0.036] | [0.035] | [0.045] | [0.054] | [0.068] | |
Tertiary education | 0.381*** | 0.447*** | 0.467*** | 0.418*** | 0.420*** | 0.333*** | 0.510*** | 0.451*** |
[0.038] | [0.043] | [0.046] | [0.045] | [0.044] | [0.061] | [0.060] | [0.089] | |
Father’s education: primary | -0.006 | -0.003 | -0.002 | -0.045 | 0.005 | 0.015 | ||
[0.052] | [0.052] | [0.052] | [0.104] | [0.083] | [0.076] | |||
Father’s education: secondary | 0.104* | 0.110* | 0.111** | 0.139 | 0.065 | 0.138** | ||
[0.055] | [0.056] | [0.056] | [0.102] | [0.077] | [0.067] | |||
Father’s education: tertiary | 0.039 | 0.047 | 0.042 | 0.016 | 0.052 | 0.113 | ||
[0.059] | [0.060] | [0.060] | [0.108] | [0.091] | [0.112] | |||
Mother’s education: primary | -0.044 | -0.030 | -0.025 | -0.139 | 0.073 | 0.013 | ||
[0.058] | [0.058] | [0.058] | [0.104] | [0.089] | [0.062] | |||
Mother’s education: secondary | 0.023 | 0.039 | 0.040 | -0.008 | 0.065 | 0.148** | ||
[0.049] | [0.049] | [0.049] | [0.098] | [0.067] | [0.063] | |||
Mother’s education: tertiary | 0.068 | 0.087 | 0.088 | -0.062 | 0.293*** | 0.112 | ||
[0.053] | [0.054] | [0.054] | [0.088] | [0.081] | [0.098] | |||
Work from home | -0.154*** | -0.144*** | -0.166*** | -0.090*** | -0.166*** | |||
[0.020] | [0.021] | [0.034] | [0.024] | [0.033] | ||||
Work weekends and nights | 0.116*** | 0.118*** | 0.135*** | 0.105** | 0.095** | |||
[0.020] | [0.020] | [0.032] | [0.041] | [0.045] | ||||
Looking for a job | 0.055 | 0.052 | 0.057 | -0.014 | 0.158* | |||
[0.042] | [0.042] | [0.069] | [0.061] | [0.086] | ||||
Constant | -2.719*** | -2.793*** | -2.769*** | -2.569*** | -2.723*** | -2.610*** | -2.977*** | -2.994*** |
[0.048] | [0.057] | [0.066] | [0.153] | [0.178] | [0.290] | [0.319] | [0.270] | |
Country fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
Socio-economic fixed effects | No | No | Yes | Yes | Yes | Yes | Yes | Yes |
Sector fixed effects | No | No | No | No | Yes | Yes | Yes | Yes |
Occupation fixed effects | No | No | No | No | Yes | Yes | Yes | Yes |
Observations | 1 033 674 | 1 033 674 | 942 312 | 939 840 | 939 430 | 294 287 | 349 021 | 295 814 |
Note: Reported coefficients are from a probit model with standard errors clustered at a regional level. The reference group for parents’ education level are parents who do not live with individuals at home. Robust standard errors in brackets. | ||||||||
Source: Eurostat (n.d.[4]), European Union Labour Force Survey (EU-LFS), https://ec.europa.eu/eurostat/web/microdata/european-union-labour-force-survey. |
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