This section presents the analysis of university-to-work transitions in the Western Balkan countries. The analysis is structured around the specific objectives and hypotheses outlined in Section 2. The aim is to provide a comprehensive understanding of how demographic and socio-economic factors influence the transition period, with a particular focus on the time-to-first-job.
The estimation for all the university graduate respondents in the sample is reported in Tables 2, 3, and 4 for all the WB6 countries in 2019, 2020, and 2021, respectively. The results highlight the impact of demographic and socio-economic factors on UTWT across different WB6 countries and years, particularly before, during, and after the COVID-19 pandemic.
Table 1
Variable definitions, sample means, and standard deviations: analysis for pooled sample at the micro/individual level
Variable | Definition (Questionnaire question) | Mean | DS |
Dependent variable | | | |
Time-to-first-job | Length of the time in years spent from university to first job Questionnaire item: ‘How long it took you between finishing university to getting the first job?’ | 3.9 | 1.8 |
External circumstances | | | |
Demographic endowments | | | |
Male | Binary variable, 1 for ’male’, 0 for ’female’. | 0.4 | 0.1 |
Age | Respondents’ age in years. | 24.5 | 2.8 |
Age square | Respondents’ square of age in years. | 606.25 | 137.4 |
Age 21–34 | Binary variable, 1 for respondents’ age ‘21–34’, and 0 for ’35 and older’. | 0.7 | 0.2 |
Rural | Binary variable for place of birth, 1 for ’rural’, 0 for ’urban’. | 0.8 | 0.3 |
Social endowments at birth | | | |
Unemployed familiars | Binary variable, 1 for ‘someone from your family lost their job’, 0 for ’other’. | 0.3 | 0.3 |
Family average socio-economic status | Binary variable if the respondent’s subjective social status is, 1 for ‘average’, 0 for ‘other’. | 0.5 | 0.2 |
Family lower socio-economic status | Binary variable if the respondent’s subjective social status is, 1 for ‘below the average’, 0 for ‘other’. | 0.4 | 0.3 |
Notes: Estimates based on the full sample of WB6 countries for years 2017 to 2021. |
Table 2
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for 2019: OLS estimates (coefficients and standard errors)
Circumstances | Albania | Bosnia and Herzegovina | Kosovo | North Macedonia | Montenegro | Serbia |
Male | -0.249 (0.192) | -0.271 (0.263) | -0.384* (0.207) | -0.179 (0.189) | 0.170 (0.227) | − .056 (.176) |
Age | -0.188*** (0.045) | -0.229*** (0.054) | -0.084* (0.005) | -0.095** (0.042) | -0.085** (0.039) | − .064* (.038) |
Age square | 0.002*** (0.001) | 0.002*** (0.001) | 0.001 (0.001) | 0.001* (0.000) | 0.001 (0.000) | 0.000 (0.000) |
Urban | 0.063 (0.224) | -0.058 (0.246) | -0.404** (0.201) | 0.207 (0.209) | -0.238 (0.269) | -0.384** (0.188) |
Family average socio-economic status | -0.099 (.329) | 0.360 (0.525) | 0.619** (0.308) | -0.452 (0.335) | 0.213 (0.439) | 0.327 (0.341) |
Family lower socio-economic status | -0.065 (0.400) | 0.588 (0.725) | 1.273*** (0.451) | 0.209 (0.405) | 0.544 (0.508) | 1.006** (0.395) |
Unemployed familiars | -0.328* (0.196) | 0.139 (0.281) | 0.063 (0.258) | -0.077 (0.195) | 0.393* (0.234) | 0.185 (0.181) |
Constant | 7.013*** (0.964) | 8.000*** (1.120) | 5.022*** (0.961) | 6.039*** (0.988) | 4.785*** (0.961) | 3.960*** (0.889) |
N | 223 | 229 | 363 | 278 | 207 | 287 |
Notes: |
Figures in curved parentheses are standard errors. |
*, ** and *** denote significance at the 10%, 5% and 1% levels, respectively. |
Table 3
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for 2020: OLS estimates (coefficients and standard errors)
Circumstances | Albania | Bosnia and Herzegovina | Kosovo | North Macedonia | Montenegro | Serbia |
Male | 0.089 (0.194) | -0.476** (0.238) | -0.065 (0.109) | -0.397** (0.191) | -0.164 (0.177) | -0.089 (0.199) |
Age | -0.188*** (0.043) | -0.105 (0.066) | -0.027 (0.028) | 0.000 (0.045) | -0.240*** (0.045) | 0.049 (0.045) |
Age square | 0.002*** (0.001) | 0.001 (0.001) | 0.000 (0.000) | -0.000 (0.000) | 0.002*** (0.000) | 0.001 (0.000) |
Urban | -0.579*** (0.211) | -0.148 (0.239) | 0.286** (0.112) | -0.180 (0.203) | -0.108 (0.188) | 0.026 (0.221) |
Family average socio-economic status | -0.215 (0.299) | 0.466 (0.441) | -0.083 (0.315) | 0.574 (0.374) | 0.076 (0.311) | 0.986 (0.621) |
Family lower socio-economic status | 0.027 (0.436) | 0.607 (0.600) | 0.453 (0.419) | 1.361*** (0.462) | 0.313 (0.372) | 1.486** (0.665) |
Unemployed familiars | 0.343 (0.222) | -0.118 (0.240) | 0.401*** (0.133) | -0.310 (0.198) | -0.066 (0.174) | 0.172 (0.201) |
Constant | 7.290*** (0.894) | 5.147*** (1.361) | 2.361*** (0.609) | 2.790*** (1.050) | 7.746*** (0.874) | 0.908 (1.227) |
N | 277 | 222 | 585 | 307 | 476 | 229 |
Notes: |
Figures in curved parentheses are standard errors. |
*, ** and *** denote significance at the 10%, 5% and 1% levels, respectively. |
Reference categories are: ‘female’ for ‘male’; ‘rural’ for ‘urban’; ‘family higher socio-economic status’ for ‘average’ and ‘lower socio-economic status’ of the family socio-economic class is ‘higher’; ‘employed familiars’ for ‘unemployed familiars’ |
Table 4
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for 2021: OLS estimates (coefficients and standard errors)
Circumstances | Albania | Bosnia and Herzegovina | Kosovo | North Macedonia | Montenegro | Serbia |
Male | -0.313* (0.180) | -0.223 (0.200) | -0.402** (0.181) | -0.602*** (0.185) | -0.154 (0.172) | -0.232 (0.184) |
Age | -0.175*** (0.038) | -0.036 (0.046) | -0.228*** (0.039) | -0.010 (0.044) | -0.147*** (0.037) | -0.010 (0.038) |
Age square | 0.001*** (0.000) | 0.001 (0.001) | 0.002 (0.000) | -0.000 (0.000) | 0.001*** (0.000) | 0.000 (0.000) |
Urban | -0.128 (0.199) | 0.211 (0.199) | -0.135 (0.186) | -0.101 (0.202) | 0.124 (0.180) | -0.174 (0.210) |
Family average socio-economic status | -0.672** (0.330) | -0.894*** (0.303) | 0.659*** (0.247) | 0.034 (0.333) | -0.310 (0.253) | -0.292 (0.302) |
Family lower socio-economic status | -0.651 (0.429) | 0.451 (0.474) | 0.563 (0.358) | 0.228 (0.412) | -0.248 (0.369) | 0.565 (0.362) |
Unemployed familiars | -0.119 (0.214) | -0.026 (0.214) | -0.357* (0.194) | -0.200 (0.195) | 0.253 (0.170) | 0.076 (0.188) |
Constant | 7.601*** (0.844) | 4.676*** (1.020) | 7.254*** (0.809) | 3.464*** (1.023) | 5.904*** (0.826) | 3.350*** (0.908) |
N | 261 | 263 | 328 | 243 | 314 | 276 |
Notes: |
Figures in curved parentheses are standard errors. |
*, ** and *** denote significance at the 10%, 5% and 1% levels, respectively. |
Reference categories are: ‘female’ for ‘male’; ‘rural’ for ‘urban’; ‘family higher socio-economic status’ for ‘average’ and ‘lower socio-economic status’ of the family socio-economic class is ‘higher’; ‘employed familiars’ for ‘unemployed familiars |
Hypothesis 1
posits that younger graduates will experience shorter transitions to their first job compared to older graduates. In 2019, the regression analysis (Table 2) indicates that younger individuals in Albania, Bosnia and Herzegovina, Kosovo, North Macedonia, and Montenegro consistently secured employment faster than their older counterparts. This pattern is particularly pronounced in Albania and Bosnia and Herzegovina, where age showed a significant U-shaped relationship with time-to-first-job, indicating that both very young and older graduates experienced longer transitions. The trend remained consistent through 2020 (Table 3) and 2021 (Table 3), although the pandemic year (2020) saw a slight increase in the transition times for younger graduates in Montenegro, likely due to economic disruptions caused by COVID-19. In 2021, the effect of age continued to be significant in Albania and Montenegro, confirming the persistent impact of age on university-to-work transitions. The data supports Hypothesis 1 across all years and most countries, indicating that younger graduates generally experience shorter transitions to their first job.
Hypothesis 2
states that female graduates face longer transitions compared to male graduates. In 2020, the data (Table 3) reveal that being a male significantly reduced the time-to-first-job in Bosnia and Herzegovina and North Macedonia, confirming this hypothesis. In Kosovo and North Macedonia, this gender disparity was particularly notable, with male graduates securing jobs faster than their female counterparts. In contrast, countries like Albania and Serbia showed less pronounced gender effects, indicating variability in gender-based disparities across the region. Over the years, the gender gap in transition times showed some fluctuations. During the pandemic in 2020, the gender disparity in North Macedonia and Bosnia and Herzegovina was exacerbated, reflecting the increased challenges faced by female graduates during economic downturns. By 2021, the gender gap persisted, particularly in Albania and Kosovo, highlighting ongoing challenges in achieving gender equality in labour market transitions. In summary, the data supports Hypothesis 2 in Bosnia and Herzegovina, Kosovo, and North Macedonia across the years, though the support is less consistent in Albania and Serbia.
Hypothesis 3
states that graduates from rural areas experience longer transitions compared to those from urban areas. In 2019, the analysis (Table 4) shows that graduates born in urban areas had shorter transition periods in Kosovo and Serbia. This urban advantage was most pronounced in Bosnia and Herzegovina and Kosovo, where urban upbringing significantly reduced the time-to-first-job. However, in Montenegro and Albania, the rural-urban disparity was less evident. During the pandemic year (2020), the advantage of urban upbringing decreased in Albania, where urban graduates faced longer transitions compared to their rural counterparts. This shift suggests that the economic impact of the pandemic affected urban areas more severely. By 2021, the rural-urban disparities remained significant in Bosnia and Herzegovina and Kosovo but showed a slight reduction in other countries, indicating some level of recovery. The data supports Hypothesis 3 in Kosovo and Serbia consistently, with partial support in Bosnia and Herzegovina and mixed results in Albania and Montenegro.
According to Hypothesis 4, graduates from lower socio-economic backgrounds will have longer transitions. The findings (Table 5) indicate that lower SES significantly increased the time-to-first-job in Kosovo and Serbia, while in Albania and Bosnia and Herzegovina, the effect was less significant. In Kosovo, graduates from lower socio-economic backgrounds experienced the longest transitions, highlighting the profound impact of SES on employment outcomes in this country. In 2020, the effect of lower SES was amplified in Montenegro, where graduates from lower socio-economic backgrounds faced significantly longer transitions, reflecting the heightened economic challenges during the pandemic. By 2021, the impact of SES remained a critical factor in Serbia and Kosovo, underscoring the persistent influence of socio-economic background on labour market integration. The data supports Hypothesis 4 in Kosovo, Serbia, and Montenegro, with partial support in Albania and Bosnia and Herzegovina.
Table 5
Inequality of opportunity for university-to-work transitions (measured in time-to-first-job) and share of contribution of each circumstances for 2019
Country | Albania | BiH | Kosovo | N. Macedonia | Montenegro | Serbia |
IOp in UTWT | 0.1778 | 0.2050 | 0.0767 | 0.0625 | 0.1265 | 0.0978 |
Circumstances | | | | | | |
Male | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |
Age | 0.14 | 0.19 | 0.14 | 0.16 | 0.24 | 0.17 |
Age square | 0.05 | 0.08 | 0.04 | 0.06 | 0.10 | 0.07 |
Urban | 0.21 | 0.34 | 0.27 | 0.23 | 0.19 | 0.25 |
Family average socio-economic status | 0.07 | 0.05 | 0.09 | 0.07 | 0.05 | 0.06 |
Family lower socio-economic status | 0.45 | 0.27 | 0.40 | 0.42 | 0.36 | 0.39 |
Unemployed familiars | 0.06 | 0.06 | 0.04 | 0.06 | 0.06 | 0.06 |
Notes: |
IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2019. We use the predicted scores of the reduced-form regression of circumstances predicting university-to-work transitions for 2019 to estimate the contribution of each circumstances. |
Hypothesis 5
states that graduates with unemployed family members will take longer to find their first job. The results (Table 6) show that having unemployed family members significantly delayed the transition in Kosovo and Serbia, supporting this hypothesis. In Albania, however, having unemployed family members unexpectedly reduced the time-to-first-job in 2019, possibly due to increased pressure and motivation to secure employment quickly. During the pandemic year (2020), the presence of unemployed family members had a mixed impact across countries. In Kosovo, this factor significantly increased transition times, while in Montenegro, it had a less pronounced effect. By 2021, the impact of family unemployment remained significant in Kosovo, highlighting the enduring economic difficulties faced by families in this region. The data supports Hypothesis 5 in Kosovo and Serbia across the years, with mixed results in Albania and Montenegro.
Table 6
Inequality of opportunity for university-to-work transitions (measured in time-to-first-job) and share of contribution of each circumstances for 2020
Country | Albania | BiH | Kosovo | N. Macedonia | Montenegro | Serbia |
IOp in UTWT | 0.2250 | 0.0648 | 0.0403 | 0.0529 | 0.0811 | 0.0665 |
Circumstances | | | | | | |
Male | 0.01 | 0.01 | 0.02 | 0.01 | 0.01 | 0.02 |
Age | 0.05 | 0.04 | 0.09 | 0.06 | 0.04 | 0.10 |
Age square | 0.07 | 0.06 | 0.13 | 0.09 | 0.05 | 0.20 |
Urban | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
Family average socio-economic status | 0.41 | 0.38 | 0.31 | 0.32 | 0.34 | 0.21 |
Family lower socio-economic status | 0.44 | 0.47 | 0.40 | 0.48 | 0.53 | 0.42 |
Unemployed familiars | 0.02 | 0.04 | 0.05 | 0.04 | 0.03 | 0.06 |
Notes: |
IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2020. We use the predicted scores of the reduced-form regression of circumstances predicting university-to-work transitions for 2020 to estimate the contribution of each circumstances. |
Tables 5, 6, and 7 report the inequality of opportunity (IOp) resulting from all the external factors included in the estimation (gender, age, urban residency, average and low (vs. high) socio-economic status of the family, and whether graduates had unemployed familiars in the household).
Table 7
Inequality of opportunity for university-to-work transitions (measured in time-to-first-job) and share of contribution of each circumstances for 2021
Country | Albania | BiH | Kosovo | N. Macedonia | Montenegro | Serbia |
IOp in UTWT | 0.2454 | 0.0859 | 0.1594 | 0.0586 | 0.1038 | 0.0830 |
Circumstances | | | | | | |
Male | 0.32 | 0.29 | 0.24 | 0.30 | 0.27 | 0.27 |
Age | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |
Age square | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 |
Urban | 0.15 | 0.16 | 0.13 | 0.14 | 0.14 | 0.12 |
Family average socio-economic status | 0.15 | 0.20 | 0.21 | 0.15 | 0.20 | 0.16 |
Family lower socio-economic status | 0.34 | 0.30 | 0.37 | 0.36 | 0.35 | 0.41 |
Unemployed familiars | 0.02 | 0.03 | 0.02 | 0.03 | 0.03 | 0.03 |
Notes: |
IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2021. We use the predicted scores of the reduced-form regression of circumstances predicting university-to-work transitions for 2021 to estimate the contribution of each circumstances. |
In 2019 (pre-pandemic), IOp in UTWT varied across countries. It was highest in Bosnia and Herzegovina (0.2050) and lowest in North Macedonia (0.0625). Age had a significant share across all countries, with a notable contribution in Montenegro (0.24) and Bosnia and Herzegovina (0.19). Urban upbringing contributed notably, especially in Bosnia and Herzegovina (0.34) and Kosovo (0.27). The self-perceived social origins from a family of lower (vs. higher) socio-economic status was a major contributor across all countries, with the highest impact in Albania (0.45) and the lowest in Bosnia and Herzegovina (0.27). While having unemployed familiars in the household had a smaller yet consistent contribution across all countries, at 0.06 for all except Kosovo (0.04).
For 2020 (pandemic year), the highest IOp was observed in Albania (0.2250) and the lowest in Bosnia and Herzegovina (0.0648). Contributions of the curvilinear effects of age varied, with notable contributions in Serbia for age square. Urban upbringing had negligible contributions across all countries. Both self-perceived social origins of the family as from an average and low (vs. high) socio-economic statuses had notable contribution. For example, family lower socio-economic status had the highest share in Montenegro (0.53). Having unemployed family members had relatively low share, with the highest in Serbia (0.06).
For 2021 (post-pandemic), the highest IOp was in Albania (0.2454) and the lowest in North Macedonia (0.0586). For male graduates, this had consistently notable contributions across all countries, with the highest in Albania (0.32). Urban upbringing continued to have significant contributions, especially in Bosnia and Herzegovina (0.16). Self-perceived social origins as from a lower (vs. higher) socio-economic status remained a significant contributor, especially in Serbia (0.41) while having unemployed family member in the household had lower contributions, with consistent values around 0.02 to 0.03.
A robustness analysis, in Table 8, 9, and 10 we have estimated the same model but age has been converted to a binary variable where we compare its effects for the 21–34 age segment with the 35 years and older as this also represents the largest share of the respective samples. In 2019, IOp values ranged from 0.0715 in Albania to 0.0859 in Serbia. Male graduates had negative coefficients in most countries, indicating a shorter time-to-first-job compared to females. Graduates from urban upbringing generally had a shorter time-to-first-job in some countries, like Kosovo. For those graduates who perceived their family as from an average socio-economic status, varied impacts are revealed, with some countries showing positive and others negative effects. On the other hand, for the lower socio-economic status, it can be said that it is generally associated with longer transitions, especially in Kosovo. Having unemployed family member in the household revealed mixed effects, with some countries showing negative impacts and others positive. In 2020, IOp values increased slightly, with Albania at 0.1435 and Serbia at 0.0426. Male graduates generally had an advantage in terms of time-to-first-job. The trend persisted for graduates with urban upbringing, with those in Kosovo and Albania having shorter transitions. For those graduates who perceived their family as from an average socio-economic status, the effects were mixed, with some positive coefficients in Albania and negative in Montenegro. Similar trends were observed, with lower socio-economic status leading to longer times in some countries. Having unemployed family members, generally led to longer transitions in some countries, like Albania. In 2021, IOp values saw some fluctuations, with Albania at 0.1077 and Serbia at 0.0475. For male graduates, the trend continued, but with more pronounced effects in certain countries like Kosovo, where being male was associated with a significantly shorter time-to-first-job. The impact of an urban background was less pronounced, with some countries showing negligible differences. For average socio-economic status, the impact remained inconsistent across countries, while for lower socio-economic status, the trend continued, with significant impacts in countries like Serbia.
Table 8
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for the ‘younger age cohort: 21–34, for 2019: OLS estimates (coefficients and standard errors)
Country | Albania | BiH | Kosovo | N. Macedonia | Monte negro | Serbia |
IOp in UTWT for younger cohort (21–34) | 0.0715 | 0.0821 | 0.0539 | 0.0356 | 0.0316 | 0.0859 |
Circumstances | | | | | | |
Male | -0.252 (0.218) | -0.571* (0.301) | -0.373 (0.214) | -0.284 (0.200) | 0.231 (0.266) | 0.036 (0.192) |
Young cohort (21–34) | 0.626*** (0.220) | 1.052*** (0.308) | 0.297 (0.224) | 0.131 (0.206) | 0.456* (0.264) | 0.523*** (0.195) |
Urban | 0.208 (0.247) | -0.073 (0.285) | -0.409** (0.113) | 0.091 (0.216) | -0.180 (0.305) | -0.408** (0.206) |
Family average socio-economic status | -0.243 (0.391) | 0.537 (0.616) | 0.650** (0.317) | -0.482 (0.347) | -0.024 (0.570) | 0.299 (0.359) |
Family lower socio-economic status | -0.055 (0.474) | 0.930 (0.982) | 1.422*** (0.468) | 0.152 (0.423) | 0.019 (0.646) | 1.075** (0.418) |
Unemployed familiars | -0.455** (0.174) | 0.034 (0.319) | 0.020 (0.266) | 0.003 (0.204) | 0.371 (0.269) | 0.182 (0.196) |
Constant | 2.617*** (0.448) | 2.059*** (0.707) | 2.978*** (0.386) | 3.820*** (0.376) | 2.487*** (0.677) | 1.954*** (0.373) |
N | 223 | 229 | 363 | 278 | 207 | 287 |
Notes: IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2019. |
Table 9
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for the ‘younger age cohort: 21–34, for 2020: OLS estimates (coefficients and standard errors)
Country | Albania | BiH | Kosovo | N. Macedonia | Monte negro | Serbia |
IOp in UTWT for younger cohort (21–34) | 0.1435 | 0.0410 | 0.0455 | 0.0646 | 0.0206 | 0.0426 |
Circumstances | | | | | | |
Male | -0.021 (0.215) | -0.461* (0.250) | -0.104 (0.110) | -0.418** (0.200) | -0.177 (0.189) | -0.016 (0.224) |
Young cohort (21–34) | 1.015*** (0.215) | 0.403 (0.252) | -0.189* (0.113) | -0.209 (0.200) | 0.506** (0.217) | 0.261 (0.228) |
Urban | -0.666*** (0.330) | -0.176 (0.251) | 0.309*** (0.113) | -0.202 (0.214) | -0.257 (0.203) | -0.032 (0.244) |
Family average socio-economic status | -0.229 (0.391) | 0.446 (0.451) | 0.074 (0.340) | 0.495 (0.382) | 0.123 (0.338) | 0.929 (0.643) |
Family lower socio-economic status | 0.144 (0.498) | 0.579 (0.623) | 0.681 (0.442) | 1.377*** (0.474) | 0.281 (0.402) | 1.553** (0.701) |
Unemployed familiars | 0.491** (0.246) | -0.115 (0.251) | 0.405*** (0.132) | -0.405* (0.208) | -0.128 (0.186) | 0.142 (0.222) |
Constant | 2.524*** (0.394) | 2.626*** (0.530) | 1.922*** (0.354) | 2.978*** (0.428) | 2.832*** (0.406) | 1.669** (0.696) |
N | 277 | 222 | 585 | 307 | 476 | 229 |
Notes: IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2020. |
Table 10
Reduced-form regression of circumstances predicting university-to-work transitions (measured in time-to-first-job) for the ‘younger age cohort: 21–34, for 2021: OLS estimates (coefficients and standard errors)
Country | Albania | BiH | Kosovo | N. Macedonia | Monte negro | Serbia |
IOp in UTWT for younger cohort (21–34) | 0.1077 | 0.0858 | 0.0826 | 0.0471 | 0.0320 | 0.0475 |
Circumstances | | | | | | |
Male | -0.322 (0.206) | -0.145 (0.212) | 0.610*** (0.194) | -0.590*** (0.197) | -0.103 (0.192) | -0.196 (0.203) |
Young cohort (21–34) | 0.980*** (0.214) | 0.306 (0.212) | 0.448** (0.198) | 0.029 (0.201) | 0.469** (0.189) | 0.211 (0.213) |
Urban | -0.174 (0.227) | 0.245 (0.213) | -0.048 (0.196) | -0.087 (0.213) | 0.109 (0.203) | -0.162 (0.233) |
Family average socio-economic status | -0.634* (0.374) | -0.952*** (0.314) | 0.707** (0.264) | 0.041 (0.340) | -0.200 (0.283) | -0.089 (0.329) |
Family lower socio-economic status | -0.250 (0.508) | 0.611 (0.527) | 0.643* (0.380) | 0.186 (0.429) | -0.183 (0.427) | 0.657 (0.401) |
Unemployed familiars | -0.232 (0.242) | -0.083 (0.229) | -0.356* (0.208) | -0.215 (0.206) | 0.256 (0.190) | 0.215 (0.205) |
Constant | 2.995*** (0.415) | 3.531*** (0.340) | 2.492*** (0.306) | 3.065*** (0.383) | 2.237*** (0.333) | 2.470*** (0.398) |
N | 261 | 263 | 328 | 243 | 314 | 276 |
Notes: IOp in UTWT is the adjusted R-Square for the reduced-form regression of circumstances predicting university-to-work transitions for 2021. |
From the findings of the regression analysis across 2019, 2020, and 2021, several key conclusions can be drawn regarding the UTWT for the younger age cohort (22–34) in the WB6 countries. The IOp values showed variation across countries and years, indicating that inequality of opportunity in university-to-work transitions is influenced by multiple external and temporal factors. IOp increased slightly during 2020, the first full year of the COVID-19 pandemic, suggesting that the pandemic may have exacerbated existing inequalities. Male graduates generally experienced shorter times-to-first-job compared to female graduates across most countries and years. This persistent gender disparity highlights ongoing challenges in achieving gender equality in labour market transitions. Graduates born in urban areas generally had an advantage in some countries, but the impact was less consistent in 2021. This suggests that urban-rural disparities in UTWT may be influenced by factors such as economic conditions, local job markets, and educational opportunities. The socio-economic status of graduates' families had mixed effects on UTWT. Higher family socio-economic status sometimes led to shorter transitions, while lower socio-economic status often resulted in longer transitions, especially in certain countries like Kosovo and Serbia. This underscores the importance of socio-economic background in shaping labour market outcomes. The presence of unemployed family members generally had a negative impact on UTWT in some years and countries, indicating that family economic conditions can significantly influence graduates' job search outcomes.
The analysis reveals significant disparities in university-to-work transitions based on age, gender, urban-rural background, socio-economic status, and family employment conditions. These disparities suggest the presence of structural inequalities that affect the labour market outcomes of young graduates in the Western Balkans. The cross-country and temporal comparisons highlight how these factors vary across different contexts and over time, particularly in response to the economic disruptions caused by the Covid19 pandemic.