# Regional Disparities and Determinants of Graduate Employability in Tunisia

Olfa Hachicha, Zyed Achour

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Olfa Hachicha, Zyed Achour. Regional Disparities and Determinants of Graduate Employability in Tunisia. International Journal of Innovative Research and Publications, 2025, pp.14 - 27. 10.51430/ijirp.2025.512.002. hal-05189253

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## Article

# Regional Disparities and Determinants of Graduate Employability in Tunisia

Olfa Hachicha<fnref n="1" />, Zyed Achour²*

Received: 14 April 2025 / Accepted: 27 April 2025 / Published online: 10 May 2025

## Abstract

The professional integration of higher education graduates represents a critical issue for developing economies, particularly in Tunisia, where persistent regional disparities affect the employment of qualified youth. This study examines the determinants of graduates' integration into the labor market, taking into account individual characteristics, educational attainment, and regional disparities. Using secondary data from a national survey of 651 graduates and estimating a probit model, the findings reveal that gender and age significantly influence employment outcomes, with male and older graduates demonstrating a higher probability of integration. The analysis further indicates that the impact of educational attainment varies: specialized training such as engineering or doctoral degrees significantly enhances employability, whereas holding a master's degree does not provide a substantial advantage over a bachelor's degree. Moreover, the study highlights pronounced territorial inequalities, as graduates from Greater Tunis and the Central-East regions exhibit better integration prospects compared to those from interior regions. These results underscore the need for targeted public policies aimed at reducing spatial disparities and promoting equitable access to employment opportunities for all graduates.

**Keywords:** Professional integration, Higher education graduates, Labor market, Regional inequalities, Probit model, Tunisia

## To cite this article:

Hachicha, O., & Achour, Z. (2025). Regional Disparities and Determinants of Graduate Employability in Tunisia. *International Journal of Innovative Research and Publications, 5*(12), 14-27.
https://doi.org/10.51430/IJIRP.2025.512.002

eISSN 2785-826X

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© 2025 by the authors. Licensee: MAC Arts & Communication. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-SA) license. (https://creativecommons.org/licenses/by/4.0/)

9 77 2 785 8 2 600 0 7

<footnote n="1">¹,²National Institute of Labour and Social Studies, University of Carthage, Tunisia</footnote>

<footnote>*Corresponding Email: zyed.achour@intes.rnu.tn</footnote>
**Introduction**

The professional integration of higher education graduates is a central issue in many developing economies. In Tunisia, while the university enrollment rate has increased significantly in recent decades, the labor market is struggling to absorb these new graduates, generating high unemployment among qualified young people. In 2022-2023, the Tunisian education system had 13 universities, bringing together 206 public and 80 private institutions, with a total of 260,930 Tunisian students and a success rate of 78.2% (ATCT, 2023). The gross enrollment rate in higher education reached 34.1% in 2021, with a notable gender disparity: 43.6% for girls compared to 25% for boys (UNICEF, 2022).

This positive dynamic in terms of training has, however, come up against structural limits, accentuated by the COVID-19 crisis, which has exacerbated labor market imbalances and territorial disparities. Moreover, recent studies have also highlighted the existence of a persistent mismatch between the skills developed at university and the real demands of the Tunisian labor market, a structural problem recognized in the National Employment Strategy (Masmoudi and Ferchichi, 2024). The authors note that this mismatch operates at both regional and national levels, worsening unemployment among young graduates despite a continued increase in school enrollment.

While many studies have analyzed the determinants of employability in Tunisia, they have often focused on individual factors—level of education, specialization, professional experience—without paying sufficient attention to the regional disparities that condition access to employment. However, recent data show that the professional integration of graduates varies significantly depending on the region: Greater Tunis and the Center-East record relatively high employment rates, while the Center-West and the Southwest remain on the margins, with limited opportunities. For example, Belhadj (2023) demonstrates that the coastal regions and Greater Tunis have significantly higher integration rates than the interior regions. These territorial inequalities, far from being reduced, tend to be reinforced, as illustrated by the work of Hamida (2024). This disparity in job opportunities underscores the importance of targeted policies aimed at fostering economic growth in underdeveloped areas. Without such interventions, graduates from these marginalized regions may continue to face challenges in securing stable employment, perpetuating cycles of inequality.

Indeed, some rural areas in the interior have unemployment rates exceeding 40%, particularly among young people aged 15 to 24, where the rate reached 40.5% in 2023 (National Institute of Statistics [INS], 2023). These disparities are largely attributable to the concentration of economic and industrial activities on the coast, which represents more than 90% of overall employment and 80% of private investment, to the detriment of the interior regions (World Bank, 2022). In addition, coastal governorates have a higher human capital index (0.62 compared to 0.48 in the interior), reflecting better conditions of access to employment and training (United Nations Development Program [UNDP], 2022). Conversely, the Northwest and Southwest regions have the highest poverty rates, often above 33% (National Observatory of Regional Development [ONDR], 2021), accentuating socio-economic disparities. This territorial heterogeneity continues to raise major questions about the mechanisms influencing professional integration depending on geographical location.

Unlike existing studies, this research proposes an integrated approach combining the individual characteristics of graduates and the territorial dynamics of employment—a perspective still rarely addressed quantitatively in the Tunisian context. With this in mind, our study aims to identify and quantify the determinants of graduates' professional integration in Tunisia by integrating a regional analysis. Through an econometric analysis based on a probit model applied to a sample of 651 graduates, we seek to better understand the gaps observed between regions and formulate informed recommendations for public policies.
The article is organized as follows: after a literature review that allows us to situate our theoretical contribution, we present the methodology adopted, detailing the data used and the econometric tools mobilized. The results of the analysis are then presented and discussed before concluding with recommendations aimed at improving the professional integration of graduates while taking into account territorial specificities.

## Literature Review

The professional integration of higher education graduates is based on a multidimensional theoretical approach, mobilizing several explanatory frameworks. Among the most studied structural variables is gender, which plays a determining role in access to employment. The signaling theory, developed by Spence (1973), postulates that employers use certain observable characteristics, such as gender, as indirect indicators of productivity in a labor market marked by information asymmetry. These signals, although imperfect, influence hiring decisions and can lead to structural discrimination. In particular, women are often perceived as less available or less committed due to stereotypes associated with their family responsibilities, which limits their opportunities to access qualified jobs.

In Tunisia, labor market dynamics, particularly regarding unemployment among young graduates, have been analyzed by Stampini and Verdier-Chouchane (2011). Although their study focuses on young people in general, it highlights the structural dysfunctions of the Tunisian labor market, which affect men and women differently. Other work shows that Tunisian women experience significantly higher unemployment rates than their male counterparts, reflecting persistent inequalities in access to formal and stable employment (World Bank, 2021).

Internationally, Kuhn and Shen (2011) demonstrate that gender preferences in job advertisements remain common, thus reinforcing hiring barriers for women. Furthermore, a survey conducted by Pew Research (2013) reveals that many women in the United States report experiencing some form of gender-based discrimination in the workplace, which hinders their career advancement. Similar findings emerge from the Tunisian context: according to Maayoufi et al. (2022), despite a significant increase in women's higher education enrollment, their labor market participation remains structurally lower than that of men due to sociocultural, institutional, and economic constraints.

All of this work converges towards a shared observation: higher education graduates face specific obstacles during their professional integration, obstacles amplified by social norms, biased expectations, and sometimes implicit discriminatory mechanisms. In this context, we formulate the following hypothesis:

**H₁:** *Gender constitutes a major discriminating factor in the professional integration of higher education graduates.*

Second, age and professional experience are major explanatory variables in the analysis of professional integration. According to human capital theory (Becker, 1964), the accumulation of experience helps to strengthen skills, increase individual productivity, and, consequently, improve employability. Within this theoretical framework, age is often considered a proxy for acquired experience, whether formal or informal. In the Tunisian context, young graduates face specific difficulties entering the job market. A recent study reveals that the youth unemployment rate reaches 33.8%, which reflects the structural obstacles faced by first-time job seekers, particularly those with higher education (GIZ, 2020). Furthermore, the World Bank (2022) highlights that wage subsidy schemes, although useful in facilitating entry into employment, mainly offer temporary opportunities without necessarily guaranteeing sustainable integration, particularly for young people.
Thus, despite the theoretically favorable effect of professional experience on employability, the segmentation of the Tunisian labor market — marked by a predominance of informal and precarious employment — tends to limit this advantage for new graduates. These observations lead us to formulate the following hypothesis:

**H2:** *Age has a positive effect on the professional integration of higher education graduates.*

Third, the type of diploma is a central determinant of professional integration, analyzed in the light of human capital theory and the training-job matching approach. Becker (1964) and Vincens (2005) emphasize that not all diplomas are equal in terms of "professional value," with some offering a higher return in terms of employment opportunities. This hierarchy of diplomas is reflected in the integration gaps observed between the different training courses.

Empirical studies, such as those of Giret and Moullet (2008) or Machin and McNally (2007), show that graduates in engineering, computer science, or applied sciences have higher employment rates than their counterparts from literary disciplines or human and social sciences. These results, widely documented in industrialized countries, are also verified in the Tunisian context. Masmoudi and Ferchichi (2024) demonstrate that the employability rate of graduates from ISET du Kef varies greatly depending on the specialty, with technical courses, particularly in engineering, offering better prospects than training in economics or management. Similarly, Stampini and Verdier-Chouchane (2011), in their analysis of the Tunisian job market, show that graduates from scientific and technical fields experience significantly shorter periods of unemployment, confirming the differentiated effect of fields on access to employment. These elements lead us to formulate the following hypothesis:

**H3:** *Type of diploma influences professional integration, with an advantage for technical and scientific training.*

Fourth, regional disparities constitute a structuring factor in the professional integration of graduates in Tunisia. The theory of unequal spatial development (Harris & Todaro, 1970), as well as the contributions of the new geographical economy (Krugman, 1991), explain that the concentration of economic opportunities in certain territories generates lasting gaps in terms of employability.

Recent work, notably that of the Arab Institute of Business Leaders (IACE, 2019), has highlighted the structural advantage of Greater Tunis and the Centre-East compared to the inland regions. These gaps can be explained in particular by unequal dynamics of investment and infrastructure development. The Ministry of Industry (2016) showed that coastal economic hubs benefit from a high concentration of businesses and equipment, contributing to the coastalization of industrial activities.

Territorial disparities in the professional integration of Tunisian graduates remain strongly marked by a concentration of economic opportunities on the coast. According to the Agency for the Promotion of Industry and Innovation (Agence de Promotion de l'Industrie et de l'Innovation APII, 2022), 75% of industrial companies are located in coastal governorates (Tunis, Sousse, and Sfax), while inland regions (Kasserine and Gafsa) attract only 5% of investments. This coastalization has an impact on graduate employment: the unemployment rate reaches 42% in the Southwest compared to 22% in Greater Tunis, according to the National Institute of Statistics (INS, 2023). The World Bankª (2023) highlights that 85% of foreign direct investment (FDI) benefits coastal areas, accentuating the exodus of graduates from the interior to the coast. These imbalances are partly explained by poor infrastructure (transport, internet) in marginalized regions, limiting access to skilled jobs (Hamida, 2024).
In response, the *National Employment Strategy 2023-2025* (Tunisian Ministry of Employment, 2023) provides tax incentives for companies setting up in the interior, with the objective of reducing regional gaps by 15% by 2025. Along the same lines, Hamza Meddeb (2020) highlights the mechanisms of economic and infrastructure concentration in large metropolises, accentuating territorial inequalities in terms of access to employment. Hamida (2024) also highlights that these disparities are evident in access to education: marginalized regions have more limited educational resources, which directly impacts the employability of young graduates. These findings lead us to formulate the following hypothesis:

**H4: Professional integration of graduates varies significantly according to regional disparities, with a marked advantage for large metropolises and coastal areas.**

Finally, the impact of residential environment (urban versus rural) on professional integration is often put into perspective when other explanatory variables are taken into account. The World Bank<sup>b</sup> (2023) has shown that the criterion of urbanization alone does not satisfactorily explain employability gaps, with other structural factors—such as the quality of educational infrastructure and the diversity of the local economic fabric—proving more decisive. Similarly, Dijkstra and Poelman (2021) emphasize that the binary opposition between urban and rural spaces is reductive, calling for an analysis based on more detailed socioeconomic criteria, such as accessibility to services or human capital. In this perspective, Sabry (2024) insists on the need to qualify this opposition by integrating the specificities of local employment policies as well as the dynamics of green transition, which could generate new opportunities in rural areas, notably via emerging sectors such as renewable energies (Lehr et al. 2018). Thus, we formulate the following hypothesis:

**H5: After controlling for individual characteristics, educational credentials, and regional disparities, the residential environment (urban vs. rural) does not significantly influence the professional integration of graduates.**

This enriched theoretical framework allows us to understand the diversity of factors—individual, structural, and territorial—that influence the professional integration of Tunisian graduates. In a job market marked by persistent imbalances, the integration of these different theoretical dimensions allows us to better understand the dynamics underlying the employability of young graduates and to identify relevant levers for developing more equitable and effective public policies.

## Methodology

### Data and Sample

The study is based on secondary data from a survey conducted by the National Institute of Statistics (INS) of Tunisia during the fourth quarter of 2023. This survey, administered by face-to-face interview, collected detailed information from 651 higher education graduates spread across the seven major regions of the country.

The sample selected is the result of a two-level stratified sampling design. First, the districts were divided into strata according to two criteria: governorate and residential area (urban or rural). Then, random sampling was carried out within each stratum to ensure geographical and socio-professional representativeness of the respondents.

The questionnaire used by the INS included several modules covering, in particular:

* Individual characteristics of graduates (age, gender, type and level of diploma, academic background)
* The family and social context

* Geographic location (region, urban/rural area)

* Professional situation at the time of the survey (employment, unemployment, inactivity, sector of activity, type of contract, etc.)

This database constitutes a valuable source for analyzing the employability dynamics of graduates from a regional and demographic perspective.

## Econometric Approach

The analysis is based on probit modeling that estimates the probability of professional integration based on different explanatory variables. The model is written:

$$P(Y = 1|X) = \Phi (\beta_0 + \beta_1 Gender + \beta_2 Age + \beta_3 Education + \beta_4 Region + \beta_5 Urban + \beta_6 Year Degree)$$

Where Y represents employment status (1 if employed, 0 otherwise) and Φ is the standard normal distribution function.

Explanatory variables are:

- Gender: Binary variable (1 = male, 0 = female)

- Age: Continuous variable measured in completed years

- Education: Categorical variable representing the diploma level

- Region: Categorical variable representing the seven geographical regions of Tunisia

- Urban: Binary variable (1 = urban area, 0 = rural area)

- GradYear: Continuous variable representing the year of graduation

## Results

### Descriptive Statistics

Table 1 presents the general characteristics of the sample and the integration rates of Tunisian graduates. The sample is composed of 651 individuals, mostly women (67.9%), while men represent 32.1% of respondents. The average age is 27.4 years, with extreme ranging from 21 to 37 years.

In terms of diploma level, Applied Licenses (32.1%) and Fundamental Licenses (32.4%) are the most common, followed by Masters (15.8%), Engineering Diplomas (8.1%), and Higher Technicians (10.8%). Analysis of professional integration rates reveals an overall rate of 41.9%, with a slight disparity between men (45.9%) and women (40.0%). Regionally, graduates from the Centre-East (57.5%) and the Greater Tunis (56.2%) show the best integration rates, while the lowest rates are recorded in the Northwest (30.2%), the Southwest (30.8%), and the Centre-West (33.7%), highlighting marked territorial inequalities in terms of access to employment.

<table><caption>Table 1: Descriptive statistics of the sample</caption><thead><tr><th>Variable</th><th>N</th><th>%</th><th>Rate insertion (%)</th></tr></thead><tbody><tr><td>Sample size</td><td>651</td><td>100.0</td><td>-</td></tr><tr><td>Gender</td><td></td><td></td><td></td></tr><tr><td>- Men</td><td>209</td><td>32.1</td><td>45.9</td></tr><tr><td>- Women</td><td>442</td><td>67.9</td><td>40.0</td></tr></tbody></table>
<table><tbody><tr><td><strong>Age</strong></td><td></td><td></td><td></td></tr><tr><td>- Average</td><td>27.4</td><td>-</td><td>-</td></tr><tr><td>- Minimum</td><td>21</td><td>-</td><td>-</td></tr><tr><td>- Maximum</td><td>37</td><td>-</td><td>-</td></tr><tr><td><strong>Degree level</strong></td><td></td><td></td><td></td></tr><tr><td>- License Applied</td><td>209</td><td>32.1</td><td>-</td></tr><tr><td>- License Fundamental</td><td>211</td><td>32.4</td><td>-</td></tr><tr><td>- Master or equivalent</td><td>103</td><td>15.8</td><td>-</td></tr><tr><td>- Diploma of Engineer</td><td>53</td><td>8.1</td><td>-</td></tr><tr><td>- Technician Superior</td><td>70</td><td>10.8</td><td>-</td></tr><tr><td>- Others ( Architect, Medicine )</td><td>5</td><td>0.8</td><td>-</td></tr><tr><td><strong>Region</strong></td><td></td><td></td><td></td></tr><tr><td>- Greater Tunis</td><td>105</td><td>16.1</td><td>56.2</td></tr><tr><td>- Center- East</td><td>87</td><td>13.4</td><td>57.5</td></tr><tr><td>- Center- West</td><td>95</td><td>14.6</td><td>33.7</td></tr><tr><td>- Northeast</td><td>76</td><td>11.7</td><td>48.7</td></tr><tr><td>- North- West</td><td>86</td><td>13.2</td><td>30.2</td></tr><tr><td>- Southeast</td><td>111</td><td>17.0</td><td>36.9</td></tr><tr><td>- Southwest</td><td>91</td><td>14.0</td><td>30.8</td></tr><tr><td><strong>Rate global integration</strong></td><td>-</td><td>-</td><td><strong>41.9</strong></td></tr></tbody></table>

*Note: The integration rates correspond to the percentage of graduates in employment at the time of the survey (2023)*

## Probit Model of Professional Integration of Graduates

### a. Estimation of Results

Table 2 below presents the main results of the estimation of the *probit* model on the professional integration of Tunisian graduates, carried out using *Stata*.

<table><caption>Table 2: Results of the Probit model</caption><thead><tr><td>Statistical</td><td>Value</td></tr></thead><tbody><tr><td>Number of observations</td><td>651</td></tr><tr><td>Pseudo R<sup>2</sup></td><td>0.167</td></tr><tr><td>Log -likelihood</td><td>-386,234</td></tr><tr><td>Chi<sup>2</sup> ( ddl = 13)</td><td>154.89</td></tr><tr><td>P-value of the Chi-square test</td><td>0.000</td></tr><tr><td>Hosmer-Lemeshow test</td><td></td></tr><tr><td>- Chi<sup>2</sup></td><td>8,234</td></tr><tr><td>- P-value</td><td>0.411</td></tr><tr><td>Multicollinearity Test (VIF)</td><td></td></tr><tr><td>- Age</td><td>1.24</td></tr><tr><td>- Gender</td><td>1.15</td></tr><tr><td>- Region</td><td>1.32</td></tr><tr><td>- Urban</td><td>1.18</td></tr><tr><td>- Education</td><td>1.28</td></tr><tr><td>Predictive performance</td><td></td></tr><tr><td>- % correctly classified</td><td>71.4%</td></tr><tr><td>- Sensitivity</td><td>68.2%</td></tr></tbody></table>
<table><tr><td>- Specificity</td><td>73.9%</td></tr><tr><td>- Value positive predictive</td><td>67.3%</td></tr><tr><td>- Value predictive negative</td><td>74.6%</td></tr></table>

The results in Table 3 highlight several significant trends. First, the coefficient associated with the constant is negative and statistically significant ($\beta_0$ = -2.341, p < 0.01), indicating an initially low probability of access to employment before taking into account the other explanatory variables. The coefficient associated with the variable Gender (Male) is positive ($\beta$ = 0.237) and statistically significant (p = 0.034), meaning that, all other things being equal, being a man increases the probability of obtaining a job. The marginal effect of 0.059 indicates that this probability is 5.9% higher for men than for women. This result is consistent with signaling theory (Spence, 1973), which posits that gender can serve as an imperfect signal to employers, particularly in contexts marked by stereotypes of availability and stability. It is also aligned with human capital theory (Becker, 1964), which posits that recruiters may anticipate career interruptions or constraints in women, negatively influencing their perceived employability. They also confirm the findings of the literature on inequalities in professional integration between men and women in Tunisia, often attributed to structural and cultural factors limiting women's access to certain employment opportunities (International Labour Organization [ILO], 2022). Hypothesis $H_1$ is therefore validated. Another important factor that seems to influence professional integration is age. Its coefficient is statistically significant (p = 0.003) and positive ($\beta$ = 0.045). An extra year of age raises the likelihood of employment by 1.1%, according to the marginal impact of 0.011. This connection can be explained in the context of human capital theory, which holds that age is frequently linked to a greater amount of experience, even unofficial experience, and improved labor market adaptability. Additionally, the candidate's reputation may be enhanced by recruiters who associate age with greater professional maturity. Thus, hypothesis $H_2$ is confirmed. The urban variable is not significant (p = 0.699), indicating that living in an urban or rural environment has no direct effect on the integration of graduates after controlling for other variables.

These results call for further exploration of the other variables in the model, including education level, region, and year of graduation, in order to refine our understanding of the dynamics of graduates' professional integration in Tunisia and to identify potential disparities depending on the profiles of individuals and their geographical context.

<table><caption>Table 3: Estimated coefficients and marginal effects</caption><thead><tr><td>Variable</td><td>Coefficient</td><td>Standard deviation</td><td>P-value</td><td>Marginal effect</td></tr></thead><tbody><tr><td>Constant</td><td>-2.341</td><td>0.523</td><td>0.000</td><td>-</td></tr><tr><td>Gender ( Male )</td><td>0.237</td><td>0.112</td><td>0.034</td><td>0.059</td></tr><tr><td>Age</td><td>0.045</td><td>0.015</td><td>0.003</td><td>0.011</td></tr><tr><td>Urban</td><td>0.048</td><td>0.124</td><td>0.699</td><td>0.012</td></tr></tbody></table>

b. Typical Effects of the Diploma

The results in Table 4 examine the impact of the level of qualification on the probability of professional integration of graduates, taking the Bachelor's degree as the reference category. The estimated coefficients thus make it possible to compare the effect of Master's, Engineering and Doctorate degrees on access to employment.

The results indicate that obtaining an Engineering degree is associated with a significant improvement in employability compared to a Bachelor's degree ($\beta$ = 0.412, p = 0.013). The marginal effect of 0.103 suggests that holders of an Engineering degree have a
10.3% higher probability of employment than those with a Bachelor's degree, all other things being equal.

Similarly, the Doctorate presents a positive and significant effect on professional integration (β = 0.534, p = 0.035), with a marginal effect of 13.3%, indicating that PhD holders have a higher probability of employment compared to graduates. However, this improvement should be interpreted with caution, as employment opportunities for PhDs may be limited to specific sectors, including higher education and research.

These results confirm the predictions of human capital theory (Becker, 1964), according to which specialized and technical training improves employability due to its relevance to labor market needs. Moreover, signaling theory (Spence, 1973) suggests that technical and advanced degrees send a strong signal to employers about the productivity of candidates. Hypothesis H₃ is therefore validated.

On the other hand, the Master has no statistically significant effect on employability compared to the Bachelor's degree (β = 0.183, p = 0.150). The marginal effect of 4.6% remains positive, but not significant, suggesting that obtaining a Master's degree does not necessarily guarantee a substantial advantage in the labor market compared to a Bachelor's degree. This result can be explained by a possible mismatch between certain Master's courses and the skills actually sought by Tunisian employers, or by a relative saturation of this level in certain sectors.

These results thus reveal that the impact of the level of qualification on professional integration is not uniform. Technical and specialized diplomas, such as those of Engineering, offer a significant advantage in terms of employment, while the effect of the Master's degree seems more limited. They highlight the central role of the training-employment match in the valorization of qualifications, and also reflect the structural preferences of the Tunisian market in favor of technical profiles. Furthermore, although the Doctorate improves employment prospects, it is necessary to examine in more detail the nature of the positions accessible to holders of this diploma, in order to assess whether it is a question of a stable and qualified integration or precariousness in certain academic and professional sectors.

<table><caption>Table 4: Effects by Level of Diploma (Ref: Bachelor's Degree)</caption><thead><tr><td>Diploma</td><td>Coefficient</td><td>Standard deviation</td><td>P-value</td><td>Marginal effect</td></tr></thead><tbody><tr><td>Master</td><td>0.183</td><td>0.127</td><td>0.150</td><td>0.046</td></tr><tr><td>Engineer</td><td>0.412</td><td>0.165</td><td>0.013</td><td>0.103</td></tr><tr><td>Doctorate</td><td>0.534</td><td>0.253</td><td>0.035</td><td>0.133</td></tr></tbody></table>

### c. Regional Effects

The results in Table 5 highlight significant regional disparities in the professional integration of graduates in Tunisia, taking the Greater Tunis region as a reference. The estimated coefficients make it possible to assess the probability of graduates finding employment in different regions compared to this reference region.

First, the results show that the Centre-East does not present a significant difference compared to Greater Tunis (β = 0.052, p = 0.780), which suggests a similarity in terms of employment probability between these two regions. On the other hand, several other regions display negative and statistically significant coefficients, indicating a more difficult professional integration than in Greater Tunis. These results confirm the work on the concentration of economic opportunities in coastal areas and the structural disadvantage of inland regions, where infrastructure and industrial fabric are less developed (Harris & Todaro, 1970). They are also in line with the contributions of the new geographical economy (Krugman, 1991), according to which agglomeration effects and the concentration of services
reinforce the economic attractiveness of certain regional poles, to the detriment of peripheral areas. Hypothesis H₄ is therefore validated.

The Centre-West (β = -0.918, p < 0.01) shows a marked negative effect, with a marginal effect of -22.9%, suggesting that graduates from this region have a significantly lower probability of employment than those from Greater Tunis. The situation is even more worrying for the North-West (β = -1.072, p < 0.01) and the South-West (β = -1.045, p < 0.01), where the marginal effect reaches -26.8% and -26.1% respectively, highlighting significant difficulties in accessing employment for graduates from these regions. These results reflect a real territorial idealization, opposing the dynamic regions of the coastal facade to the inland areas left on the margins of development.

The Southeast also displays a significant negative coefficient (β = -0.784, p < 0.01) with a marginal effect of -19.6%, while the Northeast displays a negative but non-significant coefficient (β = -0.301, p = 0.129), suggesting that graduates from this region do not face as marked a disadvantage as those from other regions, but that their situation nevertheless remains less favorable than in Greater Tunis.

These results highlight significant regional disparities in graduate employment in Tunisia. The country's interior regions, particularly the Centre-West, North-West and South-West, face major employment challenges, which may reflect structural differences in economic opportunities, labour market dynamism and access to resources. These gaps highlight the need for a reconfiguration of land use planning policies and effective decentralization of public and private investment.

These findings highlight the need for targeted public policies to improve the employability of graduates in the most disadvantaged regions and reduce inequalities in access to the labor market. These results can be explained by the fact that employment opportunities are not uniform in urban areas: some cities, although urban, offer few professional opportunities, while some rural regions may benefit from agricultural or specialized jobs. This finding is consistent with the criticisms of the urban/rural dichotomous view, which does not take into account the diversity of local economic contexts (Organization for Economic Co-operation and Development [OECD], 2021). Hypothesis H₅ is therefore validated, as our results show that the residential environment (urban vs. rural) does not significantly influence the professional integration of graduates.

<table><caption>Table 5: Regional Effects (Ref: Greater Tunis)</caption><thead><tr><td>Region</td><td>Coefficient</td><td>Standard deviation</td><td>P-value</td><td>Marginal effect</td></tr></thead><tbody><tr><td>Center- East</td><td>0.052</td><td>0.186</td><td>0.780</td><td>0.013</td></tr><tr><td>Center- West</td><td>-0.918</td><td>0.192</td><td>0.000</td><td>-0.229</td></tr><tr><td>Northeast</td><td>-0.301</td><td>0.198</td><td>0.129</td><td>-0.075</td></tr><tr><td>Northwest</td><td>-1.072</td><td>0.201</td><td>0.000</td><td>-0.268</td></tr><tr><td>Southeast</td><td>-0.784</td><td>0.187</td><td>0.000</td><td>-0.196</td></tr><tr><td>Southwest</td><td>-1.045</td><td>0.197</td><td>0.000</td><td>-0.261</td></tr></tbody></table>

## Model Prediction and Performance

The assessment of the predictive quality of the *probit* model is based on several performance indicators. The percentage of correct classifications is 71.4%, indicating that the model manages to correctly predict the professional integration or non-integration of graduates in approximately seven out of ten cases. Although this rate is satisfactory, it suggests that improvements could be considered to refine the accuracy of the model.

The sensitivity of the model is 68.2%, which means that it manages to correctly identify 68.2% of the employed individuals. In other words, approximately three employed
graduates out of ten are misclassified as unemployed. For its part, the specificity is higher (73.9%), indicating that the model detects unemployed individuals more accurately.

Predictive value indicators complete this analysis. The positive predictive value (67.3%) means that 67.3% of graduates classified as employed are actually employed, while the negative predictive value (74.6%) indicates that 74.6% of individuals predicted to be unemployed are actually unemployed.

Overall, these results show that the model captures the determinants of graduates' professional integration relatively well, with a correct classification capacity above 70%. However, the slightly lower sensitivity than the specificity suggests that the model tends to underestimate graduates' integration into the labor market. Improvements could be made by integrating other explanatory variables, refining the modeling of nonlinear effects, or exploring alternative approaches such as the logit model or machine learning methods to better predict the employability of Tunisian graduates.

## Discussion

The results of this study highlight several factors influencing the professional integration of Tunisian graduates. Probit analysis confirms that variables such as gender, age, and level of education play a significant role in access to employment. Men and graduates with engineering or doctorate degrees benefit from better employability, while master's degree holders do not seem to have a significant advantage over bachelor's degree holders. In addition, regional disparities appear marked: graduates from the interior regions, particularly the Center-West, Northwest, and Southwest, encounter significant obstacles to professional integration compared to those from Greater Tunis.

The evaluation of the model's predictive performance indicates a correct classification rate of 71.4%, with a sensitivity of 68.2% and a specificity of 73.9%. This suggests that the model manages to capture the overall trends in the graduate labor market, although it has a slight tendency to underestimate employment chances. The results also reveal that the structural conditions of the Tunisian labor market, such as the concentration of employment opportunities in certain regions and the unequal valuation of diplomas, strongly influence the professional trajectories of young graduates.

## Conclusion and Recommendations

This study highlights the major determinants of graduates' professional integration in Tunisia and highlights persistent inequalities according to gender, region, and education level. The results obtained from the probit model reveal that age, gender, and type of diploma significantly influence the chances of accessing employment, while regional disparities remain particularly marked, to the detriment of inland regions.

These findings call for more targeted public action to improve the employability of young graduates, particularly in the most disadvantaged areas. From this perspective, several recommendations can be formulated:

* Strengthening the training-employment match: Adapt training content to the realities of the labor market by promoting technical sectors and digital skills.

* Support for regional employability: Develop economic decentralization and territorial development policies aimed at stimulating demand for skilled employment in inland regions.

* Promoting local entrepreneurship: Establish support and financing mechanisms to encourage business creation among young graduates, particularly women.

* Strengthening professional experience: Generalize internship, work-study, and incubation programs in higher education establishments.
**Limitations of the Study**

This research has some limitations that should be highlighted. It is based on cross-sectional secondary data, collected at a given point in time (fourth quarter of 2023), which prevents any analysis of the temporal evolution of career paths. Furthermore, certain key variables, such as professional experience, transversal skills, or professional social networks, could not be integrated due to lack of availability in the database used.

**Avenues for Future Research**

In the future, longitudinal studies conducted over several years could provide a better understanding of the dynamics of professional integration by identifying sustainable trajectories, career changes, or geographical mobility of graduates. In addition, qualitative approaches (interviews, case studies) could complement this analysis by highlighting individual integration strategies and the obstacles perceived by graduates themselves, particularly in marginalized regions. Finally, the integration of more advanced predictive analysis tools (such as multinomial logit models, decision trees, or machine learning algorithms) could enrich the results and improve the accuracy of predictions on access to employment.

**Conflicts of Interest**

The authors declare that he has no conflicts of interest to this work.

**Data Availability Statement**

The data that support this work are available upon reasonable request to the corresponding author.

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