




































AMERICAN ECONOMIC & SOCIAL REVIEW 12(1) (2023), 1-9 

1 

 

 

    ECONOMIC & SOCIAL REVIEW  

                                                               AESR VOL 12 NO 1 (2023) P-ISSN 2576-1269  E-ISSN 2576-1277 
                                                  

   Available online at https://www.cribfb.com 

                                                                                                                                    Journal homepage: https://www.cribfb.com/journal/index.php/aesr 
                                                                                                                                                                                             Published by CRIBFB, USA 

SOCIAL CAPITAL, EDUCATION AND CHOICE JOB SEARCH 

METHODS IN SENEGAL        
 

 Mame Sangone Diop (a)    Latif Dramani (b)1  
 

(a) Economist & Researcher, University Iba Der Thiam of Thies, Senegal; E-mail: sangonebby@gmail.com 
(b) Professor, University Iba Der Thiam of Thies, Senegal; E-mail: Latif.dramani@gmail.com 

 

 
A R T I C L E I N F O 

 
 

Article History: 
 

Received: 9th August 2023 

Revised: 20th October 2023 
Accepted: 28th October 2023 

Published: 7th November 2023 

 
Keywords: 

Social Capital, Well-Being, 

Education, Job Search, MLM 

 
      JEL Classification Codes:  

 
      A13, I31, I21, D90, C51 

 

 

 

 

 
A B S T R A C T 
 
The objective of this paper is to analyze the microeconomic impact of education on well-being, as 
measured by social capital in terms of the different means used to search for a job in Senegal. The 

endogenous variable (social capital) is categorized into four sub-modalities represented as follows: « 

Personal relations », « Advertisements-firms » composed of advertisements/media/internet and 

applications to firms; « Agencies-State » composed of the civil service, the employment office, private 

placement agencies and competitions/tests; and « Other » composed of the search for partners, the 
search for financing or any other means. The exogenous characteristic variables are: the different levels 

of education (primary, middle, secondary and higher), the gender, the age and the marital status of the 

individuals aged at least 15 years. The data come from the ANSD's (2020) Senegal Poverty Monitoring 

Survey database on a sample of 168,203 individuals. Using Stata, the results obtained through 

estimation by the multinomial logistic method (MLM) show that only higher education has a positive 

and significant impact on all the means used to look for a job in Senegal, but at different levels and 

probabilities. This article suggests a strong expansion of networks of acquaintances and mutual aid, 

because the higher the individual's social capital, the more chance he has of interacting with others, 
broadening his contacts and improving his well-being. Combined with a higher level of education, it 

offers job-seekers more opportunities to succeed in their search. 

 
 

© 2023 by the authors. Licensee CRIBFB, USA. This article is an open access article  distributed 
under the terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0/). 

                                                                                   

 

INTRODUCTION 

Social capital is developed wherever it is possible to establish social ties, in other words in social spaces such as the family, 

the community and civil society as a whole. It contributes to crime reduction, better health, the achievement of educational 

goals, government effectiveness, economic performance, etc. In this article, social capital is used to describe well-being as 

the characteristics of social organization, such as trust, norms and networks, which can improve the efficiency of society by 

facilitating coordinated action. As for education, it is seen as a factor in social fulfilment for individuals, and in promoting 

competitiveness and innovation for a country's economic development. Logically, it can promote the dynamics of human 

capital accumulation, since a high stock of knowledge resulting from education remains a source of innovation and a 

prerequisite for economic growth and well-being, hence the interest of our subject. 

However, this link between education and well-being in Senegal has shown a low level of development in terms 

of the quality and quantity of its human capital, as well as a training system that offers minimal opportunities in terms of 

making it easier to find a job. It is now accepted that in Senegal, in addition to obtaining a degree, you need to join networks 

or be in contact with one of the members of a network to be able to broaden your field and your job search opportunities. 

Yet one of the major functions of welfare is to satisfy the needs of the population, which is not the case at present because 

of poor access to higher education and poorly structured social networks. These difficulties mean that the region needs to 

equip itself with sufficient quality human resources at a higher level, as well as fostering social links. To achieve this, it is 

important to answer the following question: what is the impact of each level of education on the different means used to 

look for a job in Senegal? On the basis of the answers, different contributions can be made, which will improve the level 

and quality of education in Senegal and therefore well-being. In addition, knowing the relationship between education and 

                                                      
1Corresponding author: ORCID ID:0000-0002-6336-6179 

© 2023 by the authors. Hosting by CRIBFB. Peer review under responsibility of CRIBFB, USA.  
https://doi.org/10.46281/aesr.v12i1.2112 

 

To cite this article: Diop, M. S., & Dramani, L. (2023). SOCIAL CAPITAL, EDUCATION AND CHOICE JOB SEARCH METHODS IN SENEGAL. 
American Economic & Social Review, 12(1), 1-9. https://doi.org/10.46281/aesr.v12i1.2112 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://doi.org/10.46281/aesr.v12i1.2112
https://orcid.org/0000-0002-6336-6179
https://orcid.org/0000-0001-6178-875X


Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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well-being means that the level of education can be taken into account when assessing well-being, and can serve as an 

implication for economic and employment policies. 

The aim of this article is to analyze the microeconomic impact of education on well-being as captured by social 

capital, measured by the different means used to look for a job in Senegal. More specifically, the aim is to see how the level 

of education (primary, intermediate, secondary or higher), gender, age and marital status impact on personal relationships, 

company advertisements, state agencies and all other means used to look for a job. 

In writing this article, in addition to the introduction, which sets out the context and the rationale, outlining the concepts 

around the notion of well-being, education and social capital, addressing the problem and posing the research question, we 

then carried out a literature review to establish the research methodology. Finally, we discuss the results obtained using the 

multinomial logistic method, before drawing a conclusion. 

 

LITERATURE REVIEW 

The concept of social capital is certainly seductive, but still encounters certain criticisms, the most pertinent of which 

concern methodological weaknesses with a view to its empirical application. While there is now a consensus on the 

definition of social capital, its dimensions are still the subject of numerous methodological debates, which seem to be more 

of an intellectual race. Thus, knowing the microeconomic impact of education on well-being makes it possible to appreciate 

and understand how each level of education behaves in relation to each means used to seek employment. 
 

The relationship between education and social capital 
 

Sorin (2010) extending social capital into adult education gave a brief review of the definition of social capital by some key 

authors (Coleman, Putman, Fukuyama), before quoting Bourdieu (1997) who states that social capital is part of the 

explanation for the persistence of class inequalities based on unequal resources of economic and cultural capital. First, he 

echoed Putman (1995), Emler and Frazer (1999) and Van Deth and Maraffi (1999) to show that educated people tend to 

participate more in voluntary associations, have a greater interest in politics and are more civically engaged. Referring to 

the work of Nie (1996), which shows that "educated people are more inclined to trust others, in institutions, to connect with 

different groups and to be civically involved in the community", he asserted that education is a good predictor at the 

individual level, being even more important than other factors such as: age, material conditions, gender etc.... Finally, to 

demonstrate the direct and indirect positive impact of education on social capital, he draws on Bynner and Ashford (1994) 

and Emler and Frazer (1999) who point out that "the rate of civic participation suggests that education has a direct positive 

impact on civic and political association, through the acquisition of cognitive resources, knowledge and useful skills, as well 

as indirectly through access to high-level jobs". Sorin shows us here that education is a powerful generator of social capital. 

Kamanzi and Trottier (2010) examining the extent to which the probability of access to permanent employment after post-

secondary graduation is associated with the social capital that an individual is able to mobilize, refer to Burt (1995), who 

defines "social capital as the set of relationships between friends and colleagues, as well as with other people, that enable 

the investment of various forms of capital (financial, cultural, etc.)", to show that the creation of social capital is associated 

with the creation of a permanent job, to show that the creation of new contacts beyond the immediate social circle extends 

the social information network and thus enriches social capital. Then, to show that social capital has the same properties as 

other forms of capital, they draw on Robison (2002), who state that: social capital can be combined with other forms of 

capital (human, financial, economic or cultural) to meet needs of a social or economic nature (transformation capacity). 

Social capital is a means of mediating the creation of other resources (ability to create other capital), either for its own 

extension, or for the acquisition of other forms of capital (human, financial, economic or physical). Social capital is obtained 

through the investment of other resources (investment opportunities). Finally, Granovetter and Lin (1973; 1982), Ensel and 

Vaughn (1981), show that although education remains an indispensable tool in the search for a job, social relations and an 

individual's initial social position play an important role in the race for the best jobs.  Here, Lin (1995; 2000), point to two 

types of social capital: "latent social capital", which refers to the social networks to which an individual belongs without 

necessarily having chosen them, and which he or she can call upon to achieve goals, and "mobilized social capital", which 

refers to the deliberate choice made by an individual in order to find a job of social contacts and their mobilization to achieve 

its objectives. Dupray and Vignale (2019), studying the conditions for a return at the start of working life, to the department 

of residence at the baccalaureate, for young people who left it during their higher education (what the territory says about 

the influence of social capital), call on Wagner (2007), who states that "geographical mobility is conceived as a spin-off of 

families social and cultural capital, and as a means of extending social and symbolic resources, in the case of international 

mobility, this is more the preserve of the upper classes", to show that the experience of geographical displacement could 

thus confer on individuals a capacity to emancipate themselves from ties of attachment to a territory, especially as its 

repetition in the trajectory limits the length of local registration necessary for the construction and mobilization of localized 

social capital. Then, through Hinton (2011), who showed that "the convergence of profiles should be all the more evident 

when we focus on young baccalaureate holders living in sparsely populated urban areas and conducive to the activation of 

localized social capital", Dupray and Vignale stipulate that geographic mobility was conceived more as a distancing in the 

absence of adequate nearby educational infrastructures or a strategy for accessing other opportunities for mobilizing 

economic and cultural capital. To conclude, they refer to Forse (2001), Rosvall, Rönnlund, and Johansson (2018), who have 

shown that "neighborhood networks for access to employment or education are particularly valued by the least qualified 

individuals and those residing in rural communes or small towns", to highlight the importance of social determinants and in 

particular the existence or absence of ties to family and friends in geographic mobilities. In short, we can conclude that 

geographic mobility leads to the creation of ties of attachment to a territory, which inhibits the mobilization of localized 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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social capital, even though the latter would make certain return mobilities intelligible, in this case those involving returns to 

territories that appear unattractive, particularly in economic terms. 

Three important points emerged from this review: 

 Firstly, education is an indispensable tool in the job search, and that an individual's social relations and initial social 

position play an important role in the race for better jobs. 

 Secondly, that education is a powerful generator of social capital, and that family social capital has an impact on 

school performance.  

 Finally, that there are two types of social capital: "latent social capital" refers to the social networks to which an 

individual belongs without necessarily having chosen them, and which he or she can use to achieve goals, and 

"mobilized social capital" refers to the deliberate choice of social contacts and their mobilization to achieve goals. 
 

Social Capital as a Measure of Well-Being  
 

Forse (2001), seeking to demonstrate the importance of social capital on job search, uses data from the "Emploi" survey 

carried out on a French sample of 150 000 individuals of working age. The endogenous variable is an indicator composed 

of personal approaches (family relationships, other personal relationships, competitions, classified ads, ANPE, school, 

contacted directly by the employer, business start-up, other) and the exogenous characteristic variables (social origin, level 

of education, profession and income) in order to approximate the intervention of social capital in the status acquisition 

process. The results, obtained using a logit model, show that education level has a significant effect on the use of social 

capital (chi-square = 166.69, ddl = 8, p < 0.001). The lowest levels of education mainly choose family and to a lesser extent, 

other personal relationships. Intermediate levels make the least use of their network, while higher education graduates prefer 

contacts made with an employer or as part of their training. Kamanzi and Deblois (2007) seeking to examine the extent to 

which the probability of accessing permanent employment after graduation from a post-secondary institution is associated 

with the social capital an individual is able to mobilize, performs a secondary analysis of data from the 1995 National 

Graduates Survey conducted by Statistics Canada in 1997 on a sample of 61 759 graduates. 43 040 selected candidates 

responded to the questionnaire. The dependent variable was permanent employment, while the independent variable was 

mobilized social capital, grouped into four categories: 1) placement office or service, response to an ad in the newspaper, 

Internet or other sources; 2) family member, friend or teacher; 3) current employer and 4) previous employer. As control 

variables, they took human capital (level and field of study as well as work experience), job structure (the sector of the job 

held and the link between training and employment) and the individual's social characteristics (gender and age). The results 

obtained through binary logistic regression show that level and field of study, as well as professional experience, exert a 

significant influence on the probability of access to permanent employment. In additional, job-seeking graduates who 

obtained information from public sources (employment office or service, newspaper, internet, etc.) were relatively more 

likely to find a permanent job. Nouzha and Outtaj (2020) estimating the return on education in the Moroccan labor market, 

uses the 2011 National Employment Survey (NES) database, for a sample of 14 554 corresponds to the size of the employed 

labor force. The recoded salary variable, discretized into 5 classes of equal amplitude, was chosen as the endogenous 

variable, with seniority class, age, gender, marital status and degree as the independent variables. The results obtained 

through multinomial logistic regression confirm a positive relationship between formal education, on-the-job training, 

lifelong learning and the level of wages received by an individual.  
 

 

MATERIALS AND METHODS 
Theoretical Framework of the Model  

 

Several approaches and theories have been mobilized to address the central problem. The approach adopted is identical to 

that used by Forse (2001) in his research on the "specific role and growth of social capital". More specifically, the aim is to 

show that the type of network used to look for a job is mainly correlated with the individual's level of education. The 

theoretical framework chosen is a multinomial logistic regression model (MLM), where we wish to model the interactions 

that exist between a categorical dependent variable with more than two modalities Yi and a vector of random variables X= 

(X1......Xk). Its generic form is given by the following expression: 

 

Yi = βjXik + Σij        (1) 
 

With Xik: the feature matrix; Βj: the feature-related coefficient matrix and Σi: the error term. 

Model Specification  

We observe a sample of (n) individuals divided into (j) possible categories, and each individual (i) belongs to one of the j 

possible categories. It is described by a set of (K) characteristic variables Xi1, Xi2,..., Xik as in the work of Forse (2001) and 

Kamanzi and Deblois (2007). Our model is based on the idea that: the probability that a graduate i, given his characteristic 

variables Xik, belongs to a possible category j having used personal relationships as a means to look for a job is supposed to 

depend on Xik or on a linear combination of Xik. To differentiate ourselves from the work of Nouzha and Outtaj, our research 

is specified on the one hand by characteristic variables (level of education, age, gender, marital status) relating to individuals 

aged at least 15 and on the other hand by the endogenous variable "means used to look for a job". The model will be 

estimated using multinomial logistic regression to measure the impact and significance of each level of education on the 

different means used to find a job in Senegal. The data used come from the database of the National Agency for Statistics 

and Demography (NASD), yet the Senegal Poverty Monitoring Survey (SPMS) is based on a sample of 168 203 individuals. 
 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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The model is specified as follows 
 

                

                                    0     Personal relationships 

 1 Advertisements-Companies (Advertisements/Media/Internet; Application to companies) 

Yi =               2   Agencies-State (Civil service; Employment department; Private employment agency; 

Competitions/Tests) 

                 3     Other (Partner search; Funding search; All other means) 

 

The probability that an individual i, given his or her characteristics Xik, belongs to the possible category j, having used all 

four modalities to look for a job, can be written as follows: 
 

P(j Xi)⁄ = G (β0X0 + β1X1 + ⋯ βkXk)= G (Xiβj)        (2) 

 

The difficulty is to find a functional form G such that each quantity P (j/xi) is a probability, i.e. has the following two 

properties: 

  0 < P (j/𝑥𝑖) > 1   et    ∑ 𝑃(𝑗/𝑥𝑖) = 1
𝑗
𝑖              (3) 

 

 

To ensure strict positivity, let's take the exponential form: 
 

                P (j/𝑥𝑖) = e𝑥𝑖𝛽𝑗                                  (4) 

 

But this quantity can take on values greater than 1. It is normalized by the sum of exp (xiβi). The model is written : 
 

  P (𝑗/𝑥𝑖) = 
𝑒𝑥𝑖𝛽𝑗

∑ 𝑒𝑥𝑖𝛽𝑗𝑗
𝑖

  for  j = 0,1,……..j                (5) 

 

The general expression of the final regression model is therefore written as follows: 
 

P(𝑌 = 𝑗/𝑋) =
𝑒

𝛽𝑗𝑋𝑖

1+∑ 𝑒
𝛽𝑗𝑋𝑖𝑗−1

𝑗=0

   for j = 0,1 … 3           (6) 

 

With  𝛽𝑗𝑋𝑖 = 𝛽1𝑙𝑒𝑣_𝑖𝑛𝑠𝑡𝑟𝑢𝑐𝑡𝑖 + 𝛽2𝑎𝑔𝑒𝑖 + 𝛽3𝑠𝑖𝑡_𝑀𝑎𝑡𝑟𝑖𝑚𝑜𝑛𝑖𝑎𝑙𝑖 + 𝛽4 𝑠𝑒𝑥𝑒𝑖 

 

Note: The « personal relations » modality will be taken as the reference. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

5 
 

RESULTS 

Model estimation 

Following model estimation using Stata software, the following results are obtained. 

 

Table 1. Coefficient of multinomial logistic Regression 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 
 

 
 

Source: author based on MLM estimation results in Stata 

Note: *, ** and *** indicate the degrees of significance of the regression coefficients at 10%, 5% and 1% respectively 
 

Interpretation of Results 

With regard to the « company advertisements » modality, which is made up of media-internet advertisements and 

applications to companies, the level of education variable shows that individuals with an elementary education use it less to 

look for a job, compared to those with an intermediate, secondary or higher education. The finding shows that the higher 

the individual's level of education, the greater the likelihood of using company advertisements (0.18 for average; 1.64 for 

secondary and 1.85 for higher). Compared with "personal relationships" as the reference modality, the results show that 

primary school students are more likely to use personal relationships than business advertisements, and that middle, high 

school and higher education students are more likely to use business advertisements than personal relationships when 

looking for a job. Compared to male job seekers, the fact that the job seeker is a woman increases the likelihood of using 

business ads more than personal contacts. Similarly, the older the job seeker, the lower the probability of using business-to-

business advertising (1.18; 0.46; -1.96 ; -25.93). Individuals aged between 30 and 49, compared with those under 30, have 

a higher probability of using business advertisements rather than personal relationships, while those aged 50 to 60+ have a 

lower probability of choosing business advertisements, and make greater use of personal relationships. In addition, 

jobseekers who are single or widowed have a higher probability of using job ads rather than personal relationships, while 

those who are married, divorced or in a common-law relationship are more likely to use personal relationships and less 

likely to use job ads in their job search. 

With regard to the « state-agencies » modality, comprising the civil service, the employment office, the private 

placement agency and the Concours/test, the level of education variable shows, with different probabilities, that an 

individual can use this modality (state-agencies) to look for a job, regardless of the level of education attained. The finding 

shows that high-school graduates have a higher probability (2.59) of using state agencies to look for a job, compared to 

primary (0.45), middle (0.95) and higher (1.52) school graduates. Compared with "personal relations" as the reference 

modality, the results show that, whatever the level of education attained, individuals make more use of state agencies than 

of personal relations to look for a job. Compared to male jobseekers, the fact that the jobseeker is a woman increases the 

Multinomial logistic regression    

                                                                                             Number of obs =      119253 

                                                                                                             LR chi2(45)      =      . 

                                                                                                             Prob > chi2      =      . 

                                                                                            Pseudo R2        =      0.1856 

Log likelihood = - 97845.229 

 

Independent variables 

Dependent variable: means used to find employment: the « personal relations » 

modality is taken as the reference modality. 

Company-ads  State-agencies  Others 

Coef Coef Coef 

Lev-instruction 

 

Primary  

Middle 

Secondary 

Higher 

 
 

-3.386762*** 

.1883683*** 
1.646289*** 

1.858117*** 

 
 

.4568449*** 

.9585309*** 
2.597339*** 

1.521009*** 

 
 

-.3795685*** 

-.2196879*** 
.0167717 

.3511608*** 

Sexe 

 

Male (base) 

Female   

 
 

 

1.37479*** 

 
 

 

.3518313*** 

 
 

 

-.189192*** 

Age 

 

-30 ans (base) 

30-39ans 

40-49ans 

50-59ans 

60ans et plus 

 
 

 

1.187831*** 
.4694905*** 

-1.961951*** 
-25.93686*** 

 
 

 

.3830415*** 
-1.633581*** 

-20.45673*** 
-23.14468*** 

 
 

 

-.0757514** 
-1.52931*** 

.1558382*** 

.7399174*** 

Sit-matrimonial 

 

1st wife   

2 wives/2nd wife    

3 wives/3rd wife               

Single   

Widowed   

Divorced   

Cohabiting/common-law 

 

 

-20.52326*** 
-.1064832** 

-25.79717*** 

.5464185*** 
2.153531*** 

-.8483453*** 

-1.096479*** 

 

 

-.4597964*** 
-1.484107*** 

-25.68436*** 

-.2386319*** 
-17.84218*** 

-.5154744*** 

23.12146*** 

 

 

1.904159*** 
1.113398*** 

3.872747*** 

.0714975* 
1.182533*** 

.7750316*** 

.4792897*** 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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probability of using state agencies rather than personal contacts. Similarly, the older the job seeker, the lower the probability 

of using state agencies (0.38; -1.63; -20.45; -23.14). Individuals aged between 30 and 39 compared with those under 30 are 

more likely to use state agencies than personal relationships, while those aged 40 to 60+ are less likely to choose state 

agencies and more likely to use personal relationships. On the other hand, jobseekers in a common-law relationship have a 

higher probability of using state agencies rather than personal contacts, unlike those who are married, divorced, single or 

widowed, who prefer personal contacts to state agencies in their job search. 

For the « other » modality, made up of partner search, funding search and all other means used, the level of 

education variable shows that primary and intermediate level individuals use it less to look for a job, compared to those with 

a higher level of education. Secondary level is not significant (Prob = 0.746). Compared with "personal relationships" as 

the reference modality, the results show that primary and middle school students use personal relationships more than other 

means to look for a job, while high school students use other means more than personal relationships. Compared to males, 

the fact that the job seeker is a woman increases the likelihood of using personal contacts more than other means. Similarly, 

the older the job seeker, the greater the probability of using other means (-0.75; -1.52; 0.15; 0.73). Individuals aged between 

30 and 49 compared with those under 30 have a higher probability of using personal relationships rather than other means, 

while those aged 50 to 60+ have a higher probability of choosing other means and make less use of personal relationships. 

In addition, whatever their marital status, jobseekers have a higher probability of using other means rather than personal 

relationships, but married (1.90; 1.11; 3.87) and widowed (1.18) people use other means more, compared with single (0.07), 

divorced (0.77) and common-law (0.47) people. 

 

DISCUSSIONS 

The « level of education » has effects on every means used to look for a job. We find that jobseekers in primary, middle and 

secondary school make more use of « state agencies » than of « company advertisements » and « other means ». Higher-

level jobseekers made more use of "company advertisements" than of "state agencies" and "other means". The results 

therefore show that the higher an individual's level of education, the more he or she prefers company advertisements in their 

job search. On the one hand, the fact that jobseekers at primary, intermediate or secondary level make more use of "state 

agencies" can be explained by the fact that the positions to be filled are usually advertised, and that there are generally 

specific needs for each level. On the other hand, the fact that individuals with a higher level of education make more use of 

"company advertisements", made up of advertisements/media/internet and applications to companies, can be explained by 

the fact that the higher the individual's level of education, the more he or she has the opportunity to familiarize themselves 

with new information and communication technologies, which enable them to be aware in real time of any offers and calls 

for applications. Our findings are confirmed by Cisse (2005) with data from Quid 2001, where he shows that a higher level 

of education increases the chances of seeking and finding employment. These results have important implications in terms 

of education and guidance policies. Indeed, the estimation has shown the contributions of each level of education on which 

governments could act. In our case, the actions to be taken must be geared towards achieving higher levels of education and 

prioritizing the higher level, since the latter favors the individual over all the means used to seek employment. These actions 

require, firstly, a generalization of the education system, secondly, an effective fight against drop-outs and repetition, and 

thirdly, a match between the supply of training and the demand on the job market. Such approaches are necessary to facilitate 

the link between education and employment. However, they remain a long-term solution involving the contribution of the 

state and educational development bodies. 

The « Gender » has an effect on every means used to find a job. The fact that the job seeker is a woman has a 

positive impact on "company ads" and "state agencies". On the other hand, this impact becomes negative if the job seeker 

uses "other means" (partner search, funding search, etc.). The results show that women prefer company ads and state 

agencies to other means of job search. This shows that women, compared to men, use almost (2/3) of the means proposed 

to look for a job. This may be explained by the fact that, unlike men, women are less inclined to take risks and prefer to rely 

more on formal job-seeking channels. These results are in line with the policies implemented to promote women's 

emancipation: promotion of women's rights, equity and equal opportunities, preference for female candidates and the 

granting of quotas for certain job offers, etc. These policies mean that women are now more likely to seek and obtain 

employment than men. Gakou and Kuepie (2008) confirm our results, indicating that the education of Malian women clearly 

increases their probability of entering the formal sector, and that for all individuals who have reached secondary school 

level, the proportion of women in the formal sector exceeds that of men. Boutin (2010) finds the opposite to be true, revealing 

that at equal levels of education, men compared to women are more likely to be employed. These results have important 

implications in terms of equal opportunity policies. In fact, the estimation enabled us to identify the impact of each gender 

on the different means used to seek employment. In our case, the actions to be taken should be more geared towards equity 

and equal opportunities in the job offer. Action to achieve this objective requires a fair policy that discriminates between 

men and women with equal qualifications and skills. Such an approach is necessary to promote parity and equal employment 

opportunities. 

The « age » bracket has an effect on every means used to look for a job. If age is between 30 and 39, jobseekers 

make more use of "company ads" and "state agencies" than of "other means". If their age is between 40 and 49, they make 

more use of "ads-companies" than of "state agencies" and "other means". And if age is between 50 and 60+, they use "other 

means" more than "company ads" and "state agencies". The results therefore show that the older the jobseeker, the more 

likely he or she is to use "other means", unlike younger jobseekers who prefer "company ads" and "state agencies". This can 

be explained by the fact that older people are often unable to look for a job in fields where age is a selection criterion (civil 

service, competitive examinations, company applications, etc.). This is why they usually make more use of "other means". 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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Our result is confirmed by Adair and Bellache (2014) where they show that older individuals are more likely to work as 

self-employed in contrast to younger ones. 

As for « marital status », it has an effect on every means used to search for a job. Single or widowed jobseekers 

make more use of "job ads" and "other means" than of "state agencies". If they're married or divorced, they make more use 

of "other means" to the detriment of "company ads" and "state agencies". And if they're in a common-law relationship, they 

make more use of "state agencies" and "other means" than "business ads". The results show that whatever the individual's 

marital status, using "other means" to look for a job can be a choice. This can be explained by the fact that the "other means" 

used to search for a job do not usually have discriminatory criteria in relation to the individual's marital status. The finding 

shows that singles and those in common-law unions, respectively, direct their job search towards "ads-companies" and 

"agencies-state", this can be explained by the fact that the latter are often young people, thus meeting the age criterion once 

imposed by these means. The fact that married people prefer other means of seeking employment is explained by the fact 

that this means offers more opportunities and is not based on periodic job offers. Our result is in line with those Njikam and 

Mwaffo (2005) found in Cameroon and those Adair and Bellache (2014) found in Algeria, showing that being married 

significantly increases the probability of accessing a job. They explain this result by the fact that married people, facing 

more intense social pressure, have a more active job search than single people. 

Generally speaking, our results confirm that individuals with a higher level of education are able to use each of 

these three modalities to look for a job, but with different probabilities (1.80 for ads-companies; 1.52 for agencies-state; 

0.35 for others). This shows that the higher an individual's level of education, the more likely he or she is to join networks, 

expand his or her address book and interact with others. The creation of these new contacts beyond the immediate social 

circle, enables the higher-level individual to extend his or her social network and consequently obtain information, support 

and guidance that is nowadays a crucial element in the job search process. 
 

CONCLUSIONS 

The apprehension of well-being through social capital, measured by the different means used to seek employment, does not 

seek to replace the more traditional forms of appreciation of well-being, but rather offers a complementary form of 

appreciation by focusing on each level of education and the advantages it presents for the individual in terms of choice over 

the different means used to seek employment. Social capital cannot be confused with human capital insofar as the latter 

concerns wealth acquired in isolation and individually, whereas social capital by definition requires interaction and exchange 

between people in the context of a socialized life : Sibony (2016).   

Through estimation by the multinomial logistic method, the main results of this paper are noted as follows:  

 The primary level is globally significant and impacts positively on "agencies-State" but negatively on "ads-

companies" and "others" ;  

 The middle level is significant overall, and has a positive impact on "ads-companies" and "government agencies", 

but a negative impact on "others"; 

 The secondary level has a positive and significant impact on "ads-companies" and "government-agencies";  

 The higher level has a positive and significant impact on all the means used to look for a job. 

Relying on "personal relationships" as the reference modality, the results show that individuals at primary level make more 

use of personal relationships rather than company advertisements, while those at middle, secondary or higher level prefer 

company advertisements rather than personal relationships to look for a job. Compared to the "state-agencies" modality, the 

results show that whatever the level of education obtained, individuals make more use of state-agencies than of personal 

contacts to look for a job. Compared with the "other" modality, the results show that individuals with primary or intermediate 

education make more use of personal contacts than of other means to find a job, while those with higher education prefer 

other means to personal contacts. 

Overall, the results show that only the higher level has a positive and significant impact on all the means used to 

find a job, albeit at different levels and probabilities. To maintain the positive impact of this level, we recommend on the 

one hand increasing the resources allocated to the higher level in order to generalize and modernize it further. However, a 

significant proportion of these resources should be allocated to universities to strengthen their accommodation capacities 

and working conditions (teachers, students), to disadvantaged areas to correct inter-zonal disparities in terms of logistics 

(higher structures), but also to fight effectively against repeaters and dropouts. And secondly, to introduce support policies 

that require parents or guardians to invest more in their children's education, right up to the baccalaureate or at least a 

university degree. To succeed in this challenge, the State and the structures and bodies responsible for developing the 

education system need to define and map out real routes to guarantee everyone access to higher quality education.  

In short, while social capital is recognised as an essential microeconomic component in the measurement of well-

being, it suffers from significant limitations as a measure, as it incorporates characteristics of social organisation such as 

trust, norms and the structuring of networks, but leaves out the nature of the relationship that an individual must maintain 

with society in order to live harmoniously. Future research could analyse the impact of family social capital on an 

individual's educational success. 

 
 

 

Author Contributions: Conceptualization, M.S.D. and L.D.; Methodology, M.S.D.; Software, M.S.D.; Validation, M.S.D. and L.D.; Formal Analysis, 

M.S.D.; Investigation, M.S.D.; Resources, M.S.D.; Data Curation, M.S.D.; Writing – Original Draft Preparation, M.S.D.; Writing – Review & Editing, 

M.S.D.; Visualization, M.S.D; Supervision, L.D.; Project Administration, M.S.D. Authors have read and agreed to the published version of the manuscript. 



Diop & Dramani, American Economic & Social Review 12(1) (2023), 1-9

  

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Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 

groups or sensitive issues. 

Funding: The authors received no direct funding for this research. 

Acknowledgments: Support of CREFAT (This research center for applied economics and finance). 

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest. 

 

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