Global Journal of Human Social Science, E: Economics, Volume 22 Issue 3

Constructing this variable in children is easier, unlike parents, who have retrospective information. To face this difficulty, we consider as Pasquier (2010), that the parents who work in the informal sector are those who worked in a micro-enterprise, an associative enterprise. These various enterprises belong either to a household or to the person concerned. The rest is up to the public and the parapublic. Thus, the coding of the institutional sector is carried out in the two generations by a categorical variable comprising the following three modalities: 0 “informal”, 1 “formal private” and 2 “public and parapublic”. Verification of the robustness of the results obtained from this variable requires the construction of variables allowing us to compare the effect of a particular sector of the Ascendant with the two others. In both generations, we therefore construct three variables. First we have “public VS private formal and informal”, then the second “private formal VS public and informal”, and finally the third “informal VS public and private formal”. These variables offer the advantage of isolating the causal effects of the sector of the fathers in the access of their offspring to this same sector. They also make it possible to compare which of the sectors is the most dependent on access to the status of the father. iv. The level of education To take into account the contribution of education in intergenerational mobility, we construct an education variable that takes the following four modalities: 0 "no level", 1 "Primary", 2 "Secondary", 3 "Higher". b) Methodology Since the objective is to analyze the effect of family capital on the professional integration of young graduates in Cameroon, we propose in a first time to use the log-linear models developed from the work of Birch (1963, 1964a, 1964b, 1965), Goodman (1970, 1986), Xie (1992), and Erikson and Golthorpe (1992). Several reasons justify the choice of these models in this study. Besides the fact that all analysis variables are qualitative, log-linear models (unlike the traditional approach of regression models) help to examine simultaneous analysis of coupled relations, taking into account the possibility of analyzing three-way and higher-order interactions between variables. To this end, these models allow, in addition to the intergenerational association of socioeconomic status, to test the way in which this association varies according to the modalities of a third variable: the level of education attained. Consider a contingency table formed by our three variables, O to I modalities, D to J modalities and E to K modalities. Suppose the reference model is the Egalitarian Meritocracy (EM) model. According to Goux and Maurin (1997a), this model is meritocratic. Indeed, it assumes independence between the socioeconomic status of the parent and the level of education attained. It is egalitarian in the sense that the status achieved in the labor market depends solely on the level of education. In other words, this model assumes full equality of opportunity both at school and in the labor market and looks like this: log where OED=(O)(ED) (1) the estimated frequencies of the contingency table, λ = the mean of the logarithms of all the estimated frequencies of the table. The coefficients, respectively represent the specific effects of level 1 which measure the deviation from the mean linked to the variables O, D and E. The coefficient, measures the level 2 association between E and D which represents the hypothesis that professional integration and more precisely, the destination on the labor market depends on the level of education attained. Following the estimates by the maximum likelihood method, several tests are carried out. They make it possible to determine whether the estimated frequencies are not significantly different from the observed frequencies. An additional interaction will be introduced if the frequencies are statistically different. This modeling aims to determine by addition (backward), or deletion of the interaction parameters. This parsimonious model satisfactorily reproduces the table of observed frequencies. If the estimated frequencies obtained from model 1 are statistically different from those of the empirical contingency table, an interaction between O and E noted should be introduced. This introduction leads to the Inegalitarian Meritocracy (IM) model. It thus assumes the presence of inequalities in educational opportunities. This representation is written: Log where OED= (OE)(ED) (2). If the observed data are not faithfully reproduced by model (2), we introduce an additional denoted parameter that measures the association between the socioeconomic status of an individual's parent and his or her in the labor market. Log (3) where OED=(OE)(ED)(OD) This model, commonly called the model of constant association or absence of interaction with three variables, assumes the presence of inequalities of opportunity in the labor market that are rigorously constant with the level of education. It also assumes an investment by each family in the positioning of its child on the labor market. Indeed, according to this model, all the odds ratios which measure the intergenerational statistical association obtained are constant with the level of education. Estimated with (I-1) (J-1)(K-1) degrees of freedom, this model implies that the inertia linked to the levels of education painted by this model can distort reality even when this model turns out to be close to the data. Indeed, if this model reproduces the data of the empirical contingency table in an acceptable manner, it is still necessary to test the difference between it and the saturated model. Indeed, several © 2022 Global Journals Volume XXII Issue III Version I 7 ( ) Global Journal of Human Social Science - Year 2022 E Family Capital and Professional Integration of Young Graduates in Cameroon