# **3. Previous literature’s take on why teenagers drop out of school**

The analysis of the determinants of school drop-out in developed countries has highlighted factors such as drug use, alcohol consumption, and parents' psychiatric disorders, controlling for possible confounding factors such as socio-economic status of the family, gender, race, and age of the child.<sup>1</sup> For developing countries, most often the trade-off between school and child labor has been underlined, with fewer studies concentrating just on the determinants of school performance.<sup>2</sup> In terms of method, earlier studies modeled the probability that the child would work or, in alternative, attend school, estimating a logit model.<sup>3</sup> Underlying this approach was, in some cases, the idea that school attendance and child labor are mutually exclusive activities—if the child is working, (s)he is not attending school and vice-versa. In other cases, work was included among the exogenous factors explaining school performance. Results suggested that poverty, as captured for example by the number of siblings or the work status of the father, is a determinant of child labor and of poor school performance.

Later studies acknowledged the possibility of combining work and school, in particular in countries where school lasts just half-day. One method followed was the estimation of a multinomial logit model involving four possible states: specialization in school; specialization in labor; combination of both activities; or inactivity.<sup>4</sup> Other authors accounted for the interdependence of the two decisions by estimating bivariate probit models. This allows, not just for an easy direct comparison of the impact of each variable on the probability of working and of studying, but also for the quantification of the non-explainable correlation between the two decisions, associated with unobserved factors.<sup>5</sup> Both of these methods assume that the decisions on school and work are taken simultaneously. In the same vein, Rosati and Rossi (2003) estimated a simultaneous model of school attendance and hours worked. Some of the results in this literature, though not completely consensual, are: older children and males are more prone to

> 1 See for example Chatterji and DeSimone (2005), Roebuck et al (2004), and Farahati et al (2003).

> 2 School performance is understood as an indicator of time spent in school or school outcome, such as: enrollment, attendance, truancy, drop-out, highest level attained, grade repetition, or test scores. The first set of literature includes Ravallion and Wodon (2000), Fitzsimons (2002), Beegle et al (2004), Bacolod and Ranjan (2005), Maitra and Ray (2002), Parikh and Sadoulet (2005), Ganglmair (2006), Duryea and Arends-Kuenning (2003), Duryea et al (2003), Emerson and Souza (2002), Gunnarsson et al (2006), Rosati and Rossi (2003), Canagarajah and Coulombe (1997), Psacharopoulos (1997), Jensen and Nielsen (1997), and Patrinos and Psacharopoulos (1997). The second set includes Bedi and Marshall (2002), Akhtar (1996), and Pal (2004). 3 See for example Patrinos and Psacharopoulos (1997), Psacharopoulos (1997) or, controlling for household unobservable factors, Jensen and Nielsen (1997), World Bank (2001), World Bank (2002), World Bank (2003).

> 4 See for example Bacolod and Ranjan (2005), who also estimated a bivariate probit model, and Maitra and Ray (2002), who also estimated an ordered probit model.

> 5 See Ganglmair (2006), Emerson and Souza (2002a), Duryea et at (2003), Duryea and Arends-Kuenning (2003), Parikh and Sadoulet (2005), Canagarajah and Coulombe (1997), and Emerson and Sousa (2002).

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