These findings suggest that the refugee-native schooling gap is more to do with integration problems than supply bottlenecks. Children who arrive at later ages have difficulty integrating to the schooling system due to war-induced interruptions in schooling, frequent changes in place of residence and the language barrier. On the other hand, poverty and adverse income shocks are likely to force Syrian refugee households to use child labor as a coping mechanism. Many Syrian households suffered dramatic declines in income, having lost their immovable assets to the war or left them behind and had to quit their income generating activities.
This not only means that they have lower earnings but they also face higher income shocks due to the precarious nature of their jobs. Empirical evidence suggests that children of poorer households face a higher risk of employment Edmonds, Negative income shocks due to crop failure Beegle et al. Using the TDHS-S, we calculate that the incidence of child labor among Syrian refugees is remarkably high among boys.
The employment rate of boys aged is While the incidence of child labor is lower in the first year of residence, no difference is observed across other years. In other words, it takes about a year after arrival until refugee children enter the labor market in significant numbers. Not surprisingly, higher levels of household wealth and education of the household head are associated with a lower probability of child labor, pointing to the role of poverty in child labor among refugees.
Other household characteristics that increase the child labor risk are having a young or female household head. In terms of origin characteristics, refugee children originating from villages in Syria are more likely to work. Finally, we find that demand matters substantially. In Istanbul and Eastern Marmara regions, the most industrial regions of Turkey, the probability of child labor is about 20 percentage points higher than that in other urban regions holding other variables constant. This suggests networking effects as well as work sharing.
While the former finding suggests that the availability of other wage earners reduces the need for girls to work, the latter finding implies that elderly household members increase the opportunity cost of employment more for girls than boys given the traditional gender roles.
Boys whose native language is Arabic or Kurdish are less likely to be employed than boys who speak Turkish e. The key differences in the associations by age group concern educational attainment and the age of the household head. In households where the head is young or less educated, younger children age group are much more likely to work.
To the best of our knowledge, this is the first study that does this description using a representative dataset and the first to establish the factors that increase the risk of child labor in the context of the largest refugee group in any single country. Most studies in the literature on forced migration consider their impact on host societies for a review, see Becker and Ferrara, ; Maystadt et al.
In contrast, little evidence exists regarding child labor among refugees at scale. The only other study that looks at child labor using a nationally representative dataset, to the best of our knowledge, is Krafft et al.
Our study is also important in the way that it provides guidance on targeting of policies aimed at improving the living conditions of refugees. One major policy being implemented since is the Emergency Social Safety Net ESSN Program, which provides cash transfers to refugee households provided that they fulfill certain criteria.
Among the criteria are female headship and number of dependents, which we find to be associated with child labor. We, however, also find educational level and age of the household head, the origins of Syrian refugees, and the age of children at arrival to be highly associated with child labor, but these variables are not part of the ESSN criteria.
Section 2 provides background information. Section 3 describes the data and the empirical approach. The results are presented in Section 4. Section 5 concludes the paper. The conflict in Syria started in March By April , the first group of Syrian refugees had already arrived in Turkey. Initially, they were settled in camps along the border with Syria but as the numbers escalated and the war was prolonged, many moved out of the camps.
By the end of , there were 3. A more systematic approach was adopted in the school year with the establishment of Temporary Education Centers TECs , which were later opened in off-camp areas.
TECs followed the Syrian school curriculum and taught in Arabic. A gradual transfer of Syrian students from TECs to public schools was also planned. As of the school year, all TECs are closed and the transfer of Syrian children to public schools is nearly completed MoNE, Whether in camps or not, Syrian refugee children and their families receive various types of social assistance.
Notwithstanding national and international efforts, poverty remains widespread among the refugee population. Over three quarters of the Syrian refugee population are in the bottom wealth quantile.
Children younger than 15 are not allowed to work in Turkey. However, neither Syrian children aged nor adults can formally work unless they have a work permit.
Until , obtaining a. Their arrival accelerated after this date and their number increased to , at the end of and reached 2,, by the end of Fifteen hours per week of Turkish language lessons were added to their program in the school year Emin, A regulation passed in made it possible for Syrian refugees to obtain work permits but to date, only thousand work permits have been issued Refugees Association, Informal employment, while providing a means for income, pays little.
ILO suggests that Syrian workers work for long hours over 45 hours per week but earn less than the minimum wage. They work in the service sector in restaurants, bakeries and grocery shops but also in textile manufacturing.
Some children are doing petty trade and collecting recyclable items. In addition, the fact that all assistance activities for Syrian refugees are subject to registration minimizes non-registration. The TDHS-S collected considerable information on demographic and socio-economic characteristics of sample households, including the paid employment status of household members aged 12 and over. Since our target group consists of children, we restrict our sample to year- olds.
As the vast majority of Syrian refugees migrated to Turkey with their families, the number of unaccompanied children is very limited. In analyzing the correlates of child labor, we use a linear probability model where the dependent variable is paid employment among refugee children. In line with the child labor literature, we consider individual and household characteristics of children as main determinants.
Household characteristics include household wealth, household composition, survival status of mother and father, and sex, age and education level of the household head. Household wealth is constructed using ownership of household assets and housing amenities. We also include regional controls at NUTS-1 level and controls for type of location urban and camp. Hence, if we were to divide only the refugee population into groups, say quintiles, the highest quintile would be very heterogeneous.
Apart from estimations for the whole sample, we carry out separate analyses for girls and boys and for younger aged and older aged children. Considering that more than one child may come from the same household, errors are clustered at the household-level.
Sampling weights are used throughout the analysis. Figure 1 shows paid employment rates in panel A and school enrollment rates in panel B according to age and gender. For girls, the paid employment rate changes little by age; 4. For boys, however, not only are the levels much higher but they also increase at a much faster pace by age. While only Panel B suggests a correlation between school drop- out and employment take-up among boys.
Whenever a sharp drop occurs in school drop-outs, a sharp rise is observed in employment see, for instance, those aged and No such correlation is observed among girls. As girls drop out from school, they do not appear to be entering the labor market in large numbers. Only a very small fraction of children in our sample 8 of 1, children are enrolled in school and also have paid jobs.
The data collected in pre-war Syria suggest much lower paid employment rates for and 17 year-olds when compared to data from TDHS-S in the post-conflict period in Turkey. According to MICS, only 4. The employment rate was again higher among boys than girls with 6. For children aged , the SFHS shows that the prevalence of paid employment was Again, distinctly higher rates were observed among boys with Table 1 presents the basic descriptive statistics based on TDHS-S separately for the total sample and employed children.
The mean age at arrival of refugee children is The average size of a Syrian household in our sample is 8. On average, the household head is We present the estimation results in Table 2 for four different specifications, which differ primarily by how age at arrival and years since arrival are specified. Due to perfect collinearity between age, age at arrival and years since arrival, using all three variables requires restrictions. Therefore, age and age-at-arrival dummies are used in the first specification and only age and years-since-arrival dummies in the second specification.
The results on age-at-arrival and years-since arrival dummies provided in Figure A1 of the Appendix show that, controlling for age, children who arrive after age 8 have a higher likelihood of employment than those who arrive at an earlier age and children who are in their first year of residence in Turkey are less likely to be employed than those with longer duration of residence.
Therefore, we generate an indicator variable for age at arrival that takes the value of one for those who arrive after age 8 and zero otherwise, and an indicator variable for years since arrival that takes the value of one after one year in Turkey and zero otherwise.
The restrictions imposed on the combined structure such as arrival at age 9 and 10 have the same effect solve the perfect collinearity problem, and in specification three we use both indicator variables as well as age dummies.
The fourth specification adds control variables for place and province of birth to specification three. We prefer to add these in a separate specification because these variables tend to wash out the effects of many other variables due to high correlation. Table 2 shows that children who arrive after age 8 are 5. In terms of years since arrival, Table 2 indicates that refugee children are about 12 percentage points less likely to be in paid work in their first year of residence than later years.
This is expected as it takes time for refugees to acclimatize to their new surroundings and find jobs. Age by gender effects provided in Figure A2 of the Appendix , even after controlling for other variables, display similar patterns to those in Figure 1. The gender employment gap becomes remarkable at higher ages; for instance, among year-olds, boys are 40 percentage points more likely to work than girls. The household wealth decile dummy variables in Table 2 indicate that children living in households with higher wealth are less likely to participate in paid employment.
While the coefficient of the dummy for the fifth and higher deciles of wealth is either marginally significant or not statistically significant at conventional levels, the magnitude of the coefficient is larger than that of the fourth wealth decile. In terms of household composition, only the number of children under age 7 is associated with the paid employment of to year-old children. Each child under age 7 is associated with a This suggests that a higher dependency ratio in the household raises the need for making older children work as a coping mechanism.
When the father is alive, the coefficients are consistently positive and large in magnitude, but marginally statistically insignificant at conventional levels.
The positive coefficients suggest network effects for children in finding work. Children in households where the head has attained education beyond secondary school junior high are about 10 percentage points less likely to be in paid jobs than children in households where the head has no education. In terms of the age of the household head, compared to the baseline group of young household heads aged , heads in other age groups are less. While this is not statistically significant at conventional levels, the coefficient magnitudes are large.
Table 2 also indicates that children whose mother tongue is Arabic or Kurdish are less likely to have paid jobs than children whose mother tongue is Turkish, pointing out the importance of language skills in securing jobs. Table 2 further indicates that living in the two most industrial regions of the country Istanbul and Eastern Marmara is associated with a much higher likelihood of refugee children working in a paid job.
Moreover, this association is quantitatively large. Refugee children in these two regions are percentage points more likely to be in paid jobs. This suggests that the demand for child labor matters. This finding, however, could also partly result from the sorting of refugee families with a higher propensity toward child labor into these regions.
Children originating from villages have an 8. The estimation results for separate samples of boys and girls are provided in Table 3. A number of variables affect the employment probability of boys and girls similarly, however the magnitude of the effects is higher for boys due to their higher levels of paid employment.
All topics. Prevalence of child labour Eastern and Southern Africa has the largest proportion of child labourers 26 per cent of children aged 5 to 17 years. Gender disparities In all regions, boys and girls are equally likely to be involved in child labour. Read more. Build your own dataset Build and download your own customizable dataset on child labour data. Query data. Child Labour: Global estimates , trends and the road forward. A comparative analysis.
Notes on the data. Main indicators The Resolution concerning the measurement of working time sets the threshold for economic activities at 14 or more hours per week for children aged 12 to 14 years, but does not specify precise thresholds for unpaid household services due to a lack of evidence that would support such a threshold.
Age 12 to 14 years: At least 14 hours of economic work or 21 hours of unpaid household services per week. Age 15 to 17 years: At least 43 hours of economic work per week. First name. Empath Up! Aman Sarao. Tasha Oliva , Did u try to use external powers for studying? They helped me a lot once. Aisha Pathania. Show More. Views Total views. Actions Shares. No notes for slide. Child labour presentation 1. Child labour is the practice of having children engage in economic activity, on part or full-time basis.
The practice deprives children of their childhood, and is harmful to their physical and mental development. Poverty, lack of good schools and growth of informal economy are considered as the important causes of child labour in India. Harvesting rice 4. Preparing tobacco leaves 6. According to the Census figures there are 1.
It shows that the efforts of the Government have borne the desired fruits. Metal worke r 8. For impoverished households, income from a child's work is usually crucial for his or her own survival or for that of the household. Other scholars such as Harsch on African child labour, and Edmonds and Pavcnik on global child labour have reached the same conclusion.
Some view that work is good for the character-building and skill development of children. In many cultures, particular where informal economy and small household businesses thrive, the cultural tradition is that children follow in their parents' footsteps; child labour then is a means to learn and practice that trade from a very early age.
Similarly, in many cultures the education of girls is less valued or girls are simply not expected to need formal schooling, and these girls pushed into child labour such as providing domestic services. They suggest that child labour is a serious problem in all five, but it is not a new problem. Macroeconomic causes encouraged widespread child labour across the world, over most of human history.
They suggest that the causes for child labour include both the demand and the supply side. While poverty and unavailability of good schools explain the child labour supply side, they suggest that the growth of low paying informal economy rather than higher paying formal economy is amongst the causes of the demand side. Other scholars too suggest that inflexible labour market, size of informal economy, inability of industries to scale up and lack of modern manufacturing technologies are major macroeconomic factors affecting demand and acceptability of child labour.
Electroplat e worker Consequences of child labour The presence of a large number of child laborers is regarded as a serious issue in terms of economic welfare. Children who work fail to get necessary education. They do not get the opportunity to develop physically, intellectually, emotionally and psychologically. In terms of the physical condition of children, children are not ready for long monotous work because they become exhausted more quickly than adults. This reduces their physical conditions and makes the children more vulnerable to disease.
Children in hazardous working conditions are even in worse condition. Children who work, instead of going to school, will remain illiterate which limits their ability to contribute to their own well being as well as to community they live in.
Child labour has long term adverse effects for India. Stitching soccer balls ILO estimates that million children were involved in child labour in , of which million were engaged in hazardous work.
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