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  • 标题:A micro analysis of urban child labour: some determinants of labour and its conditions.
  • 作者:Hamid, Shahnaz
  • 期刊名称:Pakistan Development Review
  • 印刷版ISSN:0030-9729
  • 出版年度:1994
  • 期号:December
  • 语种:English
  • 出版社:Pakistan Institute of Development Economics
  • 摘要:This paper focuses on (1) The estimation of urban child labour, (2) Analysis of its determinants, (3) Analysis of some of its conditions and their sectoral determinants, and finally puts forward some possible solutions.
  • 关键词:Child labor;Child labor practices;Children;City children

A micro analysis of urban child labour: some determinants of labour and its conditions.


Hamid, Shahnaz


INTRODUCTION

This paper focuses on (1) The estimation of urban child labour, (2) Analysis of its determinants, (3) Analysis of some of its conditions and their sectoral determinants, and finally puts forward some possible solutions.

This paper is divided into four sections. Section 2 explains the conceptual and analytical framework and describes the data set. Section 3 analyses the empirical evidence and finally Section 4 gives the conclusions and recommendations.

CONCEPTUAL AND ANALYTICAL FRAMEWORK

A review of literature on determinants of child labour in Pakistan shows that poverty is the most important causal factor of child labour [Ahmed (1990); Awann and Khan (1990); Hamid (1994); Husain (1986); Irfan and Hamid (1981); Khan (1982) and Mahmood (1994)]. For this paper we go a step further and ask: what are the specific characteristics of poverty at the household level that cause child labour?

For this study we define child labour as all the children in the age cohort of 5-14 years who are not in school. Our argument is that if a child not in school, he or she is either working at home or working at a work place.

Our basic proposition about child labour is that the household's socioeconomic status is an important determinant of the supply of child labour. The determinants of socio-economic status include, household income, occupation, education and gender of the head of the household.

Based on these four determinants of socio-economic status our first hypothesis is that child labour depends primarily upon the total income of household. The lower the income of the household, the higher the probability of a child working. To eliminate the effect of household size on total income, we are also analysing the impact of per capita income.

The second hypothesis is that occupational status of the head of the household reflects its social status. The periodicity of earning of the head of the household is also related to job stability and social status of a household. So our second hypothesis is that if we rank in descending order the occupational status and periodicity of earning of the head of the household these will both be negatively related to child labour.

The third hypothesis is that household head's education is important because of its impact on household income and bias towards children's schooling. Therefore our third hypothesis is that the educational level of the head of household will also be negatively related to child labour.

Our fourth hypothesis is that, husbands have a greater potential to earn for the household, so widowed or female-headed household will therefore tend to have a lower income. Therefore our hypothesis is that a higher proportion of children will be working where household is headed by a female. Limiting ourselves to the above conceptual and analytical framework:

a. We will make a partial estimate of urban child labour;

b. establish some supply determinants of child labour;

c. establish some working condition for child labour; and d. establish some sectoral determinants of the working conditions of child labour.

The study is based on the data set consisting of 792 households, drawn from the survey data of 1000 low-income urban households distributed over the entire country. The survey was conducted in 1986 under the auspices of the International Food Policy Research Institute (IFPRI) and the Pakistan Institute of Development Economics, (PIDE).

INCIDENT OF CHILD LABOUR IN URBAN PAKISTAN

We will begin by analysing the incidence of child labour by household, age, education and work activities. Table 1 shows a low incidence of households sending all their school going age children to school. While a high incidence of households are not sending at least one of their (school going age) children to school. Out of 792 households only 41 percent of the household send all their children to school, while the other 59 percent of the total households do not send at least one child to school.

Further out of the 2333 school going age children, around 61 percent of the children are in school, while the other 39 percent are not enrolled.

School Enrollment

Table 2 presents school enrollment by age and gender. The disaggregation of the age cohorts reveals the lowest enrollment ratio of 50 percent in the age cohort of 5-6 years, a higher enrollment ratio of 67 percent in age cohort of 7-12 years, while again a lower, enrollment ratio of 51 percent in the age cohort of 13-14 years.

These findings suggest that most of the children start their schooling at a later age. A more or less consistent enrollment ratio between the age cohort of 7-12 years suggest that in this age group the drop out rate is not very high. However, a lower enrollment at the age of 13 and 14 years is probably the result of drop outs.

So the evidence suggest that drop out ratios are not very important in primary education, once children get into school they mostly remain there. This increases the importance of initial enrollment.

The disaggregation of school children by gender shows a significant differential between boys enrollment of 69 percent and girls enrollment at 53 percent.

Disaggregating gender by the age cohorts of 5-6 years, 7-12 years and 13-14 years shows the same trend that we had for genders. Girls enrollment in each age cohort is much lower than for aggregated genders.

Incidence of Drop Outs

To estimate the incidence of drop outs among children not going to school, we have analysed their past school attendance. Table 3 supports the fact that drop out rates are not very important. As can be seen from Table 3, out of the total children not going to school, an overwhelming percentage, of 91 percent have never been to school, while 9 percent had initially gone to school and then dropped out. The table further shows that of the 9 percent who initially went to school, the highest percentage, 7 percent left school at the primary level, and only 2 percent left at the middle or secondary levels.

Gender disaggregation supports this pattern. There is a small differential, of 89 percent boys compared to 92 percent girls who never went to school. The table also shows that among the drop out a higher percentage of both male and female children left school at the primary level.

Pattern of Child Labour

We will now examine child labour. Table 4 presents two sets of variables, the number of children and the number of household.

The table shows that 90 percent of the total 914 children not going to school, are at home. We believe that this is a fault of the data set due to a flawed definition of child activity. Our argument is that a negligible number of children stay home to play, and the overwhelming majority work. This is invisible child labour. Table 4 shows that besides the invisible child labour in the home, there is a high percentage of visible child labour of 10 percent in the labour market. Out of 10 percent visible child labour, 5 percent are private regular workers in the private sector, 1 percent are self-employed, 2 percent involved in joint household activities, and another 2 percent were employed as labourers.

Child Labour by Age and Gender

Disaggregating child labour by gender in Table 5 in the age cohort of 5-14 years, we get a higher percentage, 97 percent of females in invisible child labour compared to males at 79 percent.

For visible child labour in the market, private employment at 11 percent is the major activity for males and joined household activities at 2 percent for females. Disaggregation of the age cohort of 5-9 years shows 99 percent of the children to be invisible child labour defined as "at home". In the age cohort of 10-14 years the incidence of invisible child labour is lower at 78 percent children "at home", with the remaining 22 percent in the visible labour market.

Disaggregating for gender in Table 5 shows the visible labour market for male children much higher 45 percent compared to female children at 5 percent. This suggests that although female children equally participating in child labour, they are mostly confined to invisible home based activities.

DETERMINANTS OF CHILD LABOUR

Our major hypotheses is that household income is the key factor that influences the supply of child labour. So households income will be negatively related to child labour.

Total Income of Household per Month

The first explanatory variable is total income of the household per month. Table 6 suggest that there is a negative relationship between total income of the household per month and child labour. In Table 6, the highest percentage of child labour of 73 percent is found in the lowest income category of less than Rs 2000 per month. Further, the incidence of child labour decreases as the income categories increase, from 73 percent to 16 percent, 5 percent and 6 percent. In almost all categories of child activities the larger proportion of child labour is found where total income of the household is Rs 3000 per month.

Household per Capita Income per Month

A more comprehensive explanation yet is per capita income. Table 7 shows a negative relationship between the household's per capita income per month and child labour. As per capita income increases from Rs 200 to Rs 300 per month, the incidence of child labour decreases from 45 percent to 16 percent.

Household Head's Occupation and Periodicity of their Earning

To test our hypothesis about occupational status of the head of the household, we will rank occupations in the following way. The highest rank is assigned to the government employees, followed by those who are private employees, self-employed, labour and the lowest rank will be for those at home.

Table 8 shows that as the household head's occupational status improves the incidence of child labour decreases but not continuously. Households with heads who are government employees have a low incidence of child labour of 9 percent. Taking a step down in the occupational status where the household head is a private employee, the incidence of child labour increases to 13 percent. The percentage of child labour increases to 36 percent for the household where the head is self-employed. A further step down in the occupational status of the household head where household head is labourer, about 18 percent of the child labour is found. Where household head's occupational status is defined as "at home" the incidence of child labour is 25 percent.

When we tested our hypothesis about the relationship between the periodiciy of earning and child labour, we found no empirical support for it.

Education of Household Head

Our next hypothesis is that the household head's educational level will be negatively related to child labour. Table 9 shows a negative relationship between the household head's educational status and child labour. As the household head's educational level improves from primary to university level, child labour decreases. The highest percent of child labour is, where household head is illiterate. A step up in the educational level, where the household head is literate, the incidence of child labour drops to 15 percent. Incidence of child labour is 16 percent where the household head's educational level is primary. There is a further drop in child labour down to where the household head has completed middle level education. Child labour decreases further when the household head has education upto university level. This supports our hypothesis that child labour is negatively related to the household head's educational level.

Female-headed Households

Table 10 presents the impact of the gender of the household head, on child labour. The table shows that in the male-headed household, the incidence of invisible children working at home, is higher at 95 percent compared to 85 percent for female-headed households. Therefore female-headed households have a higher proportion of child labour in visible activities.

SECTORAL DETERMINANTS OF ITS CONDITIONS

We aim to establish some relationship between the activities taken up by the children and their working conditions. To do so we will examine the days per week, work hours per day, frequency of payment and earning per month.

Work Days

Table 11 shows that besides the activity "at home" for which we lack data, in all other activities a high percentage of 9 percent of the children work 5-7 days a week. Among these 7 percent work for an average of 6 days a week, 2 percent work for an average of five days a week, and 0.16 percent on an average 7 days a week.

In each activity the highest percentage of children work for 6 days a week. An interesting result is that those working for more than 6 days a week are mostly from either the self-employed category or the "joint household activity". About 23 percent of the total self-employed and 11 percent of the total children "joint household activity" work for an average of 7 days a week.

Working Hours

The Table 12 shows that besides the 821 children for whom we lack data of the remaining, 10 percent work for 6-12 hours a day, 4 percent work for an average of 8-9 hours a day, and the remaining 4 percent of the children work for 10-12 hours a day.

Further examination of activities and average working hours per day shows that the children, working as "private employees" have the longest working hours. Out of total private employees, about 58 percent children work on an average of 10-12 hours a day. In all other categories of activities a higher proportion of children work an average of less than 10 hours a day.

Frequency of Payment

Table 13 presents the relationship between the frequency of payment and child activity. The table shows that besides 91 percent of the children who get nothing. The remaining 8 percent have different periodicity for their earnings. Of these 3 percent of children are monthly earners, 2 percent are daily earners, 1 percent earn weekly and 2 percent have an irregular pattern of earning.

Out of the total private employees 60 percent work on regular basis and get monthly earning. Among the self-employed, 69 percent are daily earners, while 78 percent of the children who work with their parents or other members as joint household activity get nothing.

Among the labourers 64 percent, and 80 percent of those in the category "other" are irregular earners. The table suggest that the nature of employment in relation to the frequency of payment.

Earnings per Month

Table 14 presents the relationship between the child's activity and his/her earning. The table shows while 91 percent of the children get nothing the remaining get fairly low wages.

The highest proportion of earning children of 37 percent fall in the lowest income category of less than Rs 200.

The nature of employment of the child is seem to affects their earnings. Out of the total private employees only 16 percent have an income of more than Rs 400 per month. Of self-employees a much higher 69 percent get more than Rs 400 per month. However among the children who work with their parents, only a lower 22 percent get Rs 200 to less than Rs 400 a month. Child labourers also have high percentage of earnings 57 percent earn more than Rs 400 per month. Children who are engaged in odd activities get less than Rs 200 per month.

All the above evidence suggests that the nature of employment of children affect their term and conditions, and among all the categories of employment private employees are the most exploited. They work more in terms of hours and days, but get far less in return.

CONCLUSIONS

The evidence suggests that poverty is the most pervasive factor affecting child labour and child schooling. Household income, gender, occupational status and educational level of the household head, are all linked to child labour and school enrollment.

To curb child labour we need a comprehensive policy package that can simultaneously increase employment and earning opportunities for adult household members, encourage child schooling, specially at the primary level, because drop out rates are not so important. It is more important to get children to school.

Educational opportunities can play a role in reducing child labour only if adults are offered economic incentives to compensate for the loss of that income which results from school attendance. Labour laws concerning child labour should be enforced forcefully.

Comments on "A Micro Analysis of Urban Child Labour: Some Determinants of Labour and its Conditions"

To further enrich the review of the literature and discussion you may like to include the following comments on the above study. According to Mr Moazam Mahmood in 1994, there are 18.8 million children are involved in economic activities. This is a shocking figure for many agencies. However, simple estimates and calculations indicate that out of 52 million children in Pakistan, only 31 million children get admission in schools and later 15 million children leave school before completing primary education. Therefore 21 million children are out of school. This is a large number which needs attention from the legislators, planners and policy-makers.

To mobilise positive action on this research from the concerned agencies, it will be a powerful argument to include the convention on the Rights of the Child, in the review of literature. "The convention on the Rights of the Child" (CRC) was ratified by the Government of Pakistan in November 1990. The Government is obliged to provide education to all children "not as a charity but as a right". Children must not be available for work. The Government must provide protection to children from economic exploitation. These commitments are reaffirmed in the First Report on the Implementation of the Convention on the Rights from Pakistan to the Committee on the Rights of the Child (1993-1994) in Geneva.

For details please see the attached documents. The Convention will also enrich the discussion part.

Poverty is of course the basic cause of child labour. The results of the study very clearly indicate that the majority of the working children are from the lowest socio-economic group moreover, these children belong to large families. This argument may be included with emphases on the parental attitudes towards child rearing practices.

The most unethical part of child labour is the employers exploitative attitude towards the child worker. The employment of young children in the formal or informal sectors is total violations of the existing laws and CRC commitments. A child is working for 6-12 hours a day and receives Rs 4.00 to 6.00 per day while, an adult receives Rs 80-100 per day for the same work. An employer prefers a child because he/she is an obedient servant and ready to work for long hours for low or no wages.

The child workers is illegally employed in the various sectors and secondly exploited. Child labour punishes Pakistan three times over: it deprives adults of job opportunities; it steals the country's childhood; it prevents education of its youth. This may be included in the discussion and conclusion.

Khalida Ahmed

UNICEF, Islamabad.

REFERENCES

Ahmad, Manzooruddin (1990) Child Labour a Time to Reflect UNICEF. Government of Balochistan.

Awann, Saeed, and Ali Adid Khan (1990) Child Labour in Carpet Weaving Industry in Punjab. Report of a Survey.

Hamid, Shahnaz (1994) A Micro Analysis of Urban Child Labour, some Determinants of Labour and its Conditions. Paper presented at the Tenth Annual General Meeting of Pakistan Society of Development Economists, Islamabad.

Husain, Akmal (1986) Economic Growth Poverty and Plight of Children. In Children Issue 1.

Irfan, M., and Shahnaz Harold (1981) Child Labour in Pakistan. Unpublished.

Khan, Shaheen (1982) Labour Force Participation of Children. A Case Study. Pakistan Economics and Social Review.

Mahmood Moazam (1994) Why do Children not Going to School in Pakistan. Some Estimates and Theoretical Framework. Paper presented at the Tenth Annual General Meeting of the Pakistan Society of Development Economists, April 2-5, Islamabad.

Shahnaz Hamid is Research Economist at the Pakistan Institute of Development Economics, Islamabad.
Table 1
The Distribution of Children(5-14 Years of Age) Going/Not
Going to School by Households

 Households Children

Catagory No Percent No Percent

All Children in School 322 40.7 1418 60.8
At least One Child not in School 470 59.3 915 39.2
Total 792 100 2333 100

Table 2

The Distribution of Children (15-14 Years)
Going/Not Going to School by Age and Gender

 Total Children

Age Total In Not in Enrol.
 School School Ratio

 5 242 118 124 48.76
 6 291 149 142 51.20
 7 278 188 90 67.62
 8 278 187 91 67.27
 9 193 133 60 68.91
10 256 173 83 67.58
11 161 106 55 65.84
12 272 180 92 66.18
13 173 89 84 51.44
14 188 95 93 50.53
Total 2332 1418 914 60.80

 Males

Age Total In Not in Enrol.
 School School Ratio

 5 137 73 64 53.28
 6 146 81 65 55.48
 7 142 112 30 78.87
 8 139 108 31 77.69
 9 88 71 17 80.68
10 130 102 28 78.46
11 89 64 25 71.91
12 148 109 39 73.64
13 79 45 34 56.96
14 98 57 41 58.16
Total 1196 822 374 68.72

 Females

Age Total In Not in Enrol.
 School School Ratio

 5 105 45 60 42.9
 6 145 68 77 46.9
 7 136 76 60 55.9
 8 139 79 60 56.8
 9 105 62 43 59.0
10 126 71 55 56.3
11 72 42 30 58.3
12 124 71 53 57.3
13 94 44 50 46.8
14 90 38 52 42.2
Total 1136 596 540 52.6

Table 3

The Distribution of Children not Going to School by Age,
Gender and Past School Attendance

 Age 5-14 Years

 Both Male Female

Attendance No % No % No %

Never in School 829 90.7 333 89 496 91.9
Primary 62 6.8 31 8.3 31 5.7
Middle 18 2.0 6 1.6 12 2.2
Secondary 4 0.4 3 0.8 1 0.2
Apprentice 1 0.1 1 0.3 -- --
Total 914 100 374 100 540 100

 Age 5-9 Years

 Both Male Female

Attendance No % No % No %

Never in School 501 98.8 205 99.0 296 98.7
Primary 6 1.2 2 1.0 4 1.3
Middle -- -- -- -- -- --
Secondary -- -- -- -- -- --
Apprentice -- -- -- -- -- --
Total 507 100 207 100 300 100

 Age 10-14

 Both Male Female

Attendance No % No % No %

Never in School 328 80.6 128 76.7 200 83.3
Primary 56 13.8 29 17.4 27 11.3
Middle 18 4.4 6 3.4 12 5.0
Secondary 4 1.0 3 1.8 1 0.4
Apprentice 1 0.2 1 0.6 0 0
Total 407 100 167 100 240 100

Table 4

The Distribution of Children not Going to School by
their Activities and Households

 Total Children not No of Households
 Going to School with Child Labour

Activity No Percent No Percent

At Home 821 89.8 454 85.8
Private Employee 43 4.7 33 6.2
Self-employee 13 1.4 12 2.3
Joint HH Activity 18 2.0 13 2.5
Labour 14 1.5 12 2.3
Other 5 0.5 5 0.9
Total 914 100 * 529 100

* One HH having Children in more than one activity is counted
more than one time, the actual No. of HH is 470.

Table 5

The Distribution of Child not Going to School by Age,
Gender and their Activity

 Age 5-14 Years

 Both Male Female

Attendance No % No % No %

At Home 821 89.8 296 79.1 525 97.2
Private Employee 43 4.7 42 11.2 1 0.2
Self-employee 13 1.4 12 3.2 1 0.2
Joint HH Activity 18 2.0 8 2.2 10 1.8
Labour 14 1.5 12 3.2 2 0.4
Other 5 0.6 4 1.1 1 0.2
Total 914 100 374 100 540 100

 Age 5-9 Years

 Both Male Female

Attendance No % No % No %

At Home 502 99.0 204 98.5 298 99.3
Private Employee 3 0.6 3 1.4 -- --
Self-employee -- -- -- -- -- --
Joint HH Activity 1 0.2 -- -- 1 0.3
Labour -- -- -- -- -- --
Other 1 0.2 -- -- 1 0.3
Total 507 100 207 100 300 100

 Age 10-14 Years

 Both Male Female

Attendance No % No % No %

At Home 319 78.4 92 55.1 227 94.6
Private Employee 40 9.8 39 23.3 1 0.4
Self-employee 13 3.2 12 7.2 1 0.4
Joint HH Activity 17 4.2 8 4.8 9 3.7
Labour 14 3.4 12 7.2 2 0.8
Other 4 1 4 2.4 -- --
Total 407 100 167 100 240 100

Table 6

The Distribution of Children not Going to School by their
Activities and Total Income of Household

 Private Self-
 Income Total At Home Employee employee
 per Month
 (Rs) No % No % No % No %

<1000 307 33.6 268 32.6 22 51.2 3 23.1
1000 < 2000 361 39.5 331 40.3 14 32.6 4 30.8
2000 < 3000 142 15.5 127 15.5 7 16.3 2 15.4
3000 < 4000 48 5.3 46 5.6 -- -- 1 7.7
>4000 56 6.1 49 6.0 -- -- 3 23.1
Total 914 100 821 100 43 100 13 100

 Joint HH
 Income Activity Labour Other
 per Month
 (Rs) No % No % No %

<1000 7 38.9 4 28.6 3 60.0
1000 < 2000 3 16.7 8 57.1 1 20.0
2000 < 3000 3 16.7 2 14.3 1 20.0
3000 < 4000 1 5.6 -- -- -- --
>4000 4 22.2 -- -- -- --
Total 18 100 14 100 5 100

Table 7

Distribution of Children Going to School by their Activities and
per Capita Income of the Household (Rs)

 Private Self-
 Total At Home Employee employee
 Income
per Month No % No % No % No %

<100 233 25.5 198 24.1 15 34.9 2 15.4
100 < 200 410 44.9 371 45.2 25 58.1 5 38.5
200 < 300 147 16.1 138 16.8 3 7.0 2 15.4
300 < 400 65 7.1 61 7.5 -- -- 3 23.1
>400 59 6.6 53 6.5 -- -- 1 7.7
Total 914 100 821 100 43 100 13 100

 Joint HH
 Activity Labour Other
 Income
per Month No % No % No %

<100 7 38.9 10 71.4 1 20.0
100 < 200 2 11.1 4 28.6 3 60.0
200 < 300 3 16.7 -- -- 1 20.0
300 < 400 1 5.6 -- -- -- --
>400 5 27.8 -- -- -- --
Total 18 100 14 100 5 100

Table 8

The Distribution of Children not Going to School by their Activities
and Household Head' Occupation

 Private Self-
 Total At Home Employee employee
HH Head's
Occupation No % No % No % No %

Govt. Employee 78 8.5 72 8.8 4 9.3 2 15.4
Private Employee 117 12.8 106 13.0 7 16.3 2 15.4
Self-employee 328 35.9 290 35.3 17 39.5 6 46.2
Labour 159 17.4 145 17.7 4 9.3 2 15.4
Other 10 1.1 9 1.1 1 2.3 -- --
At Home 220 24.1 197 24.0 10 23.3 1 7.7
Student 2 0.2 2 0.2 -- -- -- --
Total 914 100 821 100 43 100 13 100

 Joint HH
 Activity Labour Other
HH Head's
Occupation No % No % No %

Govt. Employee -- -- -- -- 1 20.0
Private Employee -- -- 1 7.1 3 60.0
Self-employee 10 55.6 2 14.3 1 20.0
Labour 1 5.6 6 42.9 -- --
Other -- -- -- -- -- --
At Home 7 38.9 5 35.7 -- --
Student -- -- -- -- -- --
Total 18 100 14 100 5 100

Table 9

The Distribution of Children not Going to School by their Activities
and Education Level of HH Head's

 Private Self-
 Education Total At Home Employee employee
Level of HH
 Head's No % No % No % No %

Illetrate 511 55.9 458 55.8 23 53.5 8 61.5
Literate 137 15.0 124 15.1 4 9.3 2 15.4
Primary 142 15.5 125 15.2 11 25.6 3 23.1
Middle 69 7.5 64 7.8 1 2.3 -- --
Secondary 44 4.8 40 4.9 4 9.3 -- --
University 8 0.9 7 0.8 -- -- -- --
Apprentices 2 0.2 2 0.9 -- -- -- --
Other 1 0.1 1 0.1 -- -- -- --
Total 914 100 821 100 43 100 13 100

 Joint HH
 Education Activity Labour Other
Level of HH
 Head's No % No % No %

Illetrate 4 61.1 10 71.4 1 20
Literate 4 22.2 2 14.3 1 20
Primary -- -- 1 7.1 2 40
Middle 3 16.7 -- -- 1 20
Secondary -- -- 1 7.1 -- --
University -- -- -- -- -- --
Apprentices -- -- -- -- -- --
Other -- -- -- -- -- --
Total 11 100 14 100 5 100

Table 10

The Distribution of Children not Going to School by their
Activities and Gender of the Household Head

 Private Self-
Gender of Total At Home Employee employee
 the HH
 Head No % No % No % No %

Male 866 100 780 95.0 40 4.6 12 1.4
Female 48 100 41 85.4 3 6.3 1 2.1
Total 914 100 821 89.8 43 4.7 13 1.42

 Joint HH
Gender of Activity Labour Other
 the HH
 Head No % No % No %

Male 18 2.1 11 1.3 5
Female -- -- 3 6.3 --
Total 18 1.97 14 1.5 --

Table 11

The Distribution of Children not Going to School by their
Activities and Average Work Days per Week

 Total 0 1 2

 No % No % No % No %

Activity

At Home 821 100 821 100 -- -- -- --
Private Employee 43 100 -- -- -- -- -- --
Self-employee 13 100 -- -- -- -- -- --
Joint HH 18 100 -- -- -- -- -- --
Activity
Labour 14 100 -- -- -- -- -- --
Other 5 100 -- -- -- -- -- --

Total 914 100 -- -- -- -- -- --

 3 4 5 6

 No % No % No % No %

Activity

At Home -- -- -- -- -- -- -- --
Private Employee 1 2.3 1 2.3 6 13.9 34 79.1
Self-employee 1 7.7 1 7.7 1 7.7 7 53.8
Joint HH -- -- 1 5.5 3 16.7 12 66.7
Activity 5
Labour -- -- -- -- -- 28.6 10 71.4
Other -- -- -- -- -- -- 5 100.
 0
Total 2 0.2 3 0.3 14 1.53 68 7.4

 7

 No %

Activity

At Home -- --
Private Employee 1 2
Self-employee 3 21
Joint HH 2 11
Activity
Labour -- --
Other -- --

Total 6 0.6

Table 12

The Distribution of Children not Going to School by their
Activities and by Average Work Hours per Day

 Total
 Children 0 3-4 5-6

Activity No % No % No % No %

At Home 821 100 821 100 -- -- -- --
Private Employe 43 100 -- -- 1 2.3 2 4.7
Self-employee 13 100 -- -- 3 23.0 3 23.1
Joint HH Activity 18 100 -- -- -- -- 2 11.1
Labour 14 100 -- -- 1 7.1 2 14.3
Other 5 100 -- -- -- -- 1 20.0
Total 914 100 821 89.8 5 0.5 10 1.1

 8-9 10-12

Activity No % No %

At Home -- -- -- --
Private Employe 15 34.9 25 58.2
Self-employee 4 30.8 3 23.1
Joint HH Activity 10 55.5 6 63.4
Labour 9 64.3 2 14.3
Other 2 40.0 2 40.0
Total 40 4.4 38 4.2

Table 13

The Distribution of Children not Going to School
by thier Activities and Frequency of Payment

 Total Children Nothing Daily

 Activity No % No % No %

At Home 821 100 821 100.0 -- --
Private Employee 43 100 -- -- 5 11.7
Self-employee 13 100 -- -- 9 69.2
Joint HH Activity 18 100 14 77.8 2 11.1
Labour 14 100 -- -- 3 21.4
Other 5 100 -- -- 1 20.0
Total 914 100 835 91.4 20 2.2

 Weekly Monthly Irregular

 Activity No % No % No %

At Home -- -- -- -- -- --
Private Employee 9 21.0 26 60.3 3 7.0
Self-employee 1 7.7 2 15.4 1 7.7
Joint HH Activity -- -- -- -- 2 11.1
Labour 2 14.3 -- -- 9 64.3
Other -- -- -- -- 4 80.0
Total 12 1.3 31 3.4 19 2.1

Table 14

The Distribution of Children not Going to School by
their Activities and Averaize Monthly Earning

Activity Total Children 0

 No % No 0%

At Home 821 100 821 100.0
Private Employee 43 100 -- --
Self--employee 13 100 -- --
Joint HH Activity 18 100 14 77.8
Labour 14 100 -- --
Other 5 100 -- --
Total 914 100 835 91.4

Activity < 200 200 < 400

 No % No %

At Home -- -- -- --
Private Employee 16 37.2 20 46.5
Self--employee 3 23.1 1 7.7
Joint HH Activity 1 5.6 3 16.7
Labour 6 42.9 5 35.7
Other 5 100.0 -- --
Total 31 3.4 29 3.2

Activity 400 < 400 600 & Above

 No % No %

At Home -- -- -- --
Private Employee 4 9.3 3 7.0
Self--employee 8 61.5 1 7.7
Joint HH Activity -- -- -- --
Labour 3 21.4 -- --
Other -- -- -- --
Total 15 1.6 4 0.4
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