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Development Studies Association

2010Paper by Wendy Olsen and Samantha Watson

The Institutionalisation of Bonded Labour AmongMigrants in Andhra Pradesh, India:

A Sociological Analysis of Micro Data

Aims of Paper

• Introduce child labour as one form of unfree labour, and migrant labour as highly at risk of bondage and unfreedom.

• Introduce the Young Lives Programme Data, rounds 1 and 2, adjusted by NSS to reflect Andhra Pradesh, India

• Interpret the data– Very common for rural folk to anticipate

indebted migration

• Conclude on AP micro debt crisis2

Andhra Pradesh in India

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Causes of Child Labour• Poverty• Parental strategies of accumulation• Parental strategies of survival• Child strategies of pride and contribution

– (e.g. institutionalised boy provisioning role as a mimicking of the male breadwinner role)

• Employer strategies of cost-minimisation• Beliefs about appropriate labour

– …and other proximate causes such as the mechanisms of entrapment

– … often a high risk when people migrate

Male Muslim Child Labour

Male Adult Permanent Farm Servants

Unpaid Unfree Labour

Post-Bondage Rural Worker

Female Child Cotton Worker

Urban Migrant Labour

Rural Servant Couple

Characteristics Case Number 1 2 3 4 5 6 7

Cheated and/or entrapped Indebted Gender Oppressed Culturally Obligated Treated with ViolenceHad Limitations Placed Upon Job Search

--Whether the type involves just one or both genders

both both both both both both both

Table 1: Overlapping and Varying Characteristics of UnfreeLabour Relations in India (Selected Illustrations)

?New Slavery? Book ed. Van den Anker, survey By Upadhyay• the reasons for the stubborn persistence of

bondage i.e. bonded labour include • a low-waged pattern of economic development in India as

a whole• cultural patterns that persistently keep certain castes and

groups down• “the desperate poverty of the labouring classes” is a

cause (Lerche, 2007: 445). But is this social class, assets, income or caste/ethnicity?

– The unfreedom is evolving from a traditional form of permanent bondage toward a wider range of types of re-worked unfreedom.

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New Features of Bondage

• Coercion is temporary and by threat, without longterm heritability of the relationship

• Entrapment occurs by contracts and thus there is an explicit voluntary element at some early stage on someone’s part, often a parent

• The term of the relationship is not as long as in the past– Debt always played a role, but in recent years

dowry debt needs to be paid back quickly7

A Migrant Worker Housing Area

• Mumbai

Their Home Village

Standard Village Housing

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Poorly lit, no water inside

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Argument 1 : Difficult to End Child Labour From Within

• IF poverty is still a barrier OR parents still coerce child OR family strategy still involves paid child labour THEN Bridge School opportunity will bypass this child

• IF family is heavily indebted THEN child bondage may be an option which family looks at AND/OR child may view bondage as a way out of grinding family labour also raising possibility of rescuing family – (heroic role of child?)

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Argument 2

• Background cultural assumptions about proper behaviour influence Indian families of working class toward accepting the child paid labour and bonded migrant labour scenarios– The idea of a cultural assumption is treated by

Thevenot, Jagd, as ‘conventions theory’,– by Bourdieu as doxa, – by Granovetter as embedded – but it is an

empirical question.

• We use retroduction here! New Findings!

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ILO and GOAP role

• Arg. 2 is supported and acted upon by actions of external large organisations who try to ‘do good’ in labour markets– There is a small flow of funds– There is a rescue/rehab attempt– There is a small cultural impact on

stereotypes and norms acting as new & improved reference points

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ILO Decent Labour

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ILO funded state plan 2008 “State Plan of Action for Elimination of Child Labour• I. VisionTo eliminate Child Labour in Andhra Pradesh through an integrated

action of all stakeholders.• II. ObjectivesThe three main objectives of State Action Plan are:-

(a) To eliminate Child Labour in hazardous occupations by October 2010.(b) To achieve elimination of child labour in non-hazardous occupation along with Universalisation of Elementary Education and CompulsoryEducation.(c) To achieve complete rehabilitation of all the rescued child labour and their families.

• III. Strategies . . . “Etc.

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The ILO GOAP programme

• (a) Rajiv Vidya Mission has targeted residential bridge course programme for rehabilitation of Child Labour.

• (b) NCLP targets child labour in Hazardous and Non-hazardous sectors.

• (c) Joint inspections by multi-disciplinary teams formed by Collector.

• Etc.

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Inspections

• The use of inspections puts children at risk of losing their jobs.

• There is no inspection regime for migrant labour in the construction industry.

• The inspections regime does not really involve firms as stakeholders, it just creates an atmosphere of shame or illegality for the use of child labour < age 14.

What Can YLP Tell Us?

• 1. What would you or other members of your household do in case of hard times

• and/or misfortune caused by, e.g., natural disaster, crop failure, someone losing their job? PLAN1 and PLANSPEC. PLAN2, PLAN3 are additional points.

• 2. adjust these results to allow the non-randomly selected households to take weights corresponding better to AP Rural in general - all 3 large regions. 22

Size of YLP Data Set

• The 2000 millenium babies & 1000 millenium 8-year old children were in separate households.– These 3000 households had 99% retention in

Round 2 in 2005.– Each carer for the index child was asked the

key question and many many others.– From these households, 14,410 individuals.– N=2151 for our study of ‘PLANS’.

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Simplified Options ‘Plan’ 1 Round 2, 2005

• We observe that the specific thing said by some carers was that they would go for bonded labour. However this was not given a code of its own. It is visible in some uncoded data.

• Instead various options are coded as mutually exclusive in PLAN1, the primary action if they came upon hard times.

• PLAN2 is the second action they say they would take.

• PLAN3 is the third action they say they would take.

• “WOULD BORROW & MIGRATE” = 1 if…– They said they would borrow money in PLAN1, 2 or 3;

– And

– They said they would migrate either to another part fo the country or to another country in PLAN1, 2 or 3, OR send children to work OR take children out of school in PLAN 1, 2 or 3. 24

Prevalence of ‘WOULD BORROW & MIGRATE’

• Education none or primary: 7.7% of rural AP carers of millenium children would borrow & migrate if they came upon hard times.

• Education middle school complete: 9% would borrow & migrate.

• Education secondary or higher secondary complete: just 5% said they would.

• Education higher: 15% said they would.25

Social Class and ‘WOULD BORROW & MIGRATE’

• Rural Workers:• casual wage labour 9%• formal employment 5%

• Rural Petty Commodity Producers:• non-agricultural self-employment 5%• small-scale farming 12%• mid-size farming 4%

• Rural capitalist farming 6%

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Other Facets

• Not studied by gender– But where a member of the household is a

self-help group member, the odds of PLAN being to migrate & borrow are much lower;

• Age effects are present, but remember, this cohort has young children.

• By caste group; • 12% among Dalits.

– 3% among Adivasi and 8% all others.27

Hypotheses• 1 Migrant labour with debt as a strategy

can be used by both Educated young people and by Poor people if they come upon hard times.

• 2 Social class underpins differences of plan in case they fall on hard times.– See regression results.

• 3 if they participate in a SHG scheme they will avoid planning to do indebted migration in case they fall on hard times.

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IMPACT ON ODDS OF WOULD BORROW & MIGRATE Slope T-Statistic Significance

Size of Household 0.134846 2.33 ***edyears_6 0.009028 0.03

edyears_8 -0.10631 -0.19

edyears_10 0.565869 1.38

edyears_13 0.612238 1.77 *age 0.269004 2.03 **

age_sq -0.00392 -1.97 **

Casual Worker 0.673491 1.8 *Formal sector employee -0.13656 -0.25

NonAgeSelfEmployment 0.110438 0.25

Small Scale Farming Base case

Mid Sized Farming 0.510048 1.5

Rural Capitalist -1.00328 -1.6

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IMPACT ON ODDS OF WBM Slope T-Statistic SignificanceHousehold has a self help group member -0.17911 -2.11 **Telengana 0.905191 7.21 0Rayalaseema 0.816471 6.54 0constant term -4.2147 -15.69 0

The controls for Age are not strongly significant but there is a tendency for the younger carers not to consider migrating.

The overall regression has a pseudo R2 of 6% if run without weights. The outcome, WBM, has only 8% probability overall.The constant term is large, at -4.2.

With weights, the regression overall has an F statistic of 2 and a confidence level of 99%.

An example of a difference of coefficients is shown here:MedFarmerClass b=.52 Insignificant weighted Versus MedFarmerClass b=.94 *** unweighted.

Results

• The Situation in 2005 Was Complex– 8% of adult carers

were quite prepared to consider borrowing money and moving to a different place.

– Some are at risk of bonded labour, coercion and unfreedom.

– The children here are most at risk.

– Means Were Adjusted by Using NSS Weights

– The Propensity Score Matched Results Differ from the Raw Averages

– The regression results have different coefficients

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Conclusion• We expected to find distress migration among the

poorest workers. We instead found that those with higher education levels were another group who would plan to migrate and borrow if they came upon hard times.– In AP, rural residents of the Upland Deccan Plateau had a high

probability of planning to migrate & borrow if they came upon hard times. (NOT COASTAL AP)

• Social class mattered a lot, with Casual Agric. Workers most likely to be prepared to migrate and borrow.

• Self-help group membership inhibited ‘migrating & borrowing’ if they were to come upon hard times.

• People in larger households also considered borrowing and migrating if they came upon hard times.