Institutionalizing segregation conditional cash transfers and - - PowerPoint PPT Presentation

Institutionalizing segregation

conditional cash transfers and employment choices

Public Economics for Development WIDER Development Conference 5-6 July 2017 Maputo, Mozambique María Gabriela Palacio palacio@iss.nl

The perversity rhetoric

• Levy (2008): formal workers contribute to

social insurance while informal workers depend on social assistance

• Cash transfers contribute to trapping the

poor into poverty: driven by vicious motives they self-select into informality

• My work explores the parallel to these

debates in the Ecuadorian policy and political debates and evaluates such claims by means of presenting alternative accounts

Levy was one of the architects

• f CCTs in the region

(Progresa | Mexico)

BDH and employment

• Vos, León and Bbrorich (2001)
• Bono Solidario → reduction in hours-of-work
• Disincentive to work effort
• Reduction of work effort among women

(increase in reproductive work)

• Reduction of child labor (school enrolment)
• Gonzalez-Rozada and Llerena-Pinto (2011)
• Andemic Informality IBD (2013)
• BDH → higher permanence in unemployment or separation of formal job

[unemployment insurance literature | moral hazard]

• Mideros and O’Donoghue (2014)
• BDH → decreases the marginal utility of paid work for single adults and female

partners, but has no effect on household heads’ labour participation

• Montaño and Bárcena Ibarra (2013)
• BDH → higher inactivity rates among recipients [due to care needs and state

policies e.g., social assistance]

BDH: target population

Bono de Desarrollo Humano

1.8 million households 9.5 million persons 2012 Mothers Elderly Disabled US$50/month

Or Human Development Grant

Created in the late 1990s to compensate poor families for elimination of gas subsidies Cash transfer with soft conditions | Unconditional cash transfer after enrolment

Number of BDH recipients over time, 2000-2014

Source: BDH administrative registries (MIES 2016) author’s own calculations

What the target population faces

Women and informality

• Informal employment is linked to vulnerability, economic insecurity,

and social exclusion

• Labour markets do not operate in a vacuum: they are shaped by social norms

and power inequalities

• Concrete manifestations:
• Sex occupational segregation [rational response vs socialisation]
• Skewed distribution of rights, resources, and risks

+ by assuming full-time, formal employment as the norm, social protection discriminates against women

e.g., contributory social insurance uses a fixed definition of household, perpetuating gender bias in access to entitlements (Molyneux, 2007)

+ it is among the poor that the higher prevalence of female-headed households and cohabitation is higher

Amongst the poor, the male breadwinner model, has its most detrimental effect on women

Participation rates across age cohorts (disaggregated by sex)

0.85 0.96 0.98 0.98 0.98 0.98 0.97 0.97 0.95 0.92 0.66

• 0.28
• 0.42
• 0.46
• 0.56
• 0.59
• 0.59
• 0.59
• 0.56
• 0.51
• 0.44
• 0.31

0.8 0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8 1.0

15-19 20-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60 61-64 65 and above

2007

Female Male 0.94 0.95 0.97 0.97 0.98 0.97 0.97 0.96 0.92 0.87 0.67

• 0.15
• 0.38
• 0.48
• 0.55
• 0.61
• 0.62
• 0.62
• 0.57
• 0.52
• 0.48
• 0.26

0.8 0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.8 1.0 15-19 20-25 26-30 31-35 36-40 41-45 46-50 51-55 56-60 61-64 65 and above

2015

Female Male

Note: Participation rates account for employed and unemployed population. Calculations exclude full-time students. Source: Author’s calculations using ENEMDU data from the National Centre for Statistics and Censuses (INEC) 2007–15

Motivation

• Isolating the effect of BDH on informal employment is

problematic, as informality rates are nevertheless higher among the poorest population regardless of their participation in the BDH programme.

• The identification of the specific mechanisms through which

targeted social protection affects labour market outcomes is contingent on broader institutional factors pushing poor women into flexible informal work

• unequal access to childcare
• low compliance with labour regulation
• ccupational sex segregation
• BDH recipients present a configuration of high and early

fertility, compounding the aforementioned constraints to entering formal employment

Methodological choices and procedure

Comparative static analysis of repeated samples

• ENEMDU data

collected by INEC Qualitative research

• In-depth interviews

with recipients (n=60 target population)

• Respondent assisted

sampling Self-collected survey

• Sampling frame: RS

listings (n=700)

• Two-stage sampling

Clusters: Loja and Machala SELBEN index: implicit stratification [+/- 10 points around poverty line]

• Purposive sampling

+ informal workers not listed in official records

+household analysis vs individual (gendered) +aggregation problem +altruism vs utilitarianism +motivational complexity

Male to female ratio in access to social protection [contributory vs non-contributory]

0.5 1 1.5 2 2.5 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Male to female ratio Contributory (IESS) Non-contributory (BDH)

Male to female ratio in the formal sector and informal sector 2001-2015

0.5 1 1.5 2 2.5 0.5 1 1.5 2 2.5 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Male female ratio formal sector informal sector

Sex occupational segregation

0.00 0.15 0.30 0.45 0.60 2007 2008 2009 2010 2011 2012 2013 2014 2015

Index of Dissimilarity (D)

Total labour force Some seconday education or more

0=complete integration 1=complete segregation Source: Author’s calculations using ENEMDU data from the National Centre for Statistics and Censuses (INEC) 2007–15

Sex occupational segregation

D = 0.5 * sum | N(Mi)/N(M) - N(Fi)/N(F) | i = 1,...,I where N(M) and N(F) are the overall group sizes. D is the proportion of males that would have to change category in order to get the same relative distribution as in the group of females, or vice versa

• Mostly female sectors (total labour force):
• Agriculture
• Retail trade
• Service work [incl. domestic work]
• Most ‘typical’ occupations amongst BDH recipients:
• ‘Inactive’ dependent homeworker [family system] [legibility]
• Domestic worker [age + ethnicity] [migration]
• Home-based workers [reporting issues] [inactive | unpaid family workers]
• Street vendors [entry barriers] [flexibility | career breaks]

In the intersection of gender with ethnicity, there is evidence of further stratification of the labour force

Inactive | ‘ama de casa’

Home-based worker | street vendor

Structural impediments faced by [recipient] women

• Women’s employment options are limited
• Trying to reconcile care and paid work , women opt for

mother-friendly options [in a stratified way]

• Low compliance with labour regulation
• Unequal access to childcare
• Occupational sex segregation
• BDH recipients are further limited by their institutionalised role as

caretakers e.g., mothers with dependent children

• Informality rates are higher [75% employed in the informal sector]

[poverty and education]

• Inactivity rates are also higher [care and unpaid work]

[extended family]

Selected indicators of fertility and family arrangements by BDH participation for women(*) (national urban)

Never a recipient BDH recipient Mean age of women at first child 21 19 Women who were mothers by 18 years of age (%) 15 47 Mean number of children 2 3 Women managing households on their own with children of 18 years or younger (%) 7 34 Women cohabiting with men with children of 18 years or younger (%) 7 16

Note: *Women aged between 1 2 and 48 years old (fertile years) Source: Author’s calculations based on ECV Living Standards Survey data, (INEC 201 4)

MCA analysis

• A relational technique (variant of Principal Component Analysis)
• Multivariate exploration of the data, and simplifying complex structures

(Ferragina, et al., 2012)

• The approach is not probabilistic‚ therefore is not aimed at predicting any value
• MCA Is suitable for small-n studies only (Asselin & Anh, 2008) and is presented

as complementary to large-N regression methods

• Summarizes the associations between a set of categorical variables
• access to BDH transfers [first dimension]
• employment status [second dimension]
• Interaction with supplementary variables
• marital status
• age cohort
• education level

recipient former recipient never recipient unemployed inactive paid work single (childless) spouse (childless) spouse with children single mother 19 and younger 20 to 35 46 to 65 above 65 none some primary some secondary or more

• 4
• 2

2 4 6 8

dimension 2 ( 8.4%)

• 6
• 4
• 2

2 4 6

dimension 1 (91.6%) supplementary (passive) variables: marital status; age cohort; and education level coordinates in standard normalization

MCA coordinate plot for Loja (female respondents only)

MCA - Loja

Three profiles could be identified 1) recipients who are either spouses with dependent children or elderly women, who are provided with some compensation from the maternity component or the pension component of BDH, respectively; 2) graduated BDH recipients, who are more likely to be in paid work—older spouses (above 46 years old) without dependent children 3) never recipients—following BDH inclusion criteria, childless women or under-age mothers do not qualify for BDH transfers [higher educational level - younger cohorts have had better access to education]

recipient former recipient never recipient unemployed inactive paid work single spouse (childless) spouse with children single mother under 19 20 to 35 46 to 65 above 65 none some primary some secondary or more

• 20
• 10

10 20 30 dimension 2 ( 0.2%)

• 20
• 10

10 20 30 dimension 1 (99.8%)

supplementary (passive) variables: marital status; age cohort; educational level coordinates in standard normalization

MCA coordinate plot for Machala (female respondents only)

MCA Machala

1) Higher inactivity among BDH recipients

• Additional layer: marital status.
• Inactive recipient women tend to be spouses with dependent

children 2) Never recipients were more likely to be in paid work.

• Home-based work, e.g., door-to-door sales, outweighs other
• ccupations available to single mothers of younger age

(between 20 and 35)

• Lack of childcare services/facilities

Two salient profiles could be identified

Conclusions: perverse incentives

• The perversity argument is largely misplaced: current social protection

system has only marginally affected the structure of the labour market in Ecuador

• My results both question the transformative potential of (conditional)

cash transfers while at the same time vindicate them against criticisms that they had introduced dependency and/or encouraged informality

Conclusions: occupational segregation and fragmentation

• The stratification of the labour market is accompanied by a

fragmentation of social protection provisioning

• The integration of women of minorities in social protection was

mostly focused on social assistance rather than contributory schemes [implicit bias | occupational segregation]

• Deepening of social difference
• Existing patterns of employment affect the distribution of income,

economic security and risk, with implications for the design of social protection systems

• Non-contributory social assistance might help shifting risk away from

employers towards employees e.g., domestic work

Conclusions: familism and housewifisation

• Tensions between efforts to ‘empower’ women whilst reinforcing

social divisions through which gender inequalities are reproduced

• Women’s care work is often considered non-work
• Housewifisation(Mies 1982): normative category [dependency]
• Recipient women are grouped as dependents instead of citizens with

rights

• The success of cash transfer programmes depends on women fulfilling

traditional roles i.e., care work, hampering the possibilities of levering their position in the labour market

• Women’s unpaid work continues subsiding social protection

Pushing the boundaries

• Need for a critical reflection on the structure within which social

protection operates

• Tension: maintaining ‘technical’ instruments or tackling the sources
• f marginalisation and vulnerability
• The challenge remains: how to include marginalized groups and

guarantee their social rights

Thank you!