Gender and Monitoring & Evaluation

7/30/2019 Gender and Monitoring & Evaluation

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Gender and Monitoring &

EvaluationSamantha Hung

Senior Social Development

Specialist (Gender and

Development)

The views expressed in this presentation are the views of the author and do not necessarily reflect the views or policies of the Asian Development Bank ADB), or

its Board of Governors, or the governments they represent. ADB does not guarantee the accuracy of the data included in this paper and accepts no

responsibility for any consequence of their use. The countries listed in this paper do not imply any view on ADB's part as to sovereignty or independent status or

necessarily conform to ADB's terminology


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Outline of Presentation

Importance of gender M&E?

Gender statistics cycle

Knowledge gaps

Using gender data to inform policy

Challenges

Linking to international initiatives


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Nowadays womenhave the sameopportunities as

men. So where isthe problem?

All our data are sex-disaggregated

anyway. Whats the

problem?

Businessstatistics have

nothing to do withgender.

There is noissue.

Gender statistics isnot a statistical field,what is special about

it?

The role of women is notan issue in our country.

We have resource

constraints and we needto concentrate on other

areas.

We do not want tooverburden therespondents.


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Importance of Gender M&E? To identify the problem: Gender policies can

lack focus, remain vague, aspirationalstatements rather than actionable measures

To inform economic development plans:Gender analysis & data often do notadequately inform economic planning.

To provide strategic direction: from a baselineto achievement of a defined gender goal

To increase awareness & accountability:

Information about gender issues & policycommitments are often not well publicized,so people cant track implementation progress

To track achievements: with verifiable indicators


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International commitments

BeijingPlatform for Action (1995)

2010 review found that after 15 years:Progress cannot be measured in

critical areas limited or non-existent data; many data gaps remain; need forincreased investment in

data collection and analysis

Source: Commission on the Status of Women 2010(E/CN.6/2010/CRP.5)


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Busan - 4th HLF on Aid Effectiveness Forum declaration commits countries & development

partners to collect, disseminate, harmonize and make

full use of sex-disaggregated data to inform policy

Busan Action Plan for Statistics Commits to fully mainstreaming gender mainstreaming

into national statistical systems

Address weaknesses in sex-disaggregated data amongothers as a priority initiative

Recent International Commitments


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Evidence-based Policy Making &Budgeting for Gender Equality

Plan forDevelopmentResults for Men

and Women

Budget forResults

Implement forResults

Monitor Results

Evaluate Results We need data &indicators for

planning,

budgeting

monitoring &

evaluation!

National Gender Equality

Goals formulated


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Gender Statistics Cycle

Data user groups identified &needs determined

Gender analysis of data Dissemination strategy in place and

monitored Products meet user needs Methods for disseminating data are

appropriate for user needs

Good relationships between datausers and producers

Feedback mechanisms exist Users are confident in understanding

& using statistics (statistical literacy)

Regular data collection (surveys,censuses, administrative records)

Elimination of gender bias in

collection instruments Compliance with international

standards and methodologies

Effective national statisticalsystem coordination mechanisms

Data quality frameworks in placeand monitored

Political will


Legislation & policies in place National planning, monitoring andevaluation systems

Culture of evidence-basedpolicymaking

Trust in official statistics

Emphasis on developing nationalstatistics strategies and systems

Demand

exists

Data

exists

Data are

disseminated

Data areused


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Provincial

Nationalcommitments

Internationalcommitments

Flow of data

Monitoring and Evaluation

Public Policy

International Reporting

CEDAW

Beijing

Platform

MDGs

GenderEquality

Laws

Economic

Growth

Strategies

Demand Exists:National & International level

GRB


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10

Data exists: MDG3Gender Equality & Empowerment of Women

Gender parity in primary, secondary & tertiary education

Data availability: Primary (65% of countries); Secondary (52%

of countries); Tertiary (46% of countries) had data from 2009

onwards

Even if achieved, often find that data: Incomplete coverage - Private schools often not covered

Possible misreporting (over-reporting) of enrollments

Unreliable or incomplete data on age of students

Unreliable or incomplete estimates of sub-national level

population provincial, ruralurban, etc.

Differences between national & international data


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Share of women in wage employment inthe non-agricultural sector

Only 30 % of ADBmembers have data

for 2009 onwards

Problem ofcomparability due to

varied concepts,

classification,

coverage &methods of data

collection Source: Millennium Indicators Database Online (UNSD 2011).Note: C=Country Data; E=Estimated, estimated by the international agency,

when corresponding country data on a specific year or set of years is not

available.


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12

MDG3 - representation in parliament

Women continue to be underrepresented in nationalparliaments - slow upward movement.

0

2

4

6

8

10

12

14

16

1990 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

percent

Average percent of seats held by women in National Parliament,Developed and Developing Member Economies: 1990 - 2011

Source. : Millennium Indicators Database Online (UNSD 2011) accessed 6 June 2012.


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Challenges to national demand

Institutional support & mechanisms

Explicit legislative requirement?

Clear mandate in NSDS?

Awareness on gender equality & womensrights, among decision-makers & public?

Need for capacity building & training?

Low priority for gender statistics, and as a

result, insufficient financial & humanresources

? Do these apply in Malaysian context?


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Gender analysis of data Dissemination strategy in place andmonitored

Products meet user needs Methods for disseminating data are


Good relationships between datausers and producers

Feedback mechanisms exist Users are confident in understanding






Effective national statistical systemcoordination mechanisms

Data quality frameworks in place andmonitored

Political will






Demand

exists

Data

exists

Data are

disseminated

Data areused


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What is truly treasured is measured


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Data exists: Sorting out terms

Sex-disaggregated data

Indicators & gender indicators

Goals, targets & indicators Assemble data into a large

number of statistics

They dont act as genderindicators until we use them


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Data exists common challenges

Weak coordination between data-producing

agencies Limited consultation between producers & users Obstacles to collecting gender-related data such

as cultural issues, civil unrest, employing trained

enumerators, reaching remote communities Sex-disaggregated statistics available in raw data

but harder to collate into gender indicators

Lack of baselines

Timeliness & comparability of gender statistics

Which of the above apply in Malaysia? At National,

State or Local level?


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More numbers needed to completeHERstorycommon problem data

Major Data constraints to provide evidencefor public policies related to gender equality: Violence against women

Unpaid work, care economy & time use/poverty

Household headship

Intra-household allocation

Occupation, wages, unemployment, informal

employment, decision making in private sector Entrepreneurship

Household decision making & ownership of assets

Attitudinal change


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Strategies to produce gender data

Regular multi-purpose household surveys:

Sex -disaggregation on earnings, assetownership, informal & self-employment

Leverage Demographic & Health Surveys

Key data source for many gender issues,

including health, education, bargaining

power, fertility & mortality

Irregular time use surveys:

Identify gender time constraints

Universal vital registration & ID system

Register all births & deaths

Analyze this data

19


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Strategies to produce gender data

Important to eliminate gender bias in datacollection: compromises accuracy of data

Sources of gender bias:

Poorly worded questions Inappropriate definitions and concepts

Interviewers not well recruited or trained to begender-sensitive

Who is asking? Who is answering? Whosevoice is heard or unheard?

20


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Good relationships between datausers and producers Feedback mechanisms exist Users are confident in understanding








Political will






Demand

exists

Data

exists

Data are

disseminated

Data areused


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Data are disseminated

Dissemination & communication of gender data

given less emphasis than collection & analysis

Accessibility of gender statistics remains an issue: Limited capacity to analyse & present statistics Lack of resources - both human and financial

Impact of new technologies Role of NSOs

Communication skills Make data meaningful


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World Bank Gender Stats

http://datatopics.worldbank.org/gender/

G d S i i C l


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Good relationships between datausers and producers Feedback mechanisms exist Users are confident in understanding



Elimination of gender bias incollection instruments

Compliance with internationalstandards and methodologies



Political will


Legislation & policies in place

National planning, monitoring andevaluation systems




Demand

exists

Data

exists

Data are

disseminated

Data areused


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Using gender data to inform policy

Example 1: Gender gaps in education due to sonpreference & cultural practices

Policy solution = targeted scholarships/stipends for girls

Example 2: Low representation of women in parliament

Policy solution = quotas/reserved seats for women

Example 3: Low fertility rates & low female labor forceparticipation

Policy solution = greater provision of child-care, parentalleave, tax amendments to encourage women to work

Then monitor and evaluate gender impacts of policy!

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Gender trends in EducationMore women enrolled studies considered feminine such as social sciences &

education. Underrepresented in engineering, manufacturing, and construction.

Source: UNESCO Institute for Statistics (UIS) accessed 12 June 2012.

Samoa

Cambodia

BangladeshNepal

Azerbaijan

Armenia

Lao PDR

Australia Japan

Thailand Uzbekistan

GeorgiaTajikistan

Kyrgyz Republic Hong Kong, ChinaPhilippines

Brunei DarussalamBhutanMongolia Korea, Rep of

Viet Nam

Malaysia

Singapore

0

10

20

30

40

50

0 10 20 30 40 50percentageofwomenenrolledinengineering,m

anufacturing

andconstructionfields

percentage ofmen enrolled in engineering, manufacturing and construction fields

Percentage of Enrolled Women and Men in Engineering, Manufacturing andConstruction Fields, Latest Years


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Gender parityin labor force

participationremains achallenge formost economiesin Asia

FSM = Federated States of Micronesia, PRC = Peoples Republic of China.

Sources: ADB estimates based on data from Key Indicators of the Labour Market, 7th ed. (ILO)

Labor Force Participation Rates

0.20

0.27

0.36

0.45

0.49

0.52

0.520.550.57

0.61

0.610.63

0.64

0.67

0.68

0.69

0.69

0.70

0.71

0.71

0.73

0.730.730.74

0.75

0.75

0.75

0.76

0.77

0.78

0.790.80

0.810.830.830.84

0.85

0.86

0.86

0.0 0.2 0.4 0.6 0.8 1.0

Afghanistan

Pakistan

India

Sri Lanka

Fiji

Timor -Leste

Marshall Islands

Samoa

Malaysia

Indonesia

Turkmenistan

Philippines

Uzbekistan

Solomon Islands

Bangladesh

Japan

Korea, Rep. of

Armenia

Kyrgyz Republic

Tonga

Maldives

Brunei Darussalam

FSM

Singapore

Hong Kong, China

Taipei,China

Georgia

Tajikistan

Vanuatu

Palau

Kiribati

Thailand

Australia

Mongolia

New Zealand

Cook Islands

PRC

Bhutan

Kazakhstan

Ratio

2011

or Latest Year

0.90

0.19

0.16

0.410.47

0.350.520.530.52

0.530.62

0.620.580.630.68

0.70

0.65

0.64

0.79

0.790.480.26

0.54

0.53

0.64

0.60

0.600.740.77

0.89

0.71

0.88

0.87

0.690.840.720.67

0.85

0.63

0.80

1990

or Nearest Year


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Gender disparity evident in all countries

Employment-to-Population Ratio, Aged 15 years and over, Total, Female, Male, Latest Year

Sources: Millennium Indicators Database Online (UNSD), accessed 03 July 2012; Institute for Statistics Data Centre (UNESCO), accessed 18 May 2012.

Employment-to-Population Ratio

0.0

20.0

40.0

60.0

80.0

100.0

--

Total Female Male


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Source: Goldman Sachs (April 2007) Gender Inequality G rowth and Global Ageing.

Economic costs of gender inequality

Companies with a more gender balance in managementboards, total shareholder returns 32.4% higher

(Source: Catalyst report Connecting Corporate Performance and Gender Diversity 2004. 353 of Fortune 500 companies

1996-2000)

Add i t f i lit


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Addressing costs of inequality policy informed by gender M&E

Target = women with children, who start working orincrease work-hours, as they buy products and

services.

Need to understand if women respond to economic

stimuli in the same way?

Policy response = introduction of a job-tax-deduction

favoring lower incomes more than higher:

Supply in work force as a result of the "job deduction"

projected increase in number of job hours:

Desired number of workhours

Total Women Men

Change in % 2.3 2.9 1.8

Change per annum 106000 59000 47000


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1 well-educated woman at home caring for 1.8 children costsmore than 1 adequately educated person caring for 4-5

children

Women spend 27 hrs on housework/week; Men spend 21 hrs

Win-win if women buy child care services. Creates jobs whilethey return to employment. Government gets more taxes.

Policy response = Tax deduction for purchase of home

services

Results emerging: 11,000 people work in household services

75% of them not previously working. Projected growth to 17000

jobs - based on statistics on increased demand over time.

Addressing costs of inequality policyinformed by gender M&E


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Challenges to data being used

Too often, gender statistics not fully used for

evidence-based policies

Key challenge: limited capacity of users to access,

understand, analyse, interpret & use gender statistics Enhance cooperation & partnerships (regular

consultations & dialogue) between data producers

and users, for discussing trends, issues and progress

Need clear gender M&E mandate across all sectors Need to invest in gender statistics & M&E


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Evidence & Data for Gender Equality (EDGE) developing international gender indicator database;

methodological development of standards/guidelines

on entrepreneurship and asset ownership;

presentation to UN Statistical Commission in 2015

Linking to International Initiatives (1)

Core UN IAEG-GS indicators in being developed Economic structures, participation in productive activities

& access to resources

Education

Health and related services

Public life and decision-making

Human Rights of women and girl child


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UN Inter-Agency Expert Group on GenderStatistics

Manual on mainstreaming gender in all official

statistics under finalization Guidelines on VAW statistical surveys

standard methodological guidelines on what,

how, and special features of VAW surveys

Initiatives at the regional commission level Mainstreaming gender into post-2015 Agenda

Linking to International Initiatives (2)


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Thank you for your attentionPlease visit our website

www.adb.org/gender/
http://www.adb.org/gender/http://www.adb.org/gender/


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References* Why Gender Statistics are important to monitor the progress in achieving

MDGs - Numbers tell HERstory! , Presentation by Susann Roth, SocialDevelopment Specialist, ADB

Numbers tell HERstory: Why gender statistics is important to monitor the

progress in achieving MDGs?, Presentation of Kaushal Joshi, Senior

Statistician, ADB

Statistics as evidence for inclusive growth planning: Sweden, Presentation

of Bonnie Bernstrm, President, Liberal Women

Gender-Specific Statistics: Why they matter and what can be done,

Presentation by Stephan Klasen, Universitt Gttingen

*Sourced from recent ADB-sponsored regional workshops/conference proceedings

Documents

Gender and Monitoring & Evaluation