Engendering the Statistical System in Cambodia

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Engendering the Statistical System in Cambodia

• Workshop
• Day 2
• 21-23 May 2003
• Funded by UNDP-PGE and UN-ESCAP
• Organized by UNDP-PGE and UNIFEM

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Review of Day 1Teena Chhorvy
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Review Questions

• What did you like about the session yesterday?
• What is the link between gender statistics?
• What is not so clear?

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LectureLorraine
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Engendering the Statistical System in Cambodia

• Engendered data covers all activities carried out
  by women men

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Human activities include

• Economic (market) activities paid unpaid
  labour force activities
• Unpaid household family non-market activities
• Personal services (non-market)

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Paid economic (market) activities

• Wage labour
• Own account workers
• Formal sector
• Informal sector
• Employers

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Unpaid economic (market) activities

• Unpaid work on family enterprises
• Subsistence production
• Production for own consumption
• Collection of free goods water, fuel

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Unpaid household family (non-market) activities

• Domestic services cooking, cleaning, laundry
• Care-related work child care, care of the
  elderly
• Voluntary work community service

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Personal services (non-market)

• Third party definition
• Activities that CANNOT be done for you by someone
  else
• eg. eating
• rest
• recreation
• learning
• enjoying entertainment

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Group workTeena Lorraine Movement Flip Charts
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Small Group Discussion

• Form 5 groups identify human activities that
• can move from market to household (non-market)
  Group 1
• can move from household (non-market) to market
  Group 2
• cannot move from market to household (non-market)
  Group 3
• cannot move from household (non-market) to market
  Group 4
• can move from personal services to the market
  Group 5
• Discuss for 15 minutes
• Write examples on cards post on group flip
  chart
• Review all 5 flip charts individually (5 minutes)

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Plenary Report Back SynthesisLorraine
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Activity boundaries are not fixed
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Key Points

• Activities can move from market to non-market
• Activities can move from non-market to market
• Very few activities cannot move
• heavy industry stays in market
• conjugal love stays in the family
• The same activity could be non-market at one time
  or for one person and market in another time or
  for another person

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Where are women?Where are men?
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LectureLorraine
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Engendering the Statistical System in Cambodia

• Gender analysis of activity shifts (changes in
  division of labour)

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Development changes gender-based division of
activities

• Traditional gender roles
• Men are breadwinners market
• Women are housewives mothers household
• Women move into the market
• Smaller increase in mens household work
• Double burden for women
• household family market
• Women have less time
• for personal services
• participation in other activities
• access to programmes services

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Macro-economic policies change gender-based
division of labour

• Macro policies designed to affect the market
• But may shift activities between market
  household
• Recession/economic liberalization/privatisation
• cuts in public expenditure
• cuts in social expenditure health, education
  etc
• Market services replaced by households (women)

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• Most statistical systems provide limited data on
  household sector and personal services
• Therefore, statistical systems
• Do not capture movement between market
  non-market
• Do not equally capture the activities of women
  men

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Informal group workLorraine
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Informal group exercise

• As you are seated, form groups of three and
  discuss
• What are the negative effects when the
  statistical system does not provide data on
• all 3 kinds of activities of both women and men
  and
• the movement between market and households?

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SynthesisLorraine
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Statistics must be engendered

• Engendering requires that statistics
• Are disaggregated by sex
• All individual data must be
• Presented by sex
• Analyzed by sex
• Cover both market and non-market activities of
  women and men
• ??
• The resulting data can be called engendered
  statistics

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LectureLorraine
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Engendering the Statistical System in Cambodia

• Time use surveys provide data on all activities
  of women and men

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Time use data

• Records time used in various activities
• Paid work
• Unpaid work
• Household maintenance
• Childcare
• Rest
• Personal services
• Usually collected for 24 hour period
• Recall method is most useful for developing
  countries

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Time use data provide

• Background information on household individual
  characteristics
• A comprehensive picture of activities
  interactions
• Classification of activities
• Contextual variables
• Can be linked with other data

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Sex differences in time use

• Women tend to do several activities at the same
  time - experience more time stress than men
• Women spend more time on non-market household
  activities than men
• Men spend more time on economic activities but
  womens time in economic activities is increasing
• Women predominate in unpaid (economic and non
  economic) activities
• Women have less time for rest recreation

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Some lessons from time use data

• Economic crisis economic reforms often cause an
  increase in womens unpaid household activities
• Most countries lack data on a large part of
  womens daily activities
• Data on time use are necessary to formulate sound
  national policies
• Collecting time use data is one way of
  engendering statistics

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Group workTeena - Meta Cards
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Small Group Discussion

• Each participant will write one comment or
  reaction about time use surveys on a Meta card.
• Form 5 groups
• In the groups, discuss your comments and
  reactions for 10 minutes
• Choose one significant positive and one
  significant negative comment/reaction and a
  reporter to present to the plenary.

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SynthesisLorraine
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Time use surveys

• Increase coverage of statistics system
• Better coverage of womens activities
• Household maintenance
• Childcare
• Unpaid family work agriculture
• Better coverage of informal sector
• Can be expensive
• Do not always need large-scale case studies
• Can be integrated with other surveys
• Need to consider impact on other objectives

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LectureLorraine
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Engendering the Statistical System in Cambodia

• National statistical systems

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National Statistical System covers all sectors

• Economic agriculture, labour, industry,
  informal sector
• Social health, nutrition, demography, education
• Household - time use ?

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Sources of data for NSS

• Censuses surveys
• Household-based
• Establishment-based
• Special topics informal sector
• Administrative statistics
• Health system
• School education system
• Housing land records
• Finance, banking, capital flows, imports, exports
• Public sector staffing, commune councils,
  parliament etc

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Users of the NSS

• Government
• Policy making Cabinet Parliament
• Policies planning Bureaucracy sectors
• Private sector
• Planning
• Marketing
• Civil society including NGOs
• Awareness -identifying issues
• Advocacy
• Accountability
• Researchers
• Media

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Uses of the NSS

• Provides accurate and timely data for
• Policy formulation
• Economic social management
• Planning - MDGs
• Programming
• Monitoring Evaluation - MDGs
• Advocacy - MDGs

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Overview

• NSS is more than the NIS
• NSS is bigger than the National Accounts
• NSS is more than the formal data collection
  recording systems
• Much of this data is unused
• Most of it is gender blind

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Inadequacies of national statistical systems

• Partial Coverage
• Lacks data on non-market household activities
  gender bias
• Lacks data on movement of activities from one to
  another sector gender bias
• Inadequate base for policy making
• Existing data is collected processed through
  gender-blind processes

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LectureLorraine
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Engendering the Statistical System in Cambodia

• Steps in collecting census or survey data

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Collecting Census 2001 Nepal

• Pre-enumeration stage
• Management
• Clarification of coverage, concepts definitions
  
• Sample design
• Questionnaire design
• Tabulation design
• Design of manual training for interviewers
• Training of interviewers
• Enumeration stage
• Recruit interviewers
• Training of interviewers
• Media awareness campaign
• Post-enumeration stage
• Data entry processing
• Produce tabulations other materials
• Disseminate data

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Group workLorraine Meta cards
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Small Group Exercise

• Divide into 5 groups
• Discuss how these steps might be engendered
• Prepare Meta cards from your group
• Groups 1 and 2 pre-enumeration
• Groups 3 and 4 enumeration
• Group 5 post-enumeration
• 3. Post your Meta cards on the flip chart provided

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SynthesisLorraine - Prepared chart
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Key points engendering statistics

• Gender-sensitive people
• Aware of gender differences between women men
• Value gender equality
• Gender-responsive processes
• Concepts
• Definitions
• Guiding principles
• Gender equality
• Human rights of women and men
• Explicitly address gender issues
• Differences between women men
• Relationships between women men

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LectureLorraine
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Engendering Census 2001 NepalPre-enumeration

• Gender training
• senior management
• middle management
• Committees on
• Questionnaire manual preparation
• Media
• Project management
• Occupation industry classification
• Reviewed concepts, definitions coding
• Reviewed questionnaire design

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Engendering Census 2001 NepalEnumeration Phase
Engendering Census 2001 NepalEnumeration

• Gender-responsive training
• enumerators
• supervisors
• Recruit women
• as enumerators 20 per cent
• as supervisors 10 per cent
• Public Awareness Campaign
• Women work
• Womens work is important

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Engendering Census 2001 NepalPost-Enumeration
Engendering Census 2001 NepalPost-enumeration

• Individual data disaggregated by sex
• Reviewed all data tabulations from a gender
  perspective
• Created special tabulations on gender issues
• Gender Statistics at a Glance A Fact Sheet
• Publication

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Engendered Statistics are . . .

• Sex-disaggregated
• Presented by sex
• Analyzed by sex
• 2. Cover both market and non-market activities of
  women and men
• All data processes are engendered
• Gender-sensitive people
• Gender-responsive processes
• Address gender issues