Workshop on Gender Statistics Tashkent 11-15 July 2005.

Slides:



Advertisements
Similar presentations
United Nations Economic Commission for Europe Capacity building in Central Asia and Eastern Europe Jessica Gardner United Nations Economic Commission for.
Advertisements

Lama Mitwalli Gender Statistics Division Department of Statistics Jordan Data Gaps in Gender Statistics Workshop on the Development of Gender Indicators.
Millenium Development Goals: Employment related Indicators
United Nations Statistics DivisionRegional Workshop on Integrating a Gender Perspective in the Production of Statistics, Amman, Jordan, 1-4 December 2014.
Filling the Gender Data Gap in Agriculture and Rural Development 1.
United Nations Statistics DivisionRegional Workshop on Integrating a Gender Perspective in the Production of Statistics, Amman, Jordan, 1-4 December 2014.
United Nations Economic Commission for Europe Statistical Division Producing gender statistics through population censuses: UNECE Linda Hooper, Statistician.
United Nations Economic Commission for Europe Statistical Division Labor Statistics: Informal Employment UNECE Statistical Division.
Integrating a gender perspective into work statistics Workshop on Integrating a Gender Perspective into National Statistics, Kampala, Uganda December.
United Nations Statistics Division Overview. Overview  Of the many classifications in the Family, five reference classifications will be discussed at.
Statistical Sources Bratislava, 8-10 May 2003 Angela Me Statistical Division UNECE.
THE STATUS OF STATISTICS ON WOMEN AND MEN’S ENTREPRENEURSHIP IN THE UNECE REGION Costanza Giovannelli, Hrund Gunnsteinsdottir, Angela Me UN Economic Commission.
Measuring Governance with Pro- Poor and Gender Sensitive Indicators: Process flow chart as a tool for promoting gender-responsive governance & identifying.
1 Gender Issues in Agriculture Statistics Tashkent, July 2005.
United Nations Economic Commission for Europe Statistical Division Engendering Labour Statistics UNECE Statistical Division.
Availability and Quality of Data Angela Me UNECE Statistics Division.
Use of sample surveys to measure international migration Experience of the Republic of Moldova Valentina Istrati, head of demography statistics and population.
United Nations Sub-Regional Workshop on Census Data Evaluation Phnom Penh, Cambodia, November 2011 Evaluation of Socioeconomic Data Collected from.
Overview of gender statistics: why, what, for whom and how Workshop on Integrating a Gender Perspective into National Statistics, Kampala, Uganda
1 Sources of gender statistics Angela Me UNECE Statistics Division.
United Nations Economic Commission for Europe Statistical Division Sources of gender statistics Angela Me UNECE Statistics Division.
Statistics Canada Statistics Canada Statistique Canada Statistique Canada Gender and economic statistics: Using available data UN Global Forum on Gender.
United Nations Statistics DivisionRegional Workshop on Integrating a Gender Perspective in the Production of Statistics, Amman, Jordan, 1-4 December 2014.
Presentation of Statistical Tables Bratislava, 5-7 May 2003 Angela Me Statistical Division UNECE.
Best practices in combating hate crime on the ground osce.org/odihr.
Gender Statistics in the Labour Market Angela Me UNECE Statistics Division.
Integrating a gender perspective into poverty statistics Workshop on Integrating a Gender Perspective into National Statistics, Kampala, Uganda December.
1 GENDER ISSUES in Labour Household Surveys TURIN, 9-12 Dec.2008 AHMAD HUSSEIN CONSULTANT BASED ON DOCUMENTS PREPARED.
1 Gender Statistics: What is all about? Angela Me UNECE Statistics Division.
United Nations Economic Commission for Europe Statistical Division Incorporating Gender into Labour Statistics UNECE Statistical Division.
Guide on Gender Analysis of Census Data Ralph Hakkert Population and Development Branch Technical Division, UNFPA.
Workshop Summary Subregional Workshop on Dissemination and Use of Population and Housing Census Results with a Gender Focus Suva, Fiji, July 2011.
Availability of gender statistics at the international level IAEGM on the Development of Gender Statistics New York,12-14 December 2006 Demographic and.
Census of Economic Establishments in Ethiopia Yasin Mossa Central Statistics Agency of Ethiopia July 2009.
ANALYZING CENSUS DATA WITH A GENDER FOCUS Session 2.
Portugal’s Gender Statistics Database: the Gender Profile Economic Commission for Europe Conference of European Statisticians Group of Experts on Gender.
UNDP /UNECE NHDR Workshop on Statistical Indicators Bratislava, 5-10 May 2003 Gender Statistics and Disaggregation by Sex Dono Abdurazakova, Gender Adviser.
United Nations Economic Commission for Europe Statistical Division UNECE and gender statistics Angela Me UNECE Statistical Division.
Palestinian Central Bureau of Statistics United Nations Secretariat – Statistics Division Inter-Agency and Expert Group Meeting on the Development of.
Statistics Canada Statistics Canada Statistique Canada Statistique Canada Gender and economic statistics: Using available data Heather Dryburgh, Ph.D.
United Nations Economic Commission for Europe Statistical Division GENDER DIVISION IN INDIA.
United Nations Economic Commission for Europe Statistical Division Availability and Quality of Gender Statistics Angela Me UNECE Statistics Division.
SIAP Time Use Survey Conducted in China April 2013, SIAP,Chiba,Japan Gong Shaojun NBS, China.
Integrating a gender perspective into work statistics United Nations Statistics Division.
Convention 100 Equal Remuneration, 1951 Basic principle: gender should not be the basis upon which remuneration is calculated or paid - either directly.
Measuring Gender Equality in the UNECE Region Andres Vikat Workshop on Gender Statistics Dissemination and Training Chisinau, 3-4 November 2015.
Time Use Statistics Margarita F Guerrero UNESCAP Regional Adviser on Statistics Inter-regional Workshop on the Production of Gender Statistics 6-10 August.
 The Purpose and Objective  The need for TUS  Integration of TUS in Statistics 4-7 Dec, Integrating Gender Perspective in Statistics, Kampala.
Nadejda Cojocari National Bureau of Statistics Republic of Moldova Development of Gender Statistics In Republic of Moldova.
Relation of Census of Agriculture with the Population and Housing Censuses.
Gender Statistics in Armenia National Statistical Service Republic of Armenia Prepared by Gagik Gevorgyan, Member on State Council of Statistics, Astghik.
13-Jul-07 Item 1 – Introduction. 13-Jul-07WG Core variables in social surveys Name of the presentation 16 Core Variables… 1.Geographic data I (linked.
2009 Survey of Disability, Ageing and Carers (SDAC) – emerging data Presentation to Carers NSW Biennial Conference 17 March 2011 Steve Gelsi Assistant.
United Nations Economic Commission for Europe Statistical Division Gender Pay Gap Data availability and measurement issues Work Session on Gender Statistics.
Key statistical concepts in a user-friendly manner Workshop title Location and Date.
10 August Inter-Regional Workshop on the Production of Gender Statistics New Delhi, India, 6-10 August 2007 Strengthening National Gender Statistics.
Measuring work and economic activity Workshop Title Location and Date.
“ Census is the Image of the Present and the Future ” ENGENDERING POPULATION CENSUS THE HASHEMITE KINGDOM OF JORDAN DEPARTMENT OF STATISTICS (DoS) GLOBAL.
Tahere Noori Gender Statistician Statistics Sweden
WS Gender Statistics 2004 UNECE Statistical Division Joint ECE-UNDP Assessment of official statistics related to gender equality in Eastern Europe and.
ILO Department of Statistics Measurement of the informal employment and employment in the informal sector September 2011 ILO Department of Statistics (T.
National Bureau of Statistics of the Republic of Moldova 1 High Level Seminar for Eastern Europe, Caucasus and Central Asia Countries (EECCA) on 'Quality.
4 th Inter-Agency and Expert Group Meeting (IAEGM) Dead Sea, Jordan 9-10 May 2016 The Gender Disaggregated Data in Agriculture and Rural Development Mohamed.
Common attentions and many differences
National Perspectives in Developing Gender Statistics
Data Gaps By Dr. Grace Bediako Government Statistician
Social and Housing Statistics Section
Integrating Gender into Population and Housing Censuses
Mainstreaming essential For gender programmes For social programmes
Presentation transcript:

Workshop on Gender Statistics Tashkent July 2005

Summary and Lessons Learnt The role of official statistics in providing data for gender analysis was recognized as well as the complementary research work needed to further explore gender issues and promote gender advocacy Gender statistics is not about women statistics. It provides evidence to study the different role of BOTH women and men in the society

Summary and Lessons Learnt Gender statistics deals with all statistics related to individuals. Gender should be mainstreamed in the production, dissemination and analysis of ALL fields of official statistics (including business and agriculture) The Population and Housing Census, Household surveys, and Administrative Records can provide relevant data for gender analysis. Each source has advantages and disadvantages and it is important to understand why different sources can produce different data Uzbekistan reported the experience of using extensively administrative records and the survey on income and expenditures It is encouraging that in Tajikistan the first Labour Force Survey was carried out in 2004 and data were recently released The experience of Moldova in collecting data on emigrants was reviewed as an interesting experience

Summary and Lessons Learnt The availability of gender statistics can be improved by: Increasing the use of existing data Improving the gender-sensitiveness of the current data sources (making sure that sex is included in all data collections related to individuals and reviewing the content of data collections to include more gender-sensitive topics) Improving the dissemination of sex-disaggregated data (sex as the principal classification even when other classifications are used in the presentation of the data) The quality of Gender statistics is important. Bad data gives the wrong message. Quality relates to relevance and methods used to collect the data. With the data collected through interviews, it is important that the interviewers and the questions’ wording are not gender-biased The increased use of international standards improves the quality of gender statistics

Summary and Lessons Learnt Crime data collected in police records or court records does not give proper information on the prevalence of women who experience violence. Statistics on violence against women can be improved by: Carrying out specialized surveys or including an ad-hoc module in on–going surveys (with caution!) Exploring the possibility of using service-based statistics (health centers, shelters, social services) Improving the collection of data from victims (the experience of Kyrgyzstan is a good example on how administrative records can be used to collect data on victims) It is difficult to measure domestic violence particularly because it is not visible as a crime. Government laws (such as the one approved in 2004 by Kyrgyzstan) can help in making this type of violence more visible

Summary and Lessons Learnt It is not relevant to present sex- disaggregated data based on the concept of head of household. To report data available only at household level (ex: income), it is relevant to make gender comparisons based on households composed only by one person or one adult for which the analysis by sex makes sense.

Summary and Lessons Learnt The international definition of Employment includes the concept of work made for income (cash or kind) or unpaid production of goods for own- consumption. Services provided for the households are excluded Often women engaged in the production of goods for own consumption are underreported as employed persons. There is the need to improve the reporting of women, particularly in agriculture Many women are engaged in informal employment and it is important to improve the measurement of informal employment for women and men

Summary and Lessons Learnt Looking at gender and labour market, it is important to collect data and make gender analysis in the following areas: Segregation of women and men particularly in different occupations, industries, and status in employment Gender pay gap Activity status by family composition It is important that data on the engagement of women and men in the unpaid production of services is studied Time-use surveys are the main source of data Time-use surveys require the use of diaries where members of the household can report their use of time with a relatively short intervals of time (10-15 minutes) Data from time-use surveys can provide useful information on: the unequal roles that women and men have in the household The different burden carried by women and men in paid and unpaid work that ultimately affect the empowerment of women The contribution of women and men to the overall national production of goods and services

Summary and Lessons Learnt The data relevant for gender analysis in agriculture are based on the concept of a head of an agriculture holding and his/her characteristics. The definition of a head of a holding is based on the management of the agriculture holding Women are underreported as a head of a holding and data based on sex of a head of a holding may give biased pictures There is a need to better identify the different roles of women and men in agriculture holdings

Summary and Lessons Learnt Data need to be presented in a user-friendly way Analytical tools (tables, graphs, diagrams, and maps) can help get a better understanding of statistics by users Analytical tools should be clear and simple They should present one finding or concept at a time The gender differences should be clearly and simply presented When data are reported by sex and another variable, different percentages can be calculated: To look at the sex distribution of the other variable (percentage of men and women for each category) To look at the percentage distribution within the category of the other variable both for women and then for men

Summary and Lessons Learnt Data, graphics, diagrams and maps should be presented with meaningful explanations The message should be presented with short and simple statements using a style “like a journalist” The statements should be easy to understand relevant and interesting targeted to the needs of the users

Summary and Lessons Learnt During the workshop’s exercises, we have practiced: To read tables and highlight differences between women and men To create graphics and diagrams to present the main message related to gender differences To write a simple story about gender differentials within one topic (employment, agriculture), comparing countries and comparing the same country overtime