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"Actual experiences of the gender dimensions of poverty measurement in the Caribbean: A technical perspective”. Problems associated with the collection of gender indicators at the national level in Caribbean countries.
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"Actual experiences of the gender dimensions of poverty measurement in the Caribbean: A technical perspective”
Problems associated with the collection of gender indicators at the national level in Caribbean countries • First of all the demand for these indicators are not usually internally generated but are, in fact, often pushed by global agreements by governments to identify indicators that would allow countries to measure and monitor development goals. (Kambon and Joseph-Brown, WP 2003/3).
Problems associated with the collection of gender indicators (cont’d) • The second obstacle to the generation of gender statistics that can be used for poverty measurement has to do with the infrastructure that currently exists in most Caribbean countries for the collection of data .
Capacity of data collection agencies -Staffing • While some countries have as much as 92 staff members with 25% of these persons working in the social statistical unit (Suriname), others have as little as 6 staff members, with one person being responsible for social statistics or no social statistics unit
Capacity of data collection agenciesTraining and use in appropriate software • With the exception of NSOs in the Bahamas, Barbados, Belize and Saint Lucia whose members had received training in and/or also used the appropriate software for the collection and construction of statistical data and indicators, many of the other offices did not have the same capacity, either in terms of training or use of software for the conduct of these activities.
Capacity of data collection agencies-Management of data • Most NSOs are involved in the collection, processing and dissemination of demographic and housing data, and in most cases, labour force data. • In the case of education and health data, the respective line ministries often had primary responsibility for the collection/recording of data, through administrative processes, while the NSOs were primarily responsible for the dissemination of such data • In other cases, even though collected, processed and disseminated by the NSOs, some social statistics were collected on an ad hoc basis and very infrequently.
Capacity of data collection agencies-Analysis of data • Most NSOs reported that their staff members conducted the analysis of data, which they housed or collected, in collaboration with governmental and other experts. NSO-housed data were rarely, if ever, analyzed solely by other researchers and members of the general public.
An examination of data quality issues directly related to selected gender indicators for poverty measurement • Overall sensitivity to the suitability of indicators based on socio-economic and historical context • School attendance and labour force participation less relevant in the Caribbean • Issues of family structure, domestic activity and responsibility, the allocation of household resources and the link between those issues and labour force participation and household well-being are of more immediate relevance
An examination of data quality issues directly related to selected gender indicators for poverty measurement (cont’d) • Availability and quality of the data needed for the construction of indicators • Issues of suitability and comparability of indicators for analytical purposes.
Availability and Quality • The collection of data at the regional level presents no problem if it is a census. However, in sample surveys, such as are conducted during poverty assessments, the issue of availability of data arises due to the small size of many Caribbean countries. This often results in analytical units that are so small, especially when further disaggregated, that there are data gaps.
Availability and Quality (cont’d) • Another reason for the unavailability of data is the absence, in many of the countries, of studies that would elicit the necessary data. This results in two possible scenarios • Data not available outside of census periods • Data not available because the necessary survey has not been conducted.
Box 1: Caribbean countries with household and income surveys 1994-2002 • Country poverty assessments: Belize (1995, 2002), Grenada (1999), St Kitts/Nevis (2001), Saint Lucia (1995), Saint Vincent and the Grenadines (1995) and Turks & Caicos Islands (2001); • Living standard measurement surveys: Guyana (1994) and Trinidad and Tobago (1993/94); • Survey of living conditions: the Bahamas (2001) and Jamaica (1989-2001); • The survey of social and income inequality: Barbados (1996-1997); • The survey of poverty: the Dominican Republic, Fundacion Economica y Desarrollo, Inc (1994); • Food security and living standards survey: Haiti, (1995); and • Poverty assessment: Suriname (1999). Source: ECLAC LC/CAR/G.609, 29 February 2000 and ECLAC Survey (2003)
Availability and Quality (cont’d) • Other indicators that may be difficult to obtain in a number of Caribbean countries because of the irregularity in the conduct of surveys are those requiring Contraceptive Prevalence and Reproductive Health Surveys; and Literacy Surveys.
Availability and Quality (cont’d) • Data gaps may also exist because some of the categories required for the construction of the indicators are not particularly meaningful for some countries and difficult to define in others. One such category is the urban/rural divide.
Quality • The quality and reliability of data can be especially compromised in the case of data that is collected administratively • ‘Deaths by abortion as a percentage of total maternal mortality’ • “Estimated prevalence rates of HIV (%) in the population aged 15-24 years by sex”. • Income
Recommendations • Provide support to NSOs by providing resources and training opportunities to build institutional capacity and infrastructure • Encourage greater sharing of information and data • Training of policy formulators in gender analysis • Need to recognize the specificities of SIDS in the Caribbean in order to construct and identify indicators that are suitable and relevant.