Rapid Gender Assessment Surveys, 2021
Kiribati, 2021
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Reference ID
KIR_2021_RGAS_v01_EN_M_v01_A_OCS
Producer(s)
UN Women, Asian Development Bank
Collections
Metadata
Created on
Jun 22, 2022
Last modified
Jun 22, 2022
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3299
Identification
Survey ID Number
KIR_2021_RGAS_v01_EN_M_v01_A_OCS
Title
Rapid Gender Assessment Surveys, 2021
Country
| Name | Country code |
|---|---|
| Kiribati | KIR |
Study type
Multipurpose Survey - COVID-19 data response
Series Information
For further information on similar studies, see: https://data.unwomen.org/rga
Abstract
Shortly after the onset of the COVID-19 pandemic, evidence showed the consequences of the crisis spanned well beyond its direct health effects. Across Asia and the Pacific, COVID-19 impacted outcomes ranging from access to health care, to employment and income, and women were often at a disadvantage. Two years on, the pandemic continues affecting women and men, and its lingering effects remain gendered. Ample evidence is now available on the effects on women-dominated sectors, such as tourism, and types of work, such as informal jobs, as well as on women's unpaid care work responsibilities. Women are also encountering more barriers to access stimulus packages to stay out of poverty.
In response to these concerns and to design effective responses to the crisis, the demand for gender data has increased. In the past few months, UN Women Regional Office for Asia and the Pacific and the Asian Development Bank rolled out Rapid Gender Assessment Surveys in consultation with national governments.
These surveys also include the eight FIES questions to understand the food security situation in the countries where the surveys have been run. However, it is important to note that these surveys are not identical to the FIES surveys, which are conducted by FAO.
In response to these concerns and to design effective responses to the crisis, the demand for gender data has increased. In the past few months, UN Women Regional Office for Asia and the Pacific and the Asian Development Bank rolled out Rapid Gender Assessment Surveys in consultation with national governments.
These surveys also include the eight FIES questions to understand the food security situation in the countries where the surveys have been run. However, it is important to note that these surveys are not identical to the FIES surveys, which are conducted by FAO.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Individuals
Scope
Notes
Modules included in the survey are as follows:
- HEALTH,
- MAIN ECONOMIC ACTIVITY,
- UNPAID DOMESTIC AND CARE WORK,
- FOOD HARDSHIP,
- PERSONAL AND HOUSEHOLD INCOME,
- REMITTANCES,
- AND GOVERNMENT SUPPORT.
- HEALTH,
- MAIN ECONOMIC ACTIVITY,
- UNPAID DOMESTIC AND CARE WORK,
- FOOD HARDSHIP,
- PERSONAL AND HOUSEHOLD INCOME,
- REMITTANCES,
- AND GOVERNMENT SUPPORT.
Topics
| Topic |
|---|
| Gender Statistics |
Keywords
| Keyword |
|---|
| Gender |
| COVID-19 |
| Socio-economic indicators |
| Unpaid domestic and care work |
| Food hardship |
| Vaccines coverage and hesitancy |
| Fuel and water collection |
Coverage
Geographic Coverage
National Coverage
Universe
The target population are individuals 18 years and above, with access to a mobile phone.
Producers and sponsors
Primary investigators
| Name |
|---|
| UN Women |
| Asian Development Bank |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Department of Foreign Affairs and Trade - Government of Australia | DFAT | Funding |
| Asian Development Bank | ADB | Funding |
Sampling
Sampling Procedure
The RGAS were rolled out in Kiribati (n=2,032), following a Random Digit Dialling (RDD) method, using numbering plans from national telecommunications agencies, which excluded commercial numbers and business registers. Prior to data collection, the sample was pulsed (a signal was sent to the randomly generated number to verify if it exists). No landlines were considered for this exercise. Information on socio-demographic characteristics of the respondents was unknown prior to dialling, and thus screening questions were used to achieve sex, age, region and education quotas. The quotas were calculated utilizing national household survey and population census data. Mobile phone coverage was above 70 per cent in most countries considered, with differences based on sex, age, educational attainment, and location.
Weighting
Estimates are weighted using iterative proportional fitting, more commonly referred to as raking, whereby iterative adjustments were made until the sample distribution aligned with that of the population for sex, age, location and education. Weight efficiency was considered (to avoid affecting the power of the estimates) and improved by trimming (to reduce the impact on the variance of the final weight) or by merging weighting categories. The estimates generated by RGAs aren’t meant to replace official statistics or be used for SDG monitoring.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2021-09-14 | 2021-12-08 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Cecilia Tinonin Cecilia Tinonin | UN Women | [email protected] |
| Sara Duerto Valero | UN Women | [email protected] |
Confidentiality
See https://data.unwomen.org/
Citation requirements
Copyright: Asian Development Bank and UN Women 2022
Disclaimer and copyrights
Disclaimer
ADB and UN Women do not accept any responsibility for any consequence of data use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB or UN Women in preference to others of a similar nature that are not mentioned.
By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB and UN Women do not intend to make any judgments as to the legal or other status of any territory or area.
By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB and UN Women do not intend to make any judgments as to the legal or other status of any territory or area.
Metadata production
DDI Document ID
DDI_KIR_2021_RGAS_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata producer |
DDI Document version
KIR_2021_RGAS_v01_EN_M_v01_A_OCS_v01