For further information on similar studies, see: https://data.unwomen.org/rga
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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Modules included in the survey are as follows:
- MAIN ECONOMIC ACTIVITY,
- UNPAID DOMESTIC AND CARE WORK,
- FOOD HARDSHIP,
- PERSONAL AND HOUSEHOLD INCOME,
- AND GOVERNMENT SUPPORT.
Unpaid domestic and care work
Vaccines coverage and hesitancy
Fuel and water collection
The target population are individuals 18 years and above, with access to a mobile phone.
Producers and sponsors
Asian Development Bank
Department of Foreign Affairs and Trade - Government of Australia
Asian Development Bank
The RGAs were rolled out in Pakistan (n = 3,636), 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.
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.
Copyright: Asian Development Bank and UN Women 2022
Disclaimer and copyrights
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.