YEM_2022_YMPS-R1_v01_M
Mobile Phone Survey Monitoring Round I, 2022
Monitoring Food Insecurity and Employment in Yemen
Name | Country code |
---|---|
Yemen | YEM |
Other Household Survey [hh/oth]
This is the first round of a series of mobile phone surveys
Household and individual
v2.1: Edited, anonymous dataset for public distribution.
Food security, displacement, income sources and working conditions
All governorates of Yemen except for Socotra islands
Name | Affiliation |
---|---|
Alia Aghajanian | World Bank |
Name | Affiliation | Role |
---|---|---|
Romeo Gansey | World Bank | Data analyst |
Name | Role |
---|---|
Joint Data Center on Forced Displacement (World Bank and UNHCR) Forced Displacement | Funder |
The survey used random digit dialing, relying on the range of valid numbers, with up to three attempts when a phone number was not reached—that is, the call unanswered, not picked up, picked up but unable to complete the interview at that time.
We used sample quotas were to obtain a diverse set of individuals across the governorates of Abyan, Aden, Al-Baida, Al-Dhale, Al-Hodeida, Al-Jawf, Al-Maharh, Al-Mahweet, Amran, Dhamar, Hadramout, Hajja, Ibb, Laheg, Mareb, Remah, Saadah, and Sanaa City.
Some governorate quotas were not achieved due to small populations with mobile phones, lack of infrastructure for mobile phones, or blocking of international numbers for certain mobile phone service providers.
A total of 1,297 respondents completed the interview resulting in a response rate of around 28 percent, indicating the difficulty of completing phone interviews.
The individual-level selection probabilities were modeled as if based on a stratified sampling design, where the governorates serve as the strata; 2017 projected population counts at the governorate level were available and based on the 2004 census. Hence, an individual’s selection probability was taken to be the ratio of the number of sampled individuals from the corresponding stratum and the projected governorate population size.
Household-level selection probabilities were modeled as if they were proportional to the household size, since any respondent residing in the corresponding household could have reported on household-level characteristics.
In some cases, sample respondents reported extremely large and unrealistic household sizes. As this may be due to observational error, the set of household size observations were Winsorized at the 90th percentile, which was found to be ten for these observations.
The selection probability for the sample respondents was taken to be proportional to the resulting observations.
For both the individual-level and household-level weights, we used a raking ratio calibration scheme to obtain the calibrated weights. We used the R programming language (R Core Team, 2016) with the aid of the “survey” package (Lumley, 2020, 2004) to calculate the calibrated weights.
Start | End | Cycle |
---|---|---|
2022-08 | 2022-09 | Round 1 |
Data was collected by a firm based in Amman, Jordan - Mindset. Interviews lasted approximately 30 minutes.
Name |
---|
Poverty Reduction and Policy Management Network (PREM) |
Name | Affiliation |
---|---|
Alia Aghajanian | World Bank |
Confidentiality declaration text |
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Data has been anonymized |
When using data the accompanying report should be cited for methodology and background.
Use of the dataset must be acknowledged using a citation which would include:
Example:
Alia Aghajanian (World Bank). Yemen - Mobile Phone Survey Monitoring Round I, 2022, Monitoring Food Insecurity and Employment in Yemen (YMPS 2022 R1). Ref: YEM_2022_YMPS-R1_v01_M. Downloaded from [uri] on [date].
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | |
---|---|---|
Alia Aghajanian | World Bank | aaghajanian@worldbank.org |
DDI_YEM_2022_YMPS-R1_v01_M_WB
Name | Affiliation | Role |
---|---|---|
Development Data Group | World Bank | Documentation of the study |
2023-09-07
Version 01 (2023-09-07)
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