Mobile Phone Survey Monitoring Round I, 2022
Monitoring Food Insecurity and Employment in Yemen
Yemen, Rep., 2022
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Reference ID
YEM_2022_YMPS-R1_v01_M
Producer(s)
Alia Aghajanian
Collection(s)
Metadata
Created on
Sep 07, 2023
Last modified
Sep 07, 2023
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Identification
Survey ID Number
YEM_2022_YMPS-R1_v01_M
Title
Mobile Phone Survey Monitoring Round I, 2022
Subtitle
Monitoring Food Insecurity and Employment in Yemen
Country/Economy
| Name | Country code |
|---|---|
| Yemen | YEM |
Study type
Other Household Survey [hh/oth]
Series Information
This is the first round of a series of mobile phone surveys
Abstract
The survey draws on a probability sample of 1,297 adult Yemenis (18 years of age and older) with mobile phones, targeted across 21 governorates based on the latest population projections. Interviews were conducted over the phone in August and September 2022, using a questionnaire consisting of four sections mainly focusing on labor market experiences and food insecurity. Although the survey was implemented over the phone, it is expected to have adequate coverage of the target population, as mobile phone ownership was widespread in Yemen prior to the start of the conflict. According to the Household Budget survey of 2014, 81 percent of households owned a mobile phone. While there is no recent national level data on mobile phone ownership, representative data of areas under IRG control show that mobile phone ownership increased from 84 percent in 2014 to 92 percent in 2021 (Yemen Human Development Survey 2021). Additionally, a study comparing the number of mobile phones households owned in the World Food Programme (WFP) mobile Vulnerability Analysis and Mapping (mVAM) phone survey finds a similar number to that of the last nationally representative survey, the 2014 Household Budget Survey (HBS), except for some governorates where the number of mobile phones declined due to significant population migration.
Unit of Analysis
Household and individual
Version
Version Description
v2.1: Edited, anonymous dataset for public distribution.
Scope
Notes
Food security, displacement, income sources and working conditions
Coverage
Geographic Coverage
All governorates of Yemen except for Socotra islands
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Alia Aghajanian | World Bank |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Romeo Gansey | World Bank | Data analyst |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Joint Data Center on Forced Displacement (World Bank and UNHCR) Forced Displacement | JDC | Funder |
Sampling
Sampling Procedure
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.
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.
Deviations from the Sample Design
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.
Response Rate
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.
Weighting
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.
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.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2022-08 | 2022-09 | Round 1 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Data Collection Notes
Data was collected by a firm based in Amman, Jordan - Mindset. Interviews lasted approximately 30 minutes.
Data Processing
Other Processing
Some variables (such as age), have been categorized into groups following a data disclosure risk assessment.
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Alia Aghajanian | World Bank | aaghajanian@worldbank.org |
Confidentiality
Data has been anonymized
Citation requirements
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:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
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].
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
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].
Access authority
| Name | Affiliation |
|---|---|
| Alia Aghajanian | World Bank |
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_YEM_2022_YMPS-R1_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the study |
Date of Metadata Production
2023-09-07
DDI Document version
Version 01 (2023-09-07)