COVID-19 High Frequency Phone Survey of Households 2020, Round 2
Vietnam, 2020
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Reference ID
VNM_2020_HFPS-R2_v01_M
Producer(s)
World Bank
Collection(s)
Metadata
Created on
Sep 30, 2021
Last modified
Nov 23, 2021
Page views
6672
Downloads
309
Identification
Survey ID Number
VNM_2020_HFPS-R2_v01_M
Title
COVID-19 High Frequency Phone Survey of Households 2020, Round 2
Country/Economy
| Name | Country code |
|---|---|
| Vietnam | VNM |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
Series Information
The main objective of this project is to collect household data for the ongoing assessment and monitoring of the socio-economic impacts of COVID-19 on households and family businesses in Vietnam. The estimated field work and sample size of households in each round is as follows:
Round 1 June/July 2020 fieldwork- approximately 6300 households (at least 1300 minority households)
Round 2 July/Aug 2020 fieldwork - approximately 4000 households (at least 1000 minority households)
Round 3 September 2020 - approximately 4000 households (at least 1000 minority households)
Round 4 January 2021 - approximately 4000 households (at least 1000 minority households)
Round 5 March 2021 - approximately 4000 households (at least 1000 minority households)
Additional rounds are under discussion.
Round 1 June/July 2020 fieldwork- approximately 6300 households (at least 1300 minority households)
Round 2 July/Aug 2020 fieldwork - approximately 4000 households (at least 1000 minority households)
Round 3 September 2020 - approximately 4000 households (at least 1000 minority households)
Round 4 January 2021 - approximately 4000 households (at least 1000 minority households)
Round 5 March 2021 - approximately 4000 households (at least 1000 minority households)
Additional rounds are under discussion.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Version
Version Description
Anonymized dataset for public distribution.
Version Date
2021-09-29
Coverage
Geographic Coverage
National, regional
Producers and sponsors
Primary investigators
| Name |
|---|
| World Bank |
Producers
| Name | Role |
|---|---|
| Mekong Development Research Institute | Survey collection firm |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| World Bank | WB | Partially funded the activity |
| Department of Foreign Affairs and Trade of Australia | DFAT | Partially funded the activity |
Sampling
Sampling Procedure
The 2020 Vietnam COVID-19 High Frequency Phone Survey of Households (VHFPS) uses a nationally representative household survey from 2018 as the sampling frame. The 2018 baseline survey includes 46,980 households from 3132 communes (about 25% of total communes in Vietnam). In each commune, one EA is randomly selected and then 15 households are randomly selected in each EA for interview. We use the large module of to select the households for official interview of the VHFPS survey and the small module households as reserve for replacement. After data processing, the final sample size for Round 2 is 3,935 households.
Weighting
The main steps for weight adjustment to ensure national and regional representativeness are:
(1) Start with base weights from 2018 survey
(2) HH selection and non-response adjustment using propensity score and probability of selection correction.
(3) Post-stratification: Rescale weights to match national, region, urban/rural populations based on the 2019 population census.
(4) Trim weights
(1) Start with base weights from 2018 survey
(2) HH selection and non-response adjustment using propensity score and probability of selection correction.
(3) Post-stratification: Rescale weights to match national, region, urban/rural populations based on the 2019 population census.
(4) Trim weights
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2020-07-27 | 2020-08-12 |
Time periods
| Start date | End date |
|---|---|
| 2020-07-27 | 2020-08-12 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Supervision
World Bank
Data Collectors
| Name | Abbreviation |
|---|---|
| Mekong Development Research Institute | MDRI |
Questionnaires
Questionnaires
The questionnaire for Round 2 consisted of the following sections
Section 2. Behavior
Section 3. Health
Section 5. Employment (main respondent)
Section 6. Coping
Section 7. Safety Nets
Section 8. FIES
Section 2. Behavior
Section 3. Health
Section 5. Employment (main respondent)
Section 6. Coping
Section 7. Safety Nets
Section 8. FIES
Data Processing
Data Editing
Data cleaning began during the data collection process. Inputs for the cleaning process include available interviewers’ note following each question item, interviewers’ note at the end of the tablet form as well as supervisors’ note during monitoring. The data cleaning process was conducted in following steps:
• Append households interviewed in ethnic minority languages with the main dataset interviewed in Vietnamese.
• Remove unnecessary variables which were automatically calculated by SurveyCTO
• Remove household duplicates in the dataset where the same form is submitted more than once.
• Remove observations of households which were not supposed to be interviewed following the identified replacement procedure.
• Format variables as their object type (string, integer, decimal, etc.)
• Read through interviewers’ note and make adjustment accordingly. During interviews, whenever interviewers find it difficult to choose a correct code, they are recommended to choose the most appropriate one and write down respondents’ answer in detail so that the survey management team will justify and make a decision which code is best suitable for such answer.
• Correct data based on supervisors’ note where enumerators entered wrong code.
• Recode answer option “Other, please specify”. This option is usually followed by a blank line allowing enumerators to type or write texts to specify the answer. The data cleaning team checked thoroughly this type of answers to decide whether each answer needed recoding into one of the available categories or just keep the answer originally recorded. In some cases, that answer could be assigned a completely new code if it appeared many times in the survey dataset.
• Examine data accuracy of outlier values, defined as values that lie outside both 5th and 95th percentiles, by listening to interview recordings.
• Final check on matching main dataset with different sections, where information is asked on individual level, are kept in separate data files and in long form.
• Label variables using the full question text.
• Label variable values where necessary.
• Append households interviewed in ethnic minority languages with the main dataset interviewed in Vietnamese.
• Remove unnecessary variables which were automatically calculated by SurveyCTO
• Remove household duplicates in the dataset where the same form is submitted more than once.
• Remove observations of households which were not supposed to be interviewed following the identified replacement procedure.
• Format variables as their object type (string, integer, decimal, etc.)
• Read through interviewers’ note and make adjustment accordingly. During interviews, whenever interviewers find it difficult to choose a correct code, they are recommended to choose the most appropriate one and write down respondents’ answer in detail so that the survey management team will justify and make a decision which code is best suitable for such answer.
• Correct data based on supervisors’ note where enumerators entered wrong code.
• Recode answer option “Other, please specify”. This option is usually followed by a blank line allowing enumerators to type or write texts to specify the answer. The data cleaning team checked thoroughly this type of answers to decide whether each answer needed recoding into one of the available categories or just keep the answer originally recorded. In some cases, that answer could be assigned a completely new code if it appeared many times in the survey dataset.
• Examine data accuracy of outlier values, defined as values that lie outside both 5th and 95th percentiles, by listening to interview recordings.
• Final check on matching main dataset with different sections, where information is asked on individual level, are kept in separate data files and in long form.
• Label variables using the full question text.
• Label variable values where necessary.
Other Processing
For the creation of the public data set, additional anonymization processes were conducted
• Create anonymized household and respondent ids. Households can only be identifiable by region and urban/rural location.
• Remove text responses.
• Aggregate low frequency response categories.
• Drop questions that cannot be properly anonymized.
• Remove questions that may contain sensitive information.
• Create anonymized household and respondent ids. Households can only be identifiable by region and urban/rural location.
• Remove text responses.
• Aggregate low frequency response categories.
• Drop questions that cannot be properly anonymized.
• Remove questions that may contain sensitive information.
Access policy
Confidentiality
Citation requirements
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
World Bank. Vietnam COVID-19 High Frequency Phone Survey of Households (HFPS-R2) 2020, Round 2. Ref. VNM_2020_HFPS-R2_v01_M. Dataset downloaded from www.microdata.worldbank.org on [date].
- 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
World Bank. Vietnam COVID-19 High Frequency Phone Survey of Households (HFPS-R2) 2020, Round 2. Ref. VNM_2020_HFPS-R2_v01_M. Dataset downloaded from www.microdata.worldbank.org on [date].
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_VNM_2020_HFPS-R2_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the Study |
Date of Metadata Production
2021-09-22
DDI Document version
Version 01