COVID-19 Georgia High Frequency Survey Wave 1, 2020
Georgia, 2020
Poverty and Equity Global Practice
Created on
January 27, 2021
Last modified
January 27, 2021
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Identification
Survey ID Number
GEO_2020_HFS_v01_M
Title
COVID-19 Georgia High Frequency Survey Wave 1, 2020
Country
| Name | Country code |
|---|---|
| Georgia | GEO |
Study type
Socio-Economic/Monitoring Survey [hh/sems]
Series Information
Partnering with the Caucasus Research Resource Centers (CRRC), the South Caucasus team in the Poverty and Equity Global Practice at the World Bank conducted a COVID-19 Georgia High Frequency Survey: Wave 1 (COVID-19 GHFS) to monitor the impact of COVID-19 on households in Georgia. The survey was collected in December 2020, and is the first of the two planned surveys to be completed by early 2021. The second Wave is expected to be conducted in January/February 2021.This survey is designed so that it also serves as the follow-up to the COVID-19 Monitor Survey (waves 1-6) conducted between late April and early June, 2020.
Abstract
Having reliable, timely data on poverty and inequality is critical to assess the distributional impact of COVID-19 on households and to make near-real time evidence-based strategic decisions. Partnering with the Caucasus Research Resource Centers (CRRC), the South Caucasus team in the Poverty and Equity Global Practice at the World Bank conducted a COVID-19 Georgia High Frequency Survey: Wave 1 (COVID-19 GHFS) to monitor the impact of COVID-19 on households in Georgia, conducted in December 2020, and is the first of the two planned surveys to be completed by early 2021. This survey is designed so that it also serves as the follow-up to the COVID-19 Monitor (waves 1-6) conducted between late April and early June, 2020.
COVID-19 GHFS allows one not only to monitor the COVID-19 impacts on the households but also capture the impact on poverty and a shift in households’ status from poor to non-poor due to COVID-19 pandemic. COVID-19 GHFS does not collect consumption data which can be time-consuming and vulnerable to error, which prohibits direct estimation of households’ poverty status. However, GHFS collects poverty correlates, such as household’s demography, ownership of assets and access to services which would then be converted to poverty statistics using estimation models.
COVID-19 GHFS allows one not only to monitor the COVID-19 impacts on the households but also capture the impact on poverty and a shift in households’ status from poor to non-poor due to COVID-19 pandemic. COVID-19 GHFS does not collect consumption data which can be time-consuming and vulnerable to error, which prohibits direct estimation of households’ poverty status. However, GHFS collects poverty correlates, such as household’s demography, ownership of assets and access to services which would then be converted to poverty statistics using estimation models.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household, Individual (adult over age 18)
Version
Version Description
- v2.1: Edited, anonymous dataset for public distribution.
Version Date
2021-01-26
Scope
Notes
The COVID-19 Georgia High Frequency Survey (GHFS) 2020-21 - wave 1 comprises following modules: 1 - Household Identification, 2 - Household Demographics, 3 - Assets and Access to Internet, 4 - Prevalence of COVID-19, 5 - Distance Learning, 6 - Employment Dynamics, 7 - Income, 8 - Food Security, 9 - Shocks and Coping Strategies, 10 - Vaccine, 11 - Perception.
Coverage
Geographic Coverage
National coverage, representative at the national-, rural/urban/Tbilisi-levels.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Poverty and Equity Global Practice | The World Bank |
Producers
| Name | Role |
|---|---|
| Caucasus Research Resource Centers | Data Collection |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| The World Bank | WB |
Sampling
Sampling Procedure
The COVID-19 GHFS is based on phone-interviews with application of Computer Assisted Telephone Interviews (CATI) and random digit dialing (RDD). The sampling frame is representative of the national and rural/urban/Tbilisi population. 1986 valid interviews were concluded in December 2020, equivalent to the response rate of 40%.
Response Rate
40%
Weighting
Weights were adjusted by post-stratification. Details are provided in the CRRC Fieldwork Report COVID 19 WB.
Population weight can be estimated by multiplying HH weight with HH size.
Population weight can be estimated by multiplying HH weight with HH size.
Data Collection
Dates of Data Collection
| Start |
|---|
| 2020-12-24 |
Time periods
| Start date |
|---|
| 2020-12-24 |
Data Collection Mode
Computer Assisted Telephone Interview [cati]
Supervision
Fieldwork personnel consisted of 44 individuals in total (40 interviewers and 4 supervisors). Details are provided in the CRRC Fieldwork Report.
Data Collection Notes
Data collection took place between the 18th and 24th of December. The average interview time was 7.6 minutes. Data collection took place throughout the day on all days of fieldwork. 90% of completed interviews were completed on the first contact attempt, 7% on the 2nd attempt, and 3% on the third contact attempt.
Data Collectors
| Name | Abbreviation |
|---|---|
| Caucasus Research Resource Center | CRRC |
Data Processing
Data Editing
Data cleaning was carried out to identify and, where possible, correct inconsistencies. In addition, open-ended questions with textual responses were recoded so that these answers matched numeric codes. With CATI, the cleaning process was straightforward: pre-programmed questionnaire forms helped to eliminate ambiguous codes from being entered in the dataset. Also, the form did not accept errors related to selecting more values than permitted in the questionnaire. Additional protocols for data cleaning are summarized in Table 8 in the CRRC Fieldwork Report.
Other Processing
Weighting
Census data was used to calculate poststratification weights for individuals and households. For individual level weights national data on adult population by settlement type (Capital Urban or Rural) , ethnicity (Georgian or other), age group (18-34, 35-54 and 55+), sex, and education (secondary or lower, vocational, and higher) were used. Census data on the average household size and number of households was used to calculate post stratification household weights.
Back Check
CRRC-Georgia conducted a back check of 10% of the interviews after the fieldwork. The back check fieldwork was conducted on December 23-25, 2020 simultaneously with the fieldwork. The backcheck fieldwork personnel consisted of 1 interviewer. The backcheck showed that interviews were conducted properly and only two of them were removed, one respondent was not eligible because of the age and one number was not registered.
Back check interviews were selected using RAND() function in excel one day before the fieldwork was over. In sum, 200 interviews were selected and checked.
Census data was used to calculate poststratification weights for individuals and households. For individual level weights national data on adult population by settlement type (Capital Urban or Rural) , ethnicity (Georgian or other), age group (18-34, 35-54 and 55+), sex, and education (secondary or lower, vocational, and higher) were used. Census data on the average household size and number of households was used to calculate post stratification household weights.
Back Check
CRRC-Georgia conducted a back check of 10% of the interviews after the fieldwork. The back check fieldwork was conducted on December 23-25, 2020 simultaneously with the fieldwork. The backcheck fieldwork personnel consisted of 1 interviewer. The backcheck showed that interviews were conducted properly and only two of them were removed, one respondent was not eligible because of the age and one number was not registered.
Back check interviews were selected using RAND() function in excel one day before the fieldwork was over. In sum, 200 interviews were selected and checked.
Access policy
Access authority
| Name | Affiliation | URL |
|---|---|---|
| Microdata Library | World Bank | microdata.worldbank.org |
Contacts
| Name | Affiliation | |
|---|---|---|
| Alan Fuchs Tarlovsky | WBG | afuchs@worldbank.org |
| Natsuko Kiso Nozaki | WBG | nkiso@worldbank.org |
Access conditions
Public Use Files
Citation requirements
The use of the datasets must be acknowledged using a citation which would include:
- the identification of the Primary Investigator (including country name);
- the full title of the survey and its acronym (when available), and the year(s) of implementation;
- the survey reference number;
- the source and date of download (for datasets disseminated online).
Example:
Poverty and Equity Global Practice, The World Bank. COVID-19 Georgia High Frequency Survey (GHFS) Wave 1, 2020. Ref. GEO_2020_HFS_v01_M. Dataset downloaded from [URL] on [date
- the identification of the Primary Investigator (including country name);
- the full title of the survey and its acronym (when available), and the year(s) of implementation;
- the survey reference number;
- the source and date of download (for datasets disseminated online).
Example:
Poverty and Equity Global Practice, The World Bank. COVID-19 Georgia High Frequency Survey (GHFS) Wave 1, 2020. Ref. GEO_2020_HFS_v01_M. Dataset downloaded from [URL] on [date
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector 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.
Copyright
The World Bank
Metadata production
DDI Document ID
DDI_GEO_2020_HFS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | World Bank | DECDG | Documentation of the Study |
Date of Metadata Production
2021-01-26
DDI Document version
Version 01