LSO_2022_FINDEX_v01_M
Global Financial Inclusion (Global Findex) Database 2021
Name | Country code |
---|---|
Lesotho | LSO |
Other Household Survey [hh/oth]
The Global Findex is the world’s most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of almost 145,000 adults in 139 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments. Due to ongoing COVID-19 restrictions that were in place in 2021, Global Findex 2021 data for 16 countries were collected through face-to-face interviews in 2022 and released now.
Observation data/ratings [obs]
Version 01: Edited, anonymous dataset for public distribution.
2023-05-19
This is the second update (May 2023) to the microdata originally released in Oct 2022 with the first update in Dec 2022. This includes 16 new countries that were surveyed in 2022 (Azerbaijan, Botswana, Chad, Comoros, Congo, Dem. Rep., Eswatini, Ethiopia, Gambia, The, Guatemala, Lesotho, Madagascar, Mauritania, Mexico, Niger, Vietnam, Yemen, Rep.). Please also see Microdata_update_details_2022.xlsx which details these updates.
The indicators in the Global Findex 2021 database are drawn from survey data covering almost 145,000 people in 139 economies, representing 97 percent of the world’s population. Data is available for 2021, 2017, 2014, and 2011.
National coverage
Name | Affiliation |
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Development Research Group, Finance and Private Sector Development Unit | World Bank |
Name | Role |
---|---|
Gallup, Inc. | Carried out the survey in association with its annual Gallup World Poll. |
Name | Role |
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Development Research Group, World Bank | Funded the study |
The Bill and Melinda Gates Foundation | Financial support |
In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19–related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Additionally, phone surveys were not a viable option in 16 economies in 2021, which were then surveyed in 2022.
In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.
In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.
The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).
For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.
Sample size for Lesotho is 1010.
Data weighting is used to ensure a nationally representative sample for each economy. Final weights consist of the base sampling weight, which corrects for unequal probability of selection based on household size, and the poststratification weight, which corrects for sampling and nonresponse error. Poststratification weights use economy-level population statistics on gender and age and, where reliable data are available, education or socioeconomic status.
Questionnaires are available on the website.
Start | End |
---|---|
2022-09-10 | 2022-12-25 |
Data was collected in the following language(s): English, Sesotho
Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.
Name | Affiliation | |
---|---|---|
GlobalFindex | World Bank | globalfindex@worldbank.org |
Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.
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 | |
---|---|---|
GlobalFindex | World Bank | globalfindex@worldbank.org |
Saniya Ansar | World Bank | sansar1@worldbank.org |
Jijun Wang | World Bank | jwang36@worldbank.org |
Mansi Vipin Panchamia | World Bank | mpanchamia@worldbank.org |
DDI_LSO_2022_FINDEX_v01_M_WB
Name | Affiliation | Role |
---|---|---|
Development Economics Data Group | The World Bank | Documentation of the DDI |
2023-05-23
Version 01 (May 2023).
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