Abstract

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

Geographic coverage

Sample excludes frontier governorates (Matruh, New Valley, North Sinai, Red Sea, and South Sinai) because of their remoteness and small population share. The excluded areas represent less than 2% of the population.

Analysis unit

Individuals

Universe

The target population is the civilian, non-institutionalized population 15 years and above.

Kind of data

Observation data/ratings [obs]

Sampling procedure

The indicators in the 2017 Global Findex database are drawn from survey data covering almost 150,000 people in 144 economies-representing more than 97 percent of the world’s population (see table A.1 of the Global Findex Database 2017 Report for a list of the economies included). The survey was carried out over the 2017 calendar year by Gallup, Inc., as part of its Gallup World Poll, which since 2005 has annually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 150 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. Interview procedure Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or where this is the customary methodology. In most economies the fieldwork is completed in two to four weeks.

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 handheld 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 economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or household enumeration method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

The sample size was 1000.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in more than 140 languages upon request.

Questions on cash on delivery, saving using an informal savings club or person outside the family, domestic remittances, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

Sampling error estimates

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, and Jake Hess. 2018. The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution. Washington, DC: World Bank

In this study we use long-term satellite, climate, and crop observations to document the spatial distribution of the recent stagnation in food grain production affecting the water-limited tropics (WLT), a region where 1.5 billion people live and depend on local agriculture that is constrained by chronic water shortages. Overall, our analysis shows that the recent stagnation in food production is corroborated by satellite data. The growth rate in annually integrated vegetation greenness, a measure of crop growth, has declined significantly (p < 0.10) in 23% of the WLT cropland area during the last decade, while statistically significant increases in the growth rates account for less than 2%. In most countries, the decade-long declines appear to be primarily due to unsustainable crop management practices rather than climate alone. One quarter of the statistically significant declines are observed in India, which with the world’s largest population of food-insecure people and largest WLT croplands, is a leading example of the observed declines. Here we show geographically matching patterns of enhanced crop production and irrigation expansion with groundwater that have leveled off in the past decade. We estimate that, in the absence of irrigation, the enhancement in dry-season food grain production in India, during 1982–2002, would have required an increase in annual rainfall of at least 30% over almost half of the cropland area. This suggests that the past expansion of use of irrigation has not been sustainable. We expect that improved surface and groundwater management practices will be required to reverse the recent food grain production declines. MDPI and ACS Style Milesi, C.; Samanta, A.; Hashimoto, H.; Kumar, K.K.; Ganguly, S.; Thenkabail, P.S.; Srivastava, A.N.; Nemani, R.R.; Myneni, R.B. Decadal Variations in NDVI and Food Production in India. Remote Sens. 2010, 2, 758-776. AMA Style Milesi C., Samanta A., Hashimoto H., Kumar K.K., Ganguly S., Thenkabail P.S., Srivastava A.N., Nemani R.R., Myneni R.B. Decadal Variations in NDVI and Food Production in India. Remote Sensing. 2010; 2(3):758-776. Chicago/Turabian Style Milesi, Cristina; Samanta, Arindam; Hashimoto, Hirofumi; Kumar, K. Krishna; Ganguly, Sangram; Thenkabail, Prasad S.; Srivastava, Ashok N.; Nemani, Ramakrishna R.; Myneni, Ranga B. 2010. "Decadal Variations in NDVI and Food Production in India." Remote Sens. 2, no. 3: 758-776.

Abstract

The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

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 about 128,000 adults in more than 120 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.

The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

Geographic coverage

Three districts in the North region were excluded for security reasons – Kotido, Moroto Nakapiripirit. The excluded areas represent 2% or less of the population.

Analysis unit

Individual

Kind of data

Observation data/ratings [obs]

Sampling procedure

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. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

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 Uganda is 1000.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaires are available on the website.

Sampling error estimates

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.

The Office for National Statistics (ONS) publishes data on the number of live births by the mother's country of birth in England and Wales each year. Every time a birth is registered in England and Wales both parents are required to state their places of birth on their child's birth certificate, and this information is then collated to produce these statistics. In order to make it easier to look at what these data tell us about births in London, and how these have been changing over time, the GLA Demography team has extracted the data which relate to London from the main ONS dataset since 2001 and presented it here in an easily accessible format. For more information about how the ONS produces these statistics, please visit their website: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths For more information about how we extracted these data and created this report, please this project's Github repository: https://github.com/Greater-London-Authority/births_by_mothers_country_of_birth Since 2001, the number of live births being recorded in London has changed from 104,162 to 104,246 births per year. The proportion of births which were to mothers who had been born outside the UK has changed from 43% in 2001 to 59% in the most recent year (2023). In 2023, the region of origin which supplied the largest number of births to non-UK-born mothers in London was Asia with 24,004, followed by the Africa which provided 10,596. The region of origin which has seen the largest change since 2001 is the Asia, which went from 13,489 live births per year in 2001 to 24,004 in 2023. In 2023, the region with the largest number of births to non-UK-born mothers was London with 61,357 live births (59% of all live births in London). By contrast, the region with the lowest number of births to non-UK-born mothers was the Wales with 3,891 live births to non-UK-born mothers, which only represented 14% of all live births in that region. The data shows that London accounted for 33% of all the births to non-UK-born mothers in England and Wales in 2023, which was a far higher proportion than any other region. These data also highlight a couple of other interesting comparisons. Firstly, despite being the second largest region in England and Wales in terms of population, London is not the region with the largest number of births to UK-born mothers. Secondly, London is the only region to have relatively large numbers of mothers from every region of the world according to the way in which the ONS has categorised them, including Africa, non-EU European countries (such as Turkey and Russia) and the 'Rest of the World' (which includes the Americas and Oceania). The data comparing London with England & Wales excluding London and England & Wales as a whole (including London) is provided in the table below: Total Births - UK Mothers Total Births - Overseas Mothers Pre-2004 EU countries Post-2004 EU accession countries Rest of Europe Asia Africa Rest of the world Year Region No. % No. % No. % No. % No. % No. % No. % No. % 2023 London 42,889 41% 61,357 59% 6,505 6% 8,265 8% 5,985 6% 24,004 23% 10,596 10% 6,002 6% 2023 Rest of England & Wales 360,109 74% 126,540 26% 10,590 2% 26,464 5% 6,587 1% 49,668 10% 26,014 5% 7,217 1% 2023 England & Wales 402,998 68% 187,897 32% 17,095 3% 34,729 6% 12,572 2% 73,672 12% 36,610 6% 13,219 2% Births by Mother's Country of Birth by London Borough

The global road network is rapidly growing associated with human economic development. This growth also entails a high toll for biodiversity, with several well-documented negative impacts on different species. However, there is still a great lack of knowledge about the effects of roads on the persistence of wildlife populations. Here, we aimed to summarize our current knowledge on this topic, based on systematic reviews. We found that only a small proportion of studies (8%) focused on the effects of roads on population persistence. Most of these studies were about large mammals and were performed in high-income countries. Furthermore, these works studied only 2% of those species identified by the IUCN Red List as threatened by roads. Overall, our results show that we are far from understanding how roads affect the long-term viability of wildlife populations inhabiting road-effect zones. Addressing this challenge will require modifying our conceptual perspective, from short-term to long-term studies, from single road sections to focusing the landscape scale, and strive to obtain empirical data to support sound analyses to assess how road impacts affect the survival of wildlife populations, namely with information required to perform approaches such as population viability analyses. We highlight some key studies from our reviews that have addressed this global conservation concern with population-oriented approaches.