IndicatorName: Cost of business start-up procedures (% of GNI per capita)

Limitationsandexceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures.

Statisticalconceptandmethodology:
Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.

Entrepreneurs around the world face a range of challenges. One of them is inefficient regulation. The indicator measures the procedures, time, cost and paid-in minimum capital required for a small or medium-size limited liability company to start up and formally operate.

The Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.


Aggregationmethod: Unweighted average

Developmentrelevance:
The economic health of a country is measured not only in macroeconomic terms but also by other factors that shape daily economic activity such as laws, regulations, and institutional arrangements. The data measure business regulation, gauge regulatory outcomes, and measure the extent of legal protection of property, the flexibility of employment regulation, and the tax burden on businesses.

The fundamental premise of this data is that economic activity requires good rules and regulations that are efficient, accessible to all who need to use them, and simple to implement. Thus sometimes there is more emphasis on more regulation, such as stricter disclosure requirements in related-party transactions, and other times emphasis is on for simplified regulations, such as a one-stop shop for completing business startup formalities.

Entrepreneurs may not be aware of all required procedures or may avoid legally required procedures altogether. But where regulation is particularly onerous, levels of informality are higher, which comes at a cost: firms in the informal sector usually grow more slowly, have less access to credit, and employ fewer workers - and those workers remain outside the protections of labor law. The indicator can help policymakers understand the business environment in a country and - along with information from other sources such as the World Bank's Enterprise Surveys - provide insights into potential areas of reform.

Generalcomments: Data are presented for the survey year instead of publication year.

IndicatorName: Time required to start a business (days)

License_Type: CC BY-4.0

Longdefinition: Time required to start a business is the number of calendar days needed to complete the procedures to legally operate a business. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.

Periodicity: Annual

Source: World Bank, Doing Business project (http://www.doingbusiness.org/). NOTE: Doing Business has been discontinued as of 9/16/2021. For more information: https://bit.ly/3CLCbme

Topic: Entrepreneurship


IndicatorName: Time required to start a business, female (days)

Limitationsandexceptions: The Doing Business methodology has limitations that should be considered when interpreting the data. First, the data collected refer to businesses in the economy's largest city and may not represent regulations in other locations of the economy. To address this limitation, subnational indicators are being collected for selected economies. These subnational studies point to significant differences in the speed of reform and the ease of doing business across cities in the same economy. Second, the data often focus on a specific business form - generally a limited liability company of a specified size - and may not represent regulation for other types of businesses such as sole proprietorships. Third, transactions described in a standardized business case refer to a specific set of issues and may not represent the full set of issues a business encounters. Fourth, the time measures involve an element of judgment by the expert respondents. When sources indicate different estimates, the Doing Business time indicators represent the median values of several responses given under the assumptions of the standardized case. Fifth, the methodology assumes that a business has full information on what is required and does not waste time when completing procedures. Please also see: https://www.doingbusiness.org/en/about-us/faq

Statisticalconceptandmethodology:
Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.

Entrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the time for a small- to medium-size limited liability company to start up and formally operate in each economy’s largest business city.  To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals.  The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.

The Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.


Developmentrelevance:
The economic health of a country is measured not only in macroeconomic terms but also by other factors that shape daily economic activity such as laws, regulations, and institutional arrangements. The Doing Business data measure business regulation, gauge regulatory outcomes, and measure the extent of legal protection of property, the flexibility of employment regulation, and the tax burden on businesses.

The fundamental premise of this data is that economic activity requires good rules and regulations that are efficient, accessible to all who need to use them, and simple to implement. Thus sometimes there is more emphasis on more regulation, such as stricter disclosure requirements in related-party transactions, and other times emphasis is on for simplified regulations, such as a one-stop shop for completing business startup formalities.

Entrepreneurs may not be aware of all required procedures or may avoid legally required procedures altogether. But where regulation is particularly onerous, levels of informality are higher, which comes at a cost: firms in the informal sector usually grow more slowly, have less access to credit, and employ fewer workers - and those workers remain outside the protections of labor law. The indicator can help policymakers understand the business environment in a country and - along with information from other sources such as the World Bank's Enterprise Surveys - provide insights into potential areas of reform.

IndicatorName: Time required to start a business, male (days)


IndicatorName: Start-up procedures to register a business (number)

Longdefinition: Start-up procedures are those required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Data are for businesses with specific characteristics of ownership, size, and type of production.


IndicatorName: Start-up procedures to register a business, female (number)

Statisticalconceptandmethodology:
Data are collected by the World Bank with a standardized survey that uses a simple business case to ensure comparability across economies and over time - with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys are administered through more than 9,000 local experts, including lawyers, business consultants, accountants, freight forwarders, government officials, and other professionals who routinely administer or advise on legal and regulatory requirements.

Entrepreneurs around the world face a range of challenges. One of them is inefficient regulation. This indicator measures the number of procedure for a small- to medium-size limited liability company to start up and formally operate in each economy’s largest business city.  To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals.  The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.

The Doing Business project of the World Bank encompasses two types of data: data from readings of laws and regulations and data on time and motion indicators that measure efficiency in achieving a regulatory goal. Within the time and motion indicators cost estimates are recorded from official fee schedules where applicable. The data from surveys are subjected to numerous tests for robustness, which lead to revision or expansion of the information collected.


IndicatorName: Start-up procedures to register a business, male (number)

Statisticalconceptandmethodology: This indicator measures the number of procedures for a small- to medium-size limited liability company to start up and formally operate in each economy’s largest business city.  To make the data comparable across 190 economies, Doing Business uses a standardized business that is 100% domestically owned, has a start-up capital equivalent to 10 times the income per capita, engages in general industrial or commercial activities and employs between 10 and 50 people one month after the commencement of operations, all of whom are domestic nationals. The starting a business indicators consider two cases of local limited liability companies that are identical in all aspects, except that one company is owned by five married women and the other by five married men.


Developmentrelevance:
Measuring women’s entrepreneurial activity is critically important for a better understanding of how female entrepreneurs contribute to the economy and society. The lack of comprehensive sex-disaggregated data on business entry and ownership presents a significant obstacle to the global and diversified analysis of female entrepreneurship. Due to insufficient standardized and country-comparable data, the diagnostics of gender gaps in entrepreneurship are limited.
In here, to measure female entrepreneurial activity, annual data is collected directly from 73 company registrars on the number of female/male business owners of LLCs, female/ male sole proprietors and female/ male directors of LLCs, over the past four years.

The importance of female entrepreneurship for economic development is widely recognized. Numerous studies demonstrate the positive impact of female entrepreneurs on economic growth and development, as well as sustainable and durable peace. Moreover, economies characterized by high levels of female entrepreneurial activity are more resilient to financial crises and experience economic slowdowns less frequently. Despite different methodologies, these studies find significant socioeconomic benefits of female entrepreneurship.

Generalcomments: For cross-country comparability, only limited liability corporations that operate in the formal sector are included.

IndicatorName: Number of female directors

Limitationsandexceptions:
The definition of entrepreneurship used is limited to the formal sector. Yet, it should be noted that the exclusion of the informal sector is based on the difficulties of quantifying the number of firms that compose it, rather than on its relevance for developing economies. The Entrepreneurship Database facilitates the analysis of the growth of the formal private sector and the identification of factors that encourage firms to begin operations in or transition to the formal sector. Data is collected all limited liability corporations regardless of size. Partnerships and sole proprietorships are not considered in the analysis due to the differences with respect to their definition and regulation worldwide. Data on the number of total or closed firms are not included due to heterogeneity in how these entities are defined and measured.

The data itself only provides a snapshot of a given economy's business demographics, and cannot by itself explain the factors that affect the business creation cycle. However, when the Entrepreneurship Database is combined with other data such as the Doing Business Report, Investment Climate Assessments, and/or OECD Entrepreneurship Indicators, researchers and policymakers can better understand the dynamics of the business creation process.

Longdefinition: Number of female directors is the number of female individuals who conduct the affairs of newly registered limited liability companies in the calendar year.

Source: World Bank's Entrepreneurship Survey and database (https://www.worldbank.org/en/programs/entrepreneurship). Downloaded on November 29, 2023.

Statisticalconceptandmethodology:
Data are collected by the World Bank Group’s Entrepreneurship Database.  To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.

The data collection process involves telephone interviews and email correspondence with business registries in 73 economies. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data - most often due to an absence of digitized registration systems - the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and private vendors or publicly available data.

The data includes all limited liability corporations regardless of size. Partnerships and sole proprietorships are not considered in the analysis due to the differences with respect to their definition and regulation worldwide. Data on the number of total or closed firms are not included due to heterogeneity in how these entities are defined and measured.


IndicatorName: Share of female directors (% of total directors)

Longdefinition: Share of female directors is the proportion of female directors of newly registered limited liability companies out of the total number of directors of newly registered limited liability companies in the economy in the calendar year. A  director is defined as an individual who conducts the affairs of newly registered limited liability companies in the calendar year.


IndicatorName: Number of male directors


IndicatorName: Share of male directors (% of total directors)

Longdefinition: Share of male directors is the proportion of male directors of newly registered limited liability companies out of the total number of directors of newly registered limited liability companies in the economy in the calendar year. A  director is defined as an individual who conducts the affairs of newly registered limited liability companies in the calendar year.


IndicatorName: Number of female business owners

Longdefinition: Number of female business owners is the number of female individuals that own at least one share of a limited liability company that was newly registered in the calendar year.


IndicatorName: Share of female business owners (% of total business owners)

Longdefinition: Share of female business is the proportion of female newly registered limited liability company owners out of the total number of newly registered limited liability company owners in the economy in the calendar year.


IndicatorName: Number of male business owners

Limitationsandexceptions:
The definition of entrepreneurship used is limited to the formal sector. Yet, it should be noted that the exclusion of the informal sector is based on the difficulties of quantifying the number of firms that compose it, rather than on its relevance for developing economies. The Entrepreneurship Database facilitates the analysis of the growth of the formal private sector and the identification of factors that encourage firms to begin operations in or transition to the formal sector. Data is collected on sole proprietorship. Data on the number of total or closed sole proprietorships are not included.

The data itself only provides a snapshot of a given economy's business demographics, and cannot by itself explain the factors that affect the business creation cycle. However, when the Entrepreneurship Database is combined with other data such as the Doing Business Report, Investment Climate Assessments, and/or OECD Entrepreneurship Indicators, researchers and policymakers can better understand the dynamics of the business creation process.

Longdefinition: Number of female business owners is the number of male individuals that own at least one share of a limited liability company that was newly registered in the calendar  year.


IndicatorName: Share of male business owners  (% of total business owners)

Longdefinition: Share of female business is the proportion of male newly registered limited liability company owners out of the total number of newly registered limited liability company owners in the economy in the calendar year.


Generalcomments: Cross-country comparability is not applicable to sole proprietorships due to differences in definition of sole proprietors across countries.

IndicatorName: Number of female sole proprietors

Limitationsandexceptions:
The definition of entrepreneurship used is limited to the formal sector. Yet, it should be noted that the exclusion of the informal sector is based on the difficulties of quantifying the number of firms that compose it, rather than on its relevance for developing economies. The Entrepreneurship Database facilitates the analysis of the growth of the formal private sector and the identification of factors that encourage firms to begin operations in or transition to the formal sector. Data is collected on sole proprietorship. Data on the number of total or closed sole proprietorships are not included.
                                                                                The data itself only provides a snapshot of a given economy's business demographics, and cannot by itself explain the factors that affect the business creation cycle. However, when the Entrepreneurship Database is combined with other data such as the Doing Business Report, Investment Climate Assessments, and/or OECD Entrepreneurship Indicators, researchers and policymakers can better understand the dynamics of the business creation process.

Longdefinition: Number of female sole proprietors is the number of newly registered sole proprietors owned by female individuals in the calendar year. A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.

Statisticalconceptandmethodology:
Data are collected by the World Bank Group’s Entrepreneurship Database.  To facilitate cross-country comparability, the Entrepreneurship Database employs a consistent unit of measurement, source of information, and concept of entrepreneurship that is applicable and available among the diverse sample of participating economies.

The data collection process involves telephone interviews and email correspondence with business registries in 73 economies. The main sources of information for this study are national business registries. In a limited number of cases where the business registry was unable to provide the data - most often due to an absence of digitized registration systems - the Entrepreneurship Database uses other alternatives sources, such as statistical agencies, tax and labor agencies, chambers of commerce, and private vendors or publicly available data.
                                                                                While sole proprietorships data is collected and presented, due to differences in the definition of sole proprietors across countries, cross-country comparability is applicable only to limited liability corporations that operate in the formal sector.


IndicatorName: Share of female sole proprietors  (% of sole proprietors)

Longdefinition: Share of female sole proprietors is the proportion of female newly registered sole proprietors out of the total number of newly registered sole proprietors in the economy in the calendar year. A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.


IndicatorName: Number of male sole proprietors

Longdefinition: Number of male sole proprietors is the number of newly registered sole proprietors owned by female individuals in the calendar year.  A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.


IndicatorName: Share of male sole proprietors  (% of sole proprietors)

Longdefinition: Share of female sole proprietors is the proportion of male newly registered sole proprietors out of the total number of newly registered sole proprietors in the economy in the calendar year. A sole proprietorship is a business entity owned and managed by a single individual who is indistinguishable from the business and personally liable.


Aggregationmethod: Weighted average

Developmentrelevance: An official proof of identity is essential for participation in economic, social, and political life and for the fulfillment of rights. Without an ID, people can find it difficult or impossible to access social assistance, healthcare, education, open a bank account or activate a SIM card. Countries with (large) gaps in ID ownership will also face added challenges in effectively designing and delivering public services.  Providing “legal identity to all, including birth registration” is a target (16.9) under the Sustainable Development Goals.

IndicatorName: ID ownership, female (% age 15+)

Limitationsandexceptions: In some economies, surveys may not have been able to reach certain areas due to remoteness or conflict.  However, in most cases, the samples are nationally representative and weighted against select demographics. For a full list of exclusions, see The Global Findex Database 2021 report and methodology: https://thedocs.worldbank.org/en/doc/f3ee545aac6879c27f8acb61abc4b6f8-0050062022/original/Findex-2021-Methodology.pdf.

Longdefinition: The percentage of female respondents age 15 and above who report owning a primary foundational ID (national ID or similar credential). If the minimum age for obtaining an ID is above 15, observations below the minimum age are excluded.

Periodicity: Triennial

Source: Global Findex Database

Statisticalconceptandmethodology: ID ownership is calculated based on a survey conducted on representative samples of the non-institutionalized civilian population over age 15. The data is collected in collaboration between the ID4D Initiative and Global Findex, and carried out by Gallup, Inc., as part of its Gallup World Poll. The survey asks respondents whether they personally own the economy’s primary foundational ID, using the actual term for the foundational ID in the local language. A foundational ID system is primarily created to manage identity information for the general population and provide credentials that serve as proof of identity for a wide variety of public and private sector transactions and services. The name of the credentials referenced in the survey is included in the 2021 ID4D Global ID Coverage Estimates report, available at: https://id4d.worldbank.org/global-dataset. For additional details on the survey methodology, see https://thedocs.worldbank.org/en/doc/f3ee545aac6879c27f8acb61abc4b6f8-0050062022/original/Findex-2021-Methodology.pdf.

Topic: Assets


IndicatorName: ID ownership, male (% age 15+)

Longdefinition: The percentage of male respondents age 15 and above who report owning a primary foundational ID (national ID or similar credential). If the minimum age for obtaining an ID is above 15, observations below the minimum age are excluded.


Dataset: Global Findex

Generalcomments: 2021 variables

IndicatorName: Has access to the Internet (% age 15+)

Longdefinition: The percentage of respondents who report having access to the Internet.

Referenceperiod: 2021 variable

Source: Global Findex database

Unitofmeasure: Percent


Developmentrelevance:
The digital and information revolution has changed the way the world learns, communicates, does business, and treats illnesses. New information and communications technologies (ICT) offer vast opportunities for progress in all walks of life in all countries - opportunities for economic growth, improved health, better service delivery, learning through distance education, and social and cultural advances.

Today's smartphones and tablets have computer power equivalent to that of yesterday's computers and provide a similar range of functions. Device convergence is thus rendering the conventional definition obsolete.

Comparable statistics on access, use, quality, and affordability of ICT are needed to formulate growth-enabling policies for the sector and to monitor and evaluate the sector's impact on development. Although basic access data are available for many countries, in most developing countries little is known about who uses ICT; what they are used for (school, work, business, research, government); and how they affect people and businesses. The global Partnership on Measuring ICT for Development is helping to set standards, harmonize information and communications technology statistics, and build statistical capacity in developing countries. However, despite significant improvements in the developing world, the gap between the ICT haves and have-nots remains.

Generalcomments: Please cite the International Telecommunication Union for third-party use of these data.

IndicatorName: Individuals using the Internet, female (% of female population)

Limitationsandexceptions:
Operators have traditionally been the main source of telecommunications data, so information on subscriptions has been widely available for most countries. This gives a general idea of access, but a more precise measure is the penetration rate - the share of households with access to telecommunications. During the past few years more information on information and communication technology use has become available from household and business surveys. Also important are data on actual use of telecommunications services. Ideally, statistics on telecommunications (and other information and communications technologies) should be compiled for all three measures: subscriptions, access, and use. The quality of data varies among reporting countries as a result of differences in regulations covering data provision and availability.

Discrepancies may also arise in cases where the end of a fiscal year differs from that used by ITU, which is the end of December of every year. A number of countries have fiscal years that end in March or June of every year.

Longdefinition: This indicator refers to female individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.

Source: International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database

Statisticalconceptandmethodology: The Internet is a world-wide public computer network. It provides access to a number of communication services including the World Wide Web and carries email, news, entertainment and data files, irrespective of the device used (not assumed to be only via a computer - it may also be by mobile phone, PDA, games machine, digital TV etc.). Access can be via a fixed or mobile network. For additional/latest information on sources and country notes, please also refer to: https://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx

Topic: Technology


IndicatorName: Individuals using the Internet, male (% of male population)

Longdefinition: This indicator refers to male individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.


IndicatorName: Individuals using the Internet (% of population)

Longdefinition: Internet users are individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.


IndicatorName: Made a digital merchant payment for the first time after COVID-19 started (% age 15+)

Longdefinition: The percentage of respondents who report that the first time they used a debit or credit card, or a mobile phone, to make a purchase in-store or to pay online for an internet purchase happened after COVID-19 started.


IndicatorName: Made a digital merchant payment for the first time after COVID-19 started (% who made a digital merchant payment, age 15+)

Longdefinition: Among respondents who report making a digital merchant payment, the percentage who report that their first time doing so happened after COVID-19 started--either in-store or by paying online for an internet purchase.


IndicatorName: Made a digital merchant payment (% age 15+)

Longdefinition: The percentage of respondents who report using a debit or credit card, or a mobile phone, to make a purchase in-store or to pay online for an internet purchase.


IndicatorName: Made a digital merchant payment, female (% age 15+)

Longdefinition: The percentage of respondents who report using a debit or credit card, or a mobile phone, to make a purchase in-store or to pay online for an internet purchase, female (% age 15+)


IndicatorName: Made a digital merchant payment, male (% age 15+)

Longdefinition: The percentage of respondents who report using a debit or credit card, or a mobile phone, to make a purchase in-store or to pay online for an internet purchase, male (% age 15+)


Generalcomments: Time series variables

IndicatorName: Mobile money account (% age 15+)

Longdefinition: The percentage of respondents who report personally using a mobile money service in the past year.


IndicatorName: Mobile money account, female (% age 15+)

Longdefinition: The percentage of respondents who report personally using a mobile money service in the past year, female (% age 15+)


IndicatorName: Mobile money account, male (% age 15+)

Longdefinition: The percentage of respondents who report personally using a mobile money service in the past year, male (% age 15+)


Aggregationmethod: Gap-filled total

IndicatorName: GDP (current US$)

Limitationsandexceptions:
Gross domestic product (GDP), though widely tracked, may not always be the most relevant summary of aggregated economic performance for all economies, especially when production occurs at the expense of consuming capital stock.

While GDP estimates based on the production approach are generally more reliable than estimates compiled from the income or expenditure side, different countries use different definitions, methods, and reporting standards. World Bank staff review the quality of national accounts data and sometimes make adjustments to improve consistency with international guidelines. Nevertheless, significant discrepancies remain between international standards and actual practice. Many statistical offices, especially those in developing countries, face severe limitations in the resources, time, training, and budgets required to produce reliable and comprehensive series of national accounts statistics.

Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money.

Longdefinition: GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars. Dollar figures for GDP are converted from domestic currencies using single year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.

Source: World Bank national accounts data, and OECD National Accounts data files.

Statisticalconceptandmethodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.

Topic: Economic and Social Context


Developmentrelevance: An economy's growth is measured by the change in the volume of its output or in the real incomes of its residents. The 2008 United Nations System of National Accounts (2008 SNA) offers three plausible indicators for calculating growth: the volume of gross domestic product (GDP), real gross domestic income, and real gross national income. The volume of GDP is the sum of value added, measured at constant prices, by households, government, and industries operating in the economy. GDP accounts for all domestic production, regardless of whether the income accrues to domestic or foreign institutions.

IndicatorName: GDP growth (annual %)

Limitationsandexceptions:
Each industry's contribution to growth in the economy's output is measured by growth in the industry's value added. In principle, value added in constant prices can be estimated by measuring the quantity of goods and services produced in a period, valuing them at an agreed set of base year prices, and subtracting the cost of intermediate inputs, also in constant prices. This double-deflation method requires detailed information on the structure of prices of inputs and outputs.

In many industries, however, value added is extrapolated from the base year using single volume indexes of outputs or, less commonly, inputs. Particularly in the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.

Moreover, technical progress can lead to improvements in production processes and in the quality of goods and services that, if not properly accounted for, can distort measures of value added and thus of growth. When inputs are used to estimate output, as for nonmarket services, unmeasured technical progress leads to underestimates of the volume of output. Similarly, unmeasured improvements in quality lead to underestimates of the value of output and value added. The result can be underestimates of growth and productivity improvement and overestimates of inflation.

Informal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.

Rebasing of national accounts can alter the measured growth rate of an economy and lead to breaks in series that affect the consistency of data over time. When countries rebase their national accounts, they update the weights assigned to various components to better reflect current patterns of production or uses of output. The new base year should represent normal operation of the economy - it should be a year without major shocks or distortions. Some developing countries have not rebased their national accounts for many years. Using an old base year can be misleading because implicit price and volume weights become progressively less relevant and useful.

To obtain comparable series of constant price data for computing aggregates, the World Bank rescales GDP and value added by industrial origin to a common reference year. Because rescaling changes the implicit weights used in forming regional and income group aggregates, aggregate growth rates are not comparable with those from earlier editions with different base years. Rescaling may result in a discrepancy between the rescaled GDP and the sum of the rescaled components. To avoid distortions in the growth rates, the discrepancy is left unallocated. As a result, the weighted average of the growth rates of the components generally does not equal the GDP growth rate.

Longdefinition: Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.

Statisticalconceptandmethodology:
Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices. When value added is measured at producer prices.

Growth rates of GDP and its components are calculated using the least squares method and constant price data in the local currency. Constant price in U.S. dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.


IndicatorName: GDP per capita (current US$)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.

Statisticalconceptandmethodology: For more information, see the metadata for current U.S. dollar GDP (NY.GDP.MKTP.CD) and total population (SP.POP.TOTL).


IndicatorName: GDP per capita (constant 2015 US$)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.

Statisticalconceptandmethodology: For more information, see the metadata for constant U.S. dollar GDP (NY.GDP.MKTP.KD) and total population (SP.POP.TOTL).


Developmentrelevance: Because development encompasses many factors - economic, environmental, cultural, educational, and institutional - no single measure gives a complete picture. However, the total earnings of the residents of an economy, measured by its gross national income (GNI), is a good measure of its capacity to provide for the well-being of its people.

IndicatorName: GNI, Atlas method (current US$)

Longdefinition: GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.

Statisticalconceptandmethodology:
In calculating GNI and GNI per capita in U.S. dollars for certain operational purposes, the World Bank uses the Atlas conversion factor. The purpose of the Atlas conversion factor is to reduce the impact of exchange rate fluctuations in the cross-country comparison of national incomes.

The Atlas conversion factor for any year is the average of a country's exchange rate (or alternative conversion factor) for that year and its exchange rates for the two preceding years, adjusted for the difference between the rate of inflation in the country and that in Japan, the United Kingdom, the United States, and the Euro area. A country's inflation rate is measured by the change in its GDP deflator.

The inflation rate for Japan, the United Kingdom, the United States, and the Euro area, representing international inflation, is measured by the change in the SDR deflator. (Special drawing rights, or SDRs, are the International Monetary Fund's unit of account.) The SDR deflator is calculated as a weighted average of these countries' GDP deflators in SDR terms, the weights being the amount of each country's currency in one SDR unit. Weights vary over time because both the composition of the SDR and the relative exchange rates for each currency change. The SDR deflator is calculated in SDR terms first and then converted to U.S. dollars using the SDR to dollar Atlas conversion factor. The Atlas conversion factor is then applied to a country's GNI. The resulting GNI in U.S. dollars is divided by the midyear population to derive GNI per capita.

The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. An alternative conversion factor is used in the Atlas formula when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.


IndicatorName: GNI per capita, Atlas method (current US$)

Longdefinition: GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.

Statisticalconceptandmethodology: The World Bank uses Atlas method GNI per capita in U.S. dollars to classify countries for analytical purposes and to determine borrowing eligibility. For more information, see the metadata for Atlas method GNI in current U.S. dollars (NY.GNP.ATLS.CD) and total population (SP.POP.TOTL).


IndicatorName: GNI per capita, PPP (current international $)

Longdefinition:
This indicator provides per capita values for gross national income (GNI. Formerly GNP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.
GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.

Source: International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme.

Statisticalconceptandmethodology:
Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

For more information on underlying GNI in current international dollar, please refer to the metadata for "GNI, PPP (current international $)" [NY.GNP.MKTP.PP.CD]. For more information on underlying population, please refer to the metadata for "total population" [SP.POP.TOTL].
For the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).


IndicatorName: Own a mobile phone (% age 15+)

Longdefinition: The percentage of respondents who report owning a mobile phone.


IndicatorName: Saved any money (% age 15+)

Longdefinition: The percentage of respondents who report personally saving or setting aside any money for any reason and using any mode of saving in the past year.


IndicatorName: Saved any money, female (% age 15+)

Longdefinition: The percentage of respondents who report personally saving or setting aside any money for any reason and using any mode of saving in the past year, female (% age 15+)


IndicatorName: Saved any money, male (% age 15+)

Longdefinition: The percentage of respondents who report personally saving or setting aside any money for any reason and using any mode of saving in the past year, male (% age 15+)


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

IndicatorName: Literacy rate, youth female (% of females ages 15-24)

Limitationsandexceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.

Longdefinition: Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Source: UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed September 30, 2024. https://apiportal.uis.unesco.org/bdds.

Statisticalconceptandmethodology:
Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.

Topic: Education


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around. Eliminating gender disparities in education would help increase the status and capabilities of women. Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

IndicatorName: Literacy rate, youth (ages 15-24), gender parity index (GPI)

Longdefinition: Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female youth literacy rate by male youth literacy rate.

Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.


IndicatorName: Literacy rate, youth male (% of males ages 15-24)


IndicatorName: Literacy rate, youth total (% of people ages 15-24)


IndicatorName: Literacy rate, adult female (% of females ages 15 and above)

Longdefinition: Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.


IndicatorName: Literacy rate, adult male (% of males ages 15 and above)


IndicatorName: Literacy rate, adult total (% of people ages 15 and above)


Developmentrelevance: The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around. Eliminating gender disparities in education would help increase the status and capabilities of women.

IndicatorName: School enrollment, primary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in primary education is the ratio of girls to boys enrolled at primary level in public and private schools.

Source: UNESCO Institute for Statistics (UIS). UIS.Stat Bulk Data Download Service. Accessed October 24, 2022. https://apiportal.uis.unesco.org/bdds.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in primary education by male gross enrollment ratio in primary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary and secondary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in primary and secondary education is the ratio of girls to boys enrolled at primary and secondary levels in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in primary and secondary education by male gross enrollment ratio in primary and secondary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, secondary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in secondary education by male gross enrollment ratio in secondary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, tertiary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in tertiary education is the ratio of women to men enrolled at tertiary level in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in tertiary education by male gross enrollment ratio in tertiary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


Developmentrelevance:
Ensuring that all students read with comprehension is essential to achieving the ambitious SDG targets and to building human capital. Children need to learn to read so that they can read to learn. Those who do not become proficient in reading by the end of primary school often cannot catch up later, because the curriculum of every school system assumes that secondary-school students can learn through reading. Reading is a gateway to all types of academic learning.  In high-income countries, 90% of all children learn to read with comprehension before the end of primary school, and for the highest-performing countries, the figure reaches 97% or more. Yet past evidence from many low- and middle-income countries has shown that many children are not learning to read with comprehension in primary school.
The LP indicator illustrates progress toward SDG 4’s broader goal of ensuring inclusive and equitable quality education for all. It particularly highlights progress towards SDG 4.1.1(b) and SDG 4.1.4, which specifies that all children attend primary school and reach at least a minimum proficiency level in reading at the end of primary. The indicator is also aligned with the World Bank’s Human Capital Project, which aims to ensure that children reach their full potential in school and in life. The ability to read with comprehension is a foundational skill that every education system around the world strives to impart by late in primary school—generally by age 10. Moreover, attaining the ambitious Sustainable Development Goals (SDGs) in education requires first to achieving this basic building block, and so does improving countries’ Human Capital Index scores.

IndicatorName: Learning poverty: Share of Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)

Limitationsandexceptions:
The construct of “all children reading by age 10” is an ideal that embodies normative statements about both learning and access. To achieve it, not only should all children be reading proficiently after 3 full years in primary education, but they should also have entered school at age 6 or 7.
By contrast, the actual indicators used to measure learning poverty are based on grade rather than age. Since the assessments are of 4th- through 6th-graders, the children tested will have had at least 3 to 5 years in school to reach what, according to the ideal, should 10 be an age-10 minimum proficiency, or even the entire primary-school-age segment for the out-of-school indicator.
Due to different assessment availability within and between countries, data comparability, both within countries over time and across countries still poses a significant challenge. The additional out of school component further limits comparability.
The learning poverty indicator is based on data covering four-fifths of children at the end of primary school. In other words, a little more than 80 percent of children in low- and middle-income countries live in a country with at least one learning assessment at the end of primary, carried out in the past 9 years. For regional and global aggregates, weighted imputations affect regions with less data coverage. The major gaps are concentrated in countries where the learning crisis is most acute. Less than half of children in Sub-Saharan Africa live in a country with a National Large-Scale Learning Assessment (NLSA) or a international of regional large-scale learning assessment (ILSA or RLSA) of adequate quality to be used for this purpose.
This extensive coverage became possible only in recent years, with the progress in measuring learning in countries and the GAML’s efforts to establish comparability, which has made possible the construction of a global indicator based on harmonized proficiency levels. Future efforts by coalition organizations are also ensuring more flexible assessment options are available for expanding data availability for countries, such as the Assessment of Minimum Proficiency Levels (AMPL) and policy linking exercises led by UIS.

Longdefinition: The share of 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the “minimum proficiency” threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This “union approach” to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]

Shortdefinition: The share of 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the minimum proficiency level (MPL) for reading.

Source: World Bank and UIS

Statisticalconceptandmethodology:
The learning poverty indicator brings together schooling and learning indicators. It starts with the share of children in school who haven’t achieved minimum reading proficiency (Learning Deprived) and adjusts it by the proportion of children who are out of school (Schooling Deprived).
Formally, Learning Poverty is calculated as: [LD* (1-SD)] + [1 * SD]
where LP = Learning poverty; LD = Learning deprivation or the share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring; SD = Schooling deprivation or the share of primary-school-age children who are out-of-school (OOS) and in which all OOS are regarded as being below the minimum proficiency level.
Because out-of-school children are treated as non-proficient in reading, learning poverty will always be higher than the share of children in school who haven't achieved minimum reading proficiency. For countries with a very low schooling deprivation, the learning deprivation value will be very close to Learning Poverty.
Estimating the current level of global and regional learning poverty requires deciding how to define “current.” We include results of assessments within four years before or after a set anchor year. This decision is driven by data availability. International and regional large-scale learning assessments used for SDG 4.1.1b reporting are carried out only every 3 to 4 years. And even where assessments have been carried out recently, there is a lag of a couple of years before the data are available. This band is intended as a moving window. In the original 2019 release, the anchor year used was 2015 (Assessments between 2011 and 2019 are included in the learning poverty estimate). In the 2022 Global Update, the anchor year was moved to 2019 (assessments between 2015 and 2023 are included).
Aggregations for each region comprise the average learning poverty of countries with available data, weighted by their population ages 10–14 years old. To obtain a global estimate, we weight the regional aggregations by the 10–14-year-old population regardless of data availability. This is equivalent to imputing missing country data using regional values.

Unitofmeasure: % of Total


IndicatorName: Pupils below minimum reading proficiency at end of primary (%). Low GAML threshold

Longdefinition: This indicator uses on Minimum Proficiency Levels (MPLs) defined by the Global Alliance to Monitor Learning led by the UNESCO Institute for Statistics (UIS) in the context of the SDG 4.1.1 monitoring, which established learning benchmarks across different cross-national and national assessments.

Source: Word Bank and UIS


IndicatorName: Female pupils below minimum reading proficiency at end of primary (%). Low GAML threshold

Notesfromoriginalsource: For more information please see Azevedo, Joao Pedro, and others. 2019. "Will Every Child Be Able to Read by 2030? Why Eliminating Learning Poverty Will Be Harder Than You Think, and What to Do About It." World Bank Policy Research Working Paper series. Washington, DC: World Bank. https://datacatalog.worldbank.org/dataset/learning-poverty

Source: Word Bank and UNESCO Institute for Statistics


IndicatorName: Male pupils below minimum reading proficiency at end of primary (%). Low GAML threshold


IndicatorName: Learning poverty: Share of Female Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)

Longdefinition: The share of female 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the “minimum proficiency” threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This “union approach” to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]

Shortdefinition: The share of female 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the minimum proficiency level (MPL) for reading.


IndicatorName: Learning poverty: Share of Male Children at the End-of-Primary age below minimum reading proficiency adjusted by Out-of-School Children (%)

Longdefinition: The share of male 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the “minimum proficiency” threshold for reading. This measure is defined as the union of two deprivations: 1) schooling deprivation and 2) learning deprivation. A child is considered schooling-deprived (SD) if he or she is of primary school age and out-of-school. The dimension of learning deprivation (LD) applies only for children in school, and identifies those pupils who are below the minimum proficiency level (MPL) for reading, as defined by the Global Alliance to Monitor Learning (GAML), measured in standard learning assessments, and reported in the context of the SDG 4.1.1b monitoring. This “union approach” to measurement reflects the choice that, as presented in the SDGs, all age 10 children must be both in school and learning. The final learning poverty measure combines the two dimensions in a single indicator using the following formula: LP = SD + [(1-SD) x LD]

Shortdefinition: The share of male 10-year-olds who cannot read and understand a short passage of age-appropriate material—in other words, those who are below the minimum proficiency level (MPL) for reading.


IndicatorName: Female primary school age children out-of-school (%)

Longdefinition: The Out-of-School adjustment in our Learning Poverty indicator relies on enrollment data. Our preferred definition is the adjusted net primary enrollment as reported by UIS.


IndicatorName: Male primary school age children out-of-school (%)


Developmentrelevance: Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system. The net enrollment rate excludes overage and underage students and more accurately captures the system's coverage and internal efficiency. Differences between the gross enrollment ratio and the net enrollment rate show the incidence of overage and underage enrollments.

IndicatorName: School enrollment, preprimary (% gross)

Limitationsandexceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.

Statisticalconceptandmethodology:
Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, preprimary, female (% gross)


IndicatorName: School enrollment, preprimary, male (% gross)


IndicatorName: Primary completion rate, female, based on completers

Longdefinition: Primary completion rate is the percentage of students completing the last year of primary school. The rate based on completers is calculated by taking the total number of completers in the last grade of primary school divided by the total number of children of official graduation age.


IndicatorName: Primary completion rate, male, based on completers


IndicatorName: Primary completion rate, total, based on completers


Developmentrelevance: The World Bank and the UNESCO Institute for Statistics jointly developed the primary completion rate indicator. Increasingly used as a core indicator of an education system's performance, it reflects an education system's coverage and the educational attainment of students.

IndicatorName: Primary completion rate, female (% of relevant age group)

Limitationsandexceptions:
Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.

There are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.

Longdefinition: Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.

Statisticalconceptandmethodology:
Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Primary completion rate, male (% of relevant age group)


IndicatorName: Primary completion rate, total (% of relevant age group)


Developmentrelevance: A relative high concentration of the adult population in a given level of education reflects the capacity of the educational system in the corresponding level of education. Educational attainment is closely related to the skills and competencies of a country's population, and could be seen as a proxy of both the quantitative and qualitative aspects of the stock of human capital.

IndicatorName: Educational attainment, at least completed primary, population 25+ years, female (%) (cumulative)

Limitationsandexceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).

Longdefinition: The percentage of population ages 25 and over that attained or completed primary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least completed primary, population 25+ years, male (%) (cumulative)


IndicatorName: Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative)


Developmentrelevance: The share of girls allows an assessment on gender composition in school enrollment. A value greater than 50% indicates participation of more girls at a specific level or programme of education.

IndicatorName: Primary education, pupils (% female)

Limitationsandexceptions: The percentage of female enrollment is limited in assessing gender parity, because it's affected by the gender composition of population. Ratio of female to male in enrollment rate provides a population adjusted measure of gender parity.

Longdefinition: Female pupils as a percentage of total pupils at primary level include enrollments in public and private schools.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.

Statisticalconceptandmethodology:
Percentage of female enrollment is calculated by dividing the total number of female students at a given level of education by the total enrollment at the same level, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary (% gross)

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.

Statisticalconceptandmethodology:
Gross enrollment ratio for primary school is calculated by dividing the number of students enrolled in primary education regardless of age by the population of the age group which officially corresponds to primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary, female (% gross)


IndicatorName: School enrollment, primary, male (% gross)


Developmentrelevance: The gross intake ratio in the first grade of primary education indicates the level of access to primary education and the education system's capacity to provide access to primary education. A low gross intake ratio in the first grade of primary education reflects the fact that many children do not enter primary education even though school attendance, at least through the primary level, is mandatory in most countries. Because the gross intake ratio includes all new entrants regardless of age, it can exceed 100 percent in some situations, such as immediately after fees have been abolished or when the number of reenrolled children is large.

IndicatorName: Gross intake ratio in first grade of primary education, total (% of relevant age group)

Limitationsandexceptions: The quality of data is affected when new entrants and repeaters are not correctly distinguished in the first grade of primary education. Caution is also needed for countries with a total population under 100,000 since the United Nations Population Division neither publish nor endorse single-age data for those countries. The data are highly subject to fluctuations in migration and other factors.

Longdefinition: Gross intake ratio in first grade of primary education is the number of new entrants in the first grade of primary education regardless of age, expressed as a percentage of the population of the official primary entrance age.

Statisticalconceptandmethodology:
Gross intake ratio in the first grade of primary education is calculated by dividing the number of new entrants (enrollments minus repeaters) in the first grade of primary education, regardless of age, by the population of the official primary entrance age and multiplying the result by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary (% net)

Longdefinition: Net enrollment rate is the ratio of children of official school age who are enrolled in school to the population of the corresponding official school age. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music.

Statisticalconceptandmethodology:
Net enrollment rate for primary school is calculated by dividing the number of students of official school age enrolled in primary education by the population of the age group which officially corresponds to primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, primary, female (% net)


IndicatorName: School enrollment, primary, male (% net)


Developmentrelevance: The net intake rate in the first grade of primary education indicates the level of access to primary education and the education system's capacity to provide access to primary education. A high net intake rate indicates a high degree of access to primary education for the official primary school entrance age children.

IndicatorName: Net intake rate in grade 1, female (% of official school-age population)

Longdefinition: Net intake rate in grade 1 is the number of new entrants in the first grade of primary education who are of official primary school entrance age, expressed as a percentage of the population of the corresponding age.

Statisticalconceptandmethodology:
Net intake rate in the first grade of primary education is calculated by dividing the number of children of official primary school entrance age who enter grade 1 of primary education for the first time by the population of the same age, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Net intake rate in grade 1, male (% of official school-age population)


IndicatorName: Net intake rate in grade 1 (% of official school-age population)


Developmentrelevance: The cohort survival rate measures an education system's holding power and internal efficiency. Rates approaching 100 percent indicate high retention and low dropout levels.

IndicatorName: Persistence to grade 5, female (% of cohort)

Limitationsandexceptions: The estimates have limitations in capturing real trend in that an observed rate will be applied to the underlying indicators such as repetition rate and promotion rate throughout the cohort life, and re-entrants, grade skipping, migration or transfers during a school year are not adequately captured.

Longdefinition: Persistence to grade 5 (percentage of cohort reaching grade 5) is the share of children enrolled in the first grade of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method.

Statisticalconceptandmethodology:
Cohort survival rate is calculated by dividing the total number of children belonging to a cohort who reached each successive grade of the specified level of education by the number of children in the same cohort; those originally enrolled in the first grade of primary education, and multiplying by 100. To reflect current patterns of grade transition, it is calculated based on the reconstructed cohort method, which uses data on enrollment by grade for the two most recent years and data on repeaters by grade for the most recent of those two years. Aggregate data are based on World Bank estimates.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Persistence to grade 5, male (% of cohort)


Developmentrelevance: The share of female teachers shows the level of gender representation in the teaching force. A value of greater than 50% indicates more opportunities or preference for women to participate in teaching activities. Women teachers are important as they serve as role models to girls and help to attract and retain girls in school.

IndicatorName: Primary education, teachers (% female)

Longdefinition: Female teachers as a percentage of total primary education teachers includes full-time and part-time teachers.

Statisticalconceptandmethodology:
The share of female teachers in primary education is calculated by dividing the total number of female teachers at primary level of education by the total number of teachers at the same level, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


Developmentrelevance: Relevance to gender indicator: Women teachers are important as they serve as role models to girls and help to attract and retain girls in school.

IndicatorName: Adjusted net enrollment rate, primary (% of primary school age children)

Longdefinition: Adjusted net enrollment is the number of pupils of the school-age group for primary education, enrolled either in primary or secondary education, expressed as a percentage of the total population in that age group.

Statisticalconceptandmethodology:
Adjusted net enrollment rate in primary education is calculated by dividing the number of children in the official primary school age who are enrolled in primary or secondary education by the population of the same age group and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Adjusted net enrollment rate, primary, female (% of primary school age children)


Developmentrelevance: Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system. The net enrollment rate excludes overage and underage students and more accurately captures the system's coverage and internal efficiency. Differences between the gross enrollment ratio and the net enrollment rate show the incidence of overage and underage enrollments. The adjusted net enrollment rate in primary education captures primary school-age children who have progressed to secondary education faster than their peers have and who are not counted in the traditional net enrollment rate.

IndicatorName: Adjusted net enrollment rate, primary, male (% of primary school age children)