169 KiB
169 KiB
| 1 | Code | License Type | Indicator Name | Short definition | Long definition | Source | Topic | Unit of measure | Periodicity | Aggregation method | Statistical concept and methodology | Development relevance | Limitations and exceptions | General comments | Notes from original source | License URL | Previous Indicator Name |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2 | SG.GET.JOBS.EQ | CC BY-4.0 | A woman can get a job in the same way as a man (1=yes; 0=no) | The indicator measures whether there are restrictions on a woman's legal capacity and ability to work. | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Employment and Time Use | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 3 | SG.BUS.REGT.EQ | CC BY-4.0 | A woman can register a business in the same way as a man (1=yes; 0=no) | The indicator measures whether there are restrictions on a woman registering a business (i.e. if a woman needs her husband’s or guardian’s permission, signature or consent to register a business; or the registration process at any stage requires a woman to provide additional information or documentation that is not required of a man). | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Entrepreneurship | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 4 | SG.CNT.SIGN.EQ | CC BY-4.0 | A woman can sign a contract in the same way as a man (1=yes; 0=no) | The indicator measures whether a woman obtains full legal capacity upon reaching the age of majority and there are no restrictions on her signing legally binding contracts. | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Entrepreneurship | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 5 | SG.NGT.WORK.EQ | CC BY-4.0 | A woman can work at night in the same way as a man (1=yes; 0=no) | The indicator measures whether nonpregnant and nonnursing women are prohibited from working at night or cannot work the same night hours as men. If various sectors of the economy are regulated separately (i.e., no central labor law), it is assumed that the woman is employed as a cashier in a grocery store or supermarket. It is analyzed whether restrictions on women's ability to work at night do not apply to the food retail sector; if women's consent to work at night is required; if an employer needs to comply with safety measures (such as providing transportation). | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Employment and Time Use | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. The indicator name has been changed as of February 2021. Previous indicator name: Women can work the same night hours as men (1=yes; 0=no) | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 6 | SG.DNG.WORK.DN.EQ | CC BY-4.0 | A woman can work in a job deemed dangerous in the same way as a man (1=yes; 0=no) | The indicator measures whether there are laws that prohibit or restrict nonpregnant and non-nursing women from working in a broad and subjective category of jobs deemed “hazardous,” “arduous” or “morally inappropriate.” | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Employment and Time Use | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. The indicator name has been changed as of February 2021. Previous indicator name: Women can work in jobs deemed dangerous in the same way as men (1=yes; 0=no) | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 7 | SG.IND.WORK.EQ | CC BY-4.0 | A woman can work in an industrial job in the same way as a man (1=yes; 0=no) | The indicator measures whether nonpregnant and non-nursing a woman can work in the mining, construction, manufacturing, energy, water, agriculture, and transportation industries in the same way as men. nonpregnant and non-nursing women can work in the mining, construction, manufacturing, energy, water, agriculture, and transportation industries in the same way as men. | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Employment and Time Use | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. The indicator name has been changed as of February 2021. Previous indicator name: Women are able to work in the same industries as men (1=yes; 0=no) | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | Women are able to work in the same industries as men (1=yes; 0=no) | |||
| 8 | FX.OWN.TOTL.FE.ZS | CC BY-4.0 | Account ownership at a financial institution or with a mobile-money-service provider, female (% of population ages 15+) | Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (female, % age 15+). | Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank. | Assets | Annual | Weighted average | Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018). | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||||
| 9 | FX.OWN.TOTL.MA.ZS | CC BY-4.0 | Account ownership at a financial institution or with a mobile-money-service provider, male (% of population ages 15+) | Account denotes the percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution or report personally using a mobile money service in the past 12 months (male, % age 15+). | Demirguc-Kunt et al., 2018, Global Financial Inclusion Database, World Bank. | Assets | Annual | Weighted average | Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018). | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||||
| 10 | IC.REG.COST.PC.ZS | CC BY-4.0 | Cost of business start-up procedures (% of GNI per capita) | Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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. | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 11 | IC.REG.COST.PC.FE.ZS | CC BY-4.0 | Cost of business start-up procedures, female (% of GNI per capita) | Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita. | 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 | Entrepreneurship | Annual | Unweighted average | 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 procedures, time, cost and paid-in minimum capital requirement 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 12 | IC.REG.COST.PC.MA.ZS | CC BY-4.0 | Cost of business start-up procedures, male (% of GNI per capita) | Cost to register a business is normalized by presenting it as a percentage of gross national income (GNI) per capita. | 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 | Entrepreneurship | Annual | Unweighted average | 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 paid-in minimum capital requirement 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 13 | fin7.t.a.2 | Credit card ownership, female (% age 15+) | The percentage of respondents who report having a credit card, female (% age 15+) | The percentage of respondents who report having a credit card, female (% age 15+) | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 14 | fin7.t.a.1 | Credit card ownership, male (% age 15+) | The percentage of respondents who report having a credit card, male (% age 15+). | The percentage of respondents who report having a credit card, male (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 15 | fin7.t.a | Credit card ownership (% age 15+) | The percentage of respondents who report having a credit card | The percentage of respondents who report having a credit card | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 16 | fin2.t.a | Debit card ownership (% age 15+) | The percentage of respondents who report having a debit card. | The percentage of respondents who report having a debit card. | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 17 | fin2.t.a.2 | Debit card ownership, female (% age 15+) | The percentage of respondents who report having a debit card, female (% age 15+). | The percentage of respondents who report having a debit card, female (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 18 | fin2.t.a.1 | Debit card ownership, male (% age 15+) | The percentage of respondents who report having a debit card, male (% age 15+). | The percentage of respondents who report having a debit card, male (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 19 | SL.SRV.EMPL.FE.ZS | CC BY-4.0 | Employment in services, female (% of female employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 20 | SL.SRV.EMPL.MA.ZS | CC BY-4.0 | Employment in services, male (% of male employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 21 | SL.IND.EMPL.MA.ZS | CC BY-4.0 | Employment in industry, male (% of male employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 22 | SL.IND.EMPL.FE.ZS | CC BY-4.0 | Employment in industry, female (% of female employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 23 | SL.IND.EMPL.ZS | CC BY-4.0 | Employment in industry (% of total employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 24 | SL.AGR.EMPL.MA.ZS | CC BY-4.0 | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4). | International Labour Organization, ILOSTAT database. Data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity. The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas. The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment. Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries. | There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source. Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries. The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectorsdata. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 25 | fin1.t.a | Financial institution account (% age 15+) | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution. | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution. | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 26 | fin1.t.a.2 | Financial institution account,female(% age 15+) | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution,female (% age 15+). | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution,female (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 27 | fin1.t.a.1 | Financial institution account,male(% age 15+) | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution, male (% age 15+). | The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution, male (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 28 | SG.OWN.PRRT.IM | CC BY-4.0 | Men and women have equal ownership rights to immovable property (1=yes; 0=no) | The indicator measures whether no legal restriction related to property is applied to women or men based on gender (i.e. if legal restrictions on property ownership are applied based on gender, or if there are gender differences in the legal treatment of spousal property, such as granting the husband administrative control of marital property. This includes instances in which legal systems are supported by custom and judicial precedent). | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Assets | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 29 | IC.WEF.LLCO.FE | Number of female business owners | 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. | World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship). | Entrepreneurship | 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. | 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. | 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. | For cross-country comparability, only limited liability corporations that operate in the formal sector are included. | ||||||||
| 30 | IC.WEF.LLCO.MA | Number of male business owners | 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. | World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship). | Entrepreneurship | 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. | 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. | 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. | For cross-country comparability, only limited liability corporations that operate in the formal sector are included. | ||||||||
| 31 | SG.TIM.UWRK.MA | CC BY-4.0 | Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day) | The average time men spend on household provision of services for own consumption. Data are expressed as a proportion of time in a day. Domestic and care work includes food preparation, dishwashing, cleaning and upkeep of a dwelling, laundry, ironing, gardening, caring for pets, shopping, installation, servicing and repair of personal and household goods, childcare, and care of the sick, elderly or disabled household members, among others. | National statistical offices or national database and publications compiled by United Nations Statistics Division | Employment and Time Use | Annual | Proportion of time spent on unpaid domestic and care work is calculated by dividing the daily average number of hours spent on unpaid domestic and care work by 24 hours. Data presented for this indicator are expressed as a proportion of time in a day. Weekly data is averaged over seven days of the week to obtain the daily average time. | Women often spend disproportionately more time on unpaid domestic and care work than men. This unequal division of responsibilities is correlated with gender differences in economic opportunities, includign low female labor force participation, occupational sex segregation, and earnings diffrentials. The need for a gender balance in the distribution of unpaid domestic and care work has been increasingly recognized and the Sustainable Development Goals address the issue in the target 5.4. | Data may not be strictly comparable across countries as the methods and sampling involved for data collection may differ. | This is the Sustainable Development Goal indicator 5.4.1[https://unstats.un.org/sdgs/metadata/]. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 32 | fin18.t.d.1 | Saved any money in the past year, male (% age 15+) | 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 12 months., male (% age 15+). | 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 12 months., male (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 33 | fin18.t.d.2 | Saved any money in the past year, female (% age 15+) | 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 12 months., female (% age 15+). | 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 12 months., female (% age 15+). | Global Findex database | Assets | Percent | Triennial | Weighted Average | ||||||||
| 34 | IC.WEF.LLCO.FE.ZS | Share of female business owners (% of total business owners) | 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. | World Bank's Entrepreneurship Survey and database (http://www.doingbusiness.org/data/exploretopics/entrepreneurship). | Entrepreneurship | 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. | 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. | 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. | For cross-country comparability, only limited liability corporations that operate in the formal sector are included. | ||||||||
| 35 | IC.REG.PROC | CC BY-4.0 | Start-up procedures to register a business (number) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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. | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 36 | IC.REG.PROC.FE | CC BY-4.0 | Start-up procedures to register a business, female (number) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 37 | IC.REG.PROC.MA | CC BY-4.0 | Start-up procedures to register a business, male (number) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 38 | SG.LAW.CRDD.GR | CC BY-4.0 | The law prohibits discrimination in access to credit based on gender (1=yes; 0=no) | The indicator measures whether the law prohibits discrimination by creditors based on gender or prescribes equal access for both men and women when conducting financial transactions, entrepreneurial activities or receiving financial assistance, or if the law prohibits gender discrimination when accessing goods and services (and services are defined to include financial services). | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Assets | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 39 | SG.LAW.NODC.HR | CC BY-4.0 | The law prohibits discrimination in employment based on gender (1=yes; 0=no) | The indicator measures whether the law generally prevents or penalizes gender-based discrimination in employment. Laws that mandate equal treatment or equality between women and men in employment are also counted for this question. It is not considered whether the laws only prohibit discrimination in one aspect of employment, such as pay or dismissal. | World Bank: Women, Business and the Law. https://wbl.worldbank.org/ | Employment and Time Use | Annual | Women, Business and the Law tracks progress toward legal equality between men and women in 190 economies. Data are collected with standardized questionnaires to ensure comparability across economies. Questionnaires are administered to over 2,000 respondents with expertise in family, labor, and criminal law, including lawyers, judges, academics, and members of civil society organizations working on gender issues. Respondents provide responses to the questionnaires and references to relevant laws and regulations. The Women, Business and the Law team collects the texts of these codified sources of national law - constitutions, codes, laws, statutes, rules, regulations, and procedures - and checks questionnaire responses for accuracy. Thirty-five data points are scored across eight indicators of four or five binary questions, with each indicator representing a different phase of a woman’s career. Indicator-level scores are obtained by calculating the unweighted average of the questions within that indicator and scaling the result to 100. Overall scores are then calculated by taking the average of each indicator, with 100 representing the highest possible score. | The knowledge and analysis provided by Women, Business and the Law make a strong economic case for laws that empower women. Better performance in the areas measured by the Women, Business and the Law index is associated with more women in the labor force and with higher income and improved development outcomes. Equality before the law and of economic opportunity are not only wise social policy but also good economic policy. The equal participation of women and men will give every economy a chance to achieve its potential. Given the economic significance of women's empowerment, the ultimate goal of Women, Business and the Law is to encourage governments to reform laws that hold women back from working and doing business. | The Women, Business and the Law methodology has limitations that should be considered when interpreting the data. All eight indicators are based on standardized assumptions to ensure comparability across economies. Comparability is one of the strengths of the data, but the assumptions can also be limitations as they may not capture all restrictions or represent all particularities in a country. It is assumed that the woman resides in the economy's main business city of the economy. In federal economies, laws affecting women can vary by state or province. Even in nonfederal economies, women in rural areas and small towns could face more restrictive local legislation. Such restrictions are not captured by Women, Business and the Law unless they are also found in the main business city. The woman has reached the legal age of majority and is capable of making decisions as an adult, is in good health and has no criminal record. She is a lawful citizen of the economy being examined, and she works as a cashier in the food retail sector in a supermarket or grocery store that has 60 employees. She is a cisgender, heterosexual woman in a monogamous first marriage registered with the appropriate authorities (de facto marriages and customary unions are not measured), she is of the same religion as her husband, and is in a marriage under the rules of the default marital property regime, or the most common regime for that jurisdiction, which will not change during the course of the marriage. She is not a member of a union, unless membership is mandatory. Membership is considered mandatory when collective bargaining agreements cover more than 50 percent of the workforce in the food retail sector and when they apply to individuals who were not party to the original collective bargaining agreement. Where personal law prescribes different rights and obligations for different groups of women, the data focus on the most populous group, which may mean that restrictions that apply only to minority populations are missed. Women, Business and the Law focuses solely on the ways in which the formal legal and regulatory environment determines whether women can work or open their own businesses. The data set is constructed using laws and regulations that are codified (de jure) and currently in force, therefore implementation of laws (de facto) is not measured. The data looks only at laws that apply to the private sector. These assumptions can limit the representativeness of the data for the entire population in each country. Finally, Women, Business and the Law recognizes that the laws it measures do not apply to all women in the same way. Women face intersectional forms of discrimination based on gender, sex, sexuality, race, gender identity, religion, family status, ethnicity, nationality, disability, and a myriad of other grounds. Women, Business and the Law therefore encourages readers to interpret the data in conjunction with other available research. | For the reference period, WDI and Gender Databases take the data coverage years instead of reporting years used in WBL (https://wbl.worldbank.org/). For example, the data for YR2020 in WBL (report year) corresponds to data for YR2019 in WDI and Gender Databases. | This is one of the 35 scored indicators. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 40 | IC.REG.DURS | CC BY-4.0 | Time required to start a business (days) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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. | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 41 | IC.REG.DURS.FE | CC BY-4.0 | Time required to start a business, female (days) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 42 | IC.REG.DURS.MA | CC BY-4.0 | Time required to start a business, male (days) | 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. | 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 | Entrepreneurship | Annual | Unweighted average | 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. | 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. | 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 | Data are presented for the survey year instead of publication year. | https://datacatalog.worldbank.org/public-licenses#cc-by | ||||
| 43 | SL.EMP.VULN.MA.ZS | CC BY-4.0 | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment. | Derived using data from International Labour Organization, ILOSTAT database. The data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The indicator of status in employment distinguishes between two categories of the total employed. These are: (a) wage and salaried workers (also known as employees); and (b) self-employed workers. Self-employed group is broken down in the subcategories: self-employed workers with employees (employers), self-employed workers without employees (own-account workers), members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of contributing family workers and own-account workers. Data are derived using ILO modeled estimate series which are harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Breaking down employment information by status in employment provides a statistical basis for describing workers' behaviour and conditions of work, and for defining an individual's socio-economic group. A high proportion of wage and salaried workers in a country can signify advanced economic development. If the proportion of own-account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. A high proportion of contributing family workers — generally unpaid, although compensation might come indirectly in the form of family income — may indicate weak development, little job growth, and often a large rural economy. Each status group faces different economic risks, and contributing family workers and own-account workers are the most vulnerable - and therefore the most likely to fall into poverty. They are the least likely to have formal work arrangements, are the least likely to have social protection and safety nets to guard against economic shocks, and often are incapable of generating sufficient savings to offset these shocks. | Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic. | https://datacatalog.worldbank.org/public-licenses#cc-by | |||||
| 44 | SL.EMP.VULN.FE.ZS | CC BY-4.0 | Vulnerable employment, female (% of female employment) (modeled ILO estimate) | Vulnerable employment is contributing family workers and own-account workers as a percentage of total employment. | Derived using data from International Labour Organization, ILOSTAT database. The data retrieved on January 29, 2021. | Employment and Time Use | Annual | Weighted average | The indicator of status in employment distinguishes between two categories of the total employed. These are: (a) wage and salaried workers (also known as employees); and (b) self-employed workers. Self-employed group is broken down in the subcategories: self-employed workers with employees (employers), self-employed workers without employees (own-account workers), members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of contributing family workers and own-account workers. Data are derived using ILO modeled estimate series which are harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available. | Breaking down employment information by status in employment provides a statistical basis for describing workers' behaviour and conditions of work, and for defining an individual's socio-economic group. A high proportion of wage and salaried workers in a country can signify advanced economic development. If the proportion of own-account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. A high proportion of contributing family workers — generally unpaid, although compensation might come indirectly in the form of family income — may indicate weak development, little job growth, and often a large rural economy. Each status group faces different economic risks, and contributing family workers and own-account workers are the most vulnerable - and therefore the most likely to fall into poverty. They are the least likely to have formal work arrangements, are the least likely to have social protection and safety nets to guard against economic shocks, and often are incapable of generating sufficient savings to offset these shocks. | Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic. | https://datacatalog.worldbank.org/public-licenses#cc-by |