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MSME Finance Gap

Description: 

Micro, Small and Medium Enterprises (MSMEs) are one of the strongest drivers of economic development, innovation and employment.
Access to finance is frequently identified as a critical barrier to growth for MSMEs.Creating opportunities for MSMEs in emerging markets is a key way to advance economic development and reduce poverty.
The private and public sector can better address this matter if they have better insights about the magnitude and nature of the finance gap. Hence, sizing MSME finance gap is crucial for the governors, financiers and other private sector players to...

Type: 
Other

Historical IFC Financial Clients’ Reach Data

Description: 

Lack of access to financial services is a key barrier to the growth of micro, small, medium enterprises (MSMEs). IFC is working to develop solutions to close the MSME financing gap. By partnering with many types of financial intermediaries, including microfinance institutions (MFIs), commercial banks, leasing companies, and private equity funds, IFC reaches many more small and medium enterprises (SMEs) than it could directly.

Type: 
Other

World Bank (IBRD) Bonds (1947-1980, select issues from 1980-2019)

Description: 

The International Bank for Reconstruction and Development (IBRD) is a triple-A rated multilateral development institution and the first to enter the capital markets in July 1947. All World Bank (IBRD) bonds support World Bank operations and sustainable development. The World Bank Treasury manages the IBRD funding program. These data include all bonds issued from 1947-1980 and select transactions from 1980-2019). Transactions and will be routinely updated.

Type: 
Other

Food Safety in Africa: Past Endeavors and Future Directions

Description: 

The Global Food Safety Partnership's (GFSP) Food Safety in Africa provides access to descriptive information on 518 food safety investments in sub-Saharan Africa between 2010 and early 2017. It may be used to identify and cross-reference these projects, perform country-, sector-, or donor-specific analysis, and plan future interventions. The dataset includes basic information, such as the project title, donor, name and type of implementing organization, countries where work was implemented, years underway, and budgets (overall and food-safety specific). It also classifies the primary...

Type: 
Time Series

Historical IBRD Income Statements Data

Description: 

This dataset contains Income Statement data from IBRD’s published financial statements It was compiled from data in our systems as well as by extracting the data from the published Financial Statements documents. The dataset goes as far back as the foundation of the institution (1946). This data has been verified and validated for publication, but does not, in any capacity, replace the official published Financial Statements. An archive for IBRD’s annual Financial Statements is available at www.worldbank.org/financialresults

Type: 
Other

Historical IBRD Balance Sheets Data

Description: 

This dataset contains Balance Sheets data from IBRD’s published financial statements.It was compiled from data in our systems as well as by extracting the data from the published Financial Statements documents. The dataset goes as far back as the foundation of the institution (1946). This data has been verified and validated for publication, but does not, in any capacity, replace the official published Financial Statements. An archive for IBRD’s annual Financial Statements is available at www.worldbank.org/financialresults

Type: 
Other

Albania - Public Buildings Inventory and Energy Profiles

Description: 

The buildings inventory is based on a survey of all Albanian municipalities and ministries that are owners and operators of public buildings. 17 walk-through energy audits were performed for standard buildings in different climatic zones in order to determine typical energy consumption and building characteristics and retrofit needs as well as to extrapolate the data for the whole population of public buildings in the country based on the number and types of buildings data collected.

Type: 
Other

Expected Years of School, Male

Expected Years of School is calculated as the sum of age-specific enrollment rates between ages 4 and 17. Age-specific enrollment rates are approximated using school enrollment rates at different levels: pre-primary enrollment rates approximate the age-specific enrolment rates for 4 and 5 year-olds; the primary rate approximates for 6-11 year-olds; the lower-secondary rate approximates for 12-14 year-olds; and the upper-secondary approximates for 15-17 year-olds. Most recent estimates are used. Year of most recent primary enrollment rate used is shown in data notes.

Harmonized Test Scores

Harmonized Test Scores from major international student achievement testing programs. They are measured in TIMMS-equivalent units, where 300 is minimal attainment and 625 is advanced attainment. Most recent estimates are used. The year of the most recent estimate is shown in the data notes.

Harmonized Test Scores, Male

Harmonized Test Scores from major international student achievement testing programs. They are measured in TIMMS-equivalent units, where 300 is minimal attainment and 625 is advanced attainment. Most recent estimates are used. The year of the most recent estimate is shown in the data notes.

Human Capital Index (HCI), Lower Bound (scale 0-1)

The HCI Lower Bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.

Human Capital Index (HCI), Female, Lower Bound (scale 0-1)

The HCI Lower Bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.

Human Capital Index (HCI), Male, Lower Bound (scale 0-1)

The HCI Lower Bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the lower bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.

Human Capital Index (HCI), Upper Bound (scale 0-1)

The HCI Upper Bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.

Human Capital Index (HCI), Female, Upper Bound (scale 0-1)

The HCI Upper Bound reflects uncertainty in the measurement of the components and the overall index. It is obtained by recalculating the HCI using estimates of the upper bounds of each of the components of the HCI. The range between the upper and lower bound is the uncertainty interval. While the uncertainty intervals constructed here do not have a rigorous statistical interpretation, a rule of thumb is that if for two countries they overlap substantially, the differences between their HCI values are not likely to be practically meaningful.